{"id": "term:alpha", "title": "Alpha", "text": "# Alpha\n\n**Category:** quantitative-methods · **Level:** intro\n\n**Summary:** The excess return of a portfolio over a benchmark or risk-model expectation, attributed to manager skill rather than market exposure.\n\n**Definition:** Alpha (α) is the intercept term in a regression of portfolio returns on factor returns. Operationally, it is the residual return that is not explained by the portfolio's exposure to systematic risk factors (beta to the market, size, value, momentum, etc.). A positive alpha implies the manager generated return beyond what passive exposure to those factors would predict; a negative alpha implies the opposite. Alpha is fragile — it shrinks as more factors are added to the model and as a strategy is replicated.\n\n**Intuition:** Imagine you bet on horses and consistently beat the odds set by the bookies. Your edge is alpha. Beta, by contrast, is just betting at the odds — you might still win, but only because the favorites won.\n\n**In practice:** Allocators rarely accept gross alpha at face value. They decompose it into factor alpha, strategy alpha, and style alpha, then haircut for capacity, crowding, and decay. A 'real' alpha is one that survives a Fama-French 5-factor regression and persists across regimes.\n\n**Example:** A long/short equity fund returns 12% in a year. The benchmark (S&P 500) returns 10%. The fund has a beta of 0.4 to the market. Risk-free rate is 4%. α = R_p − [R_f + β(R_m − R_f)] = 12% − [4% + 0.4 × (10% − 4%)] = 12% − 6.4% = 5.6% → 5.6% Jensen's alpha. The fund earned 5.6 percentage points above what its market exposure justified.\n\n**Pitfalls:** • Confusing total return with alpha — much of what looks like alpha is undisclosed beta to alternative risk factors. • Computing alpha on a too-short window (< 3 years) where it is dominated by noise. • Ignoring fees — gross alpha minus 2/20 often turns negative.", "source": "https://hedgefund.wiki/api/glossary/term/alpha.json", "entity": {"type": "term", "id": "alpha"}, "tokens_approx": 468, "tags": ["performance", "regression", "skill", "factor-model", "quantitative-methods", "intro"]}
{"id": "term:beta", "title": "Beta", "text": "# Beta\n\n**Category:** quantitative-methods · **Level:** intro\n\n**Summary:** The sensitivity of an asset's return to a benchmark's return — the slope of a regression of asset returns on market returns.\n\n**Definition:** Beta (β) measures systematic risk. A β of 1.0 implies the asset moves in lockstep with the benchmark; β of 2.0 implies it amplifies benchmark moves 2×; β of 0 implies independence; β of −1 implies it moves equal-and-opposite. In CAPM, β is the only priced risk: investors demand a premium proportional to β over the risk-free rate. Hedge funds are often marketed as 'low-β' or 'market-neutral' (β ≈ 0).\n\n**Intuition:** Beta is the rope tying you to the boat. A high-β stock yanks you when the boat moves; a low-β stock barely tugs.\n\n**In practice:** Beta is unstable. A stock's β shifts with leverage, sector rotation, and volatility regime. Fund-level β is computed rolling (typically 36-month) and can be decomposed by sector or factor.\n\n**Example:** A stock has a covariance of 0.018 with the S&P 500. The S&P 500 has a variance of 0.012. β = Cov(R_i, R_m) / Var(R_m) = 0.018 / 0.012 = 1.5 → β = 1.5. The stock is expected to move 1.5% for every 1% move in the market.\n\n**Pitfalls:** • Treating beta as constant — it changes regime by regime. • Confusing accounting beta with market beta. • Assuming low-β = low risk; idiosyncratic risk is invisible to β.", "source": "https://hedgefund.wiki/api/glossary/term/beta.json", "entity": {"type": "term", "id": "beta"}, "tokens_approx": 344, "tags": ["systematic-risk", "regression", "factor", "quantitative-methods", "intro"]}
{"id": "term:sharpe-ratio", "title": "Sharpe Ratio", "text": "# Sharpe Ratio\n\n**Category:** quantitative-methods · **Level:** intro\n\n**Summary:** Risk-adjusted return: excess return per unit of total volatility. Sharpe = (R_p − R_f) / σ_p.\n\n**Definition:** Defined by William Sharpe (1966), the Sharpe ratio is excess return over the risk-free rate divided by the standard deviation of excess returns. It is the single most quoted performance number in hedge funds. A Sharpe > 1 is acceptable; > 2 is institutional; > 3 over a long window is rare and merits scrutiny for return-smoothing or hidden tail risk.\n\n**Intuition:** How much pain (volatility) did you suffer per dollar of reward (return)? Higher is better.\n\n**In practice:** Annualize by multiplying monthly Sharpe by √12, daily by √252. Use the same return frequency for numerator and denominator. Always specify the window — Sharpe over 12 months is dominated by luck. Be wary of monthly-marked illiquid books; their reported σ is artificially low and Sharpe artificially high.\n\n**Example:** A fund has monthly excess returns averaging 0.7% with a monthly standard deviation of 1.5%. Monthly Sharpe = 0.7% / 1.5% = 0.467. Annualized = 0.467 × √12 = 1.62 → Annualized Sharpe ≈ 1.62 — a respectable institutional-grade number.\n\n**Pitfalls:** • Comparing Sharpe ratios across different frequencies without annualizing. • Trusting Sharpe > 3 without checking liquidity, return autocorrelation, and tail risk. • Ignoring that Sharpe penalizes upside volatility — use Sortino or Omega for skewed strategies.", "source": "https://hedgefund.wiki/api/glossary/term/sharpe-ratio.json", "entity": {"type": "term", "id": "sharpe-ratio"}, "tokens_approx": 375, "tags": ["performance", "risk-adjusted", "ratio", "quantitative-methods", "intro"]}
{"id": "term:sortino-ratio", "title": "Sortino Ratio", "text": "# Sortino Ratio\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** A Sharpe variant that divides excess return only by downside deviation, rewarding upside volatility.\n\n**Definition:** The Sortino ratio replaces total standard deviation with downside deviation — the standard deviation of returns below a target (usually zero or the risk-free rate). It corrects Sharpe's blindness to skew: a strategy with frequent small wins and rare large losses can have an attractive Sharpe but a poor Sortino. Conversely, a long-vol strategy with occasional large gains will look better under Sortino than Sharpe.\n\n**Intuition:** Volatility on the way up isn't risk — it's reward. Sortino only counts the volatility of losses.\n\n**Example:** Same fund as Sharpe example, but the downside-only standard deviation is 0.9% per month. Monthly Sortino = 0.7% / 0.9% = 0.778. Annualized ≈ 2.69 → Sortino ≈ 2.69 — meaningfully higher than Sharpe because the fund's volatility is asymmetric (mostly upside).", "source": "https://hedgefund.wiki/api/glossary/term/sortino-ratio.json", "entity": {"type": "term", "id": "sortino-ratio"}, "tokens_approx": 252, "tags": ["performance", "downside-risk", "asymmetry", "quantitative-methods", "intermediate"]}
{"id": "term:calmar-ratio", "title": "Calmar Ratio", "text": "# Calmar Ratio\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Annualized return divided by absolute value of maximum drawdown over the same period.\n\n**Definition:** The Calmar ratio (Terry Young, 1991) penalizes large drawdowns rather than volatility. It speaks to investors who care less about wiggles and more about peak-to-trough pain. Typical institutional thresholds: > 0.5 acceptable, > 1.0 strong, > 3.0 elite-and-suspect. Computed over rolling 36-month windows by convention.\n\n**Intuition:** How much annual return did you earn for each percentage point of worst-case loss?\n\n**Example:** A fund returns 14% annualized over 5 years with a max drawdown of 8%. Calmar = 14% / 8% = 1.75 → Calmar = 1.75 — strong on a drawdown-adjusted basis.", "source": "https://hedgefund.wiki/api/glossary/term/calmar-ratio.json", "entity": {"type": "term", "id": "calmar-ratio"}, "tokens_approx": 193, "tags": ["performance", "drawdown-adjusted", "quantitative-methods", "intermediate"]}
{"id": "term:information-ratio", "title": "Information Ratio", "text": "# Information Ratio\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Active return over benchmark divided by tracking error — the Sharpe of relative performance.\n\n**Definition:** The information ratio (IR) measures the consistency with which a manager beats a benchmark, scaled by the volatility of that outperformance. IR = (R_p − R_b) / σ(R_p − R_b). It is the standard metric for benchmarked managers (long-only equity, smart-beta, factor funds). Grinold's 'fundamental law of active management' decomposes IR into IC × √breadth, where IC is the per-bet information coefficient and breadth is the number of independent bets per year.\n\n**Intuition:** Skill (IC) times opportunity (breadth) equals information ratio. A weak signal applied across thousands of names can beat a strong signal on a few.", "source": "https://hedgefund.wiki/api/glossary/term/information-ratio.json", "entity": {"type": "term", "id": "information-ratio"}, "tokens_approx": 206, "tags": ["performance", "benchmark-relative", "skill", "quantitative-methods", "intermediate"]}
{"id": "term:treynor-ratio", "title": "Treynor Ratio", "text": "# Treynor Ratio\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Excess return per unit of systematic risk: (R_p − R_f) / β.\n\n**Definition:** Like Sharpe but uses beta in the denominator instead of total volatility. Appropriate for diversified portfolios where idiosyncratic risk has been diversified away — only systematic risk remains. Less useful for concentrated hedge fund books.", "source": "https://hedgefund.wiki/api/glossary/term/treynor-ratio.json", "entity": {"type": "term", "id": "treynor-ratio"}, "tokens_approx": 102, "tags": ["performance", "systematic-risk", "quantitative-methods", "intermediate"]}
{"id": "term:omega-ratio", "title": "Omega Ratio", "text": "# Omega Ratio\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** Probability-weighted ratio of gains versus losses above and below a threshold return.\n\n**Definition:** Ω(τ) = ∫_τ^∞ (1 − F(r)) dr / ∫_{-∞}^τ F(r) dr, where F is the cumulative distribution of returns and τ is a target. Unlike Sharpe and Sortino, Omega uses the entire return distribution — it is not blind to higher moments. Omega(0%) > 1 means more probability-weighted gain than loss above zero.", "source": "https://hedgefund.wiki/api/glossary/term/omega-ratio.json", "entity": {"type": "term", "id": "omega-ratio"}, "tokens_approx": 120, "tags": ["performance", "distribution", "quantitative-methods", "advanced"]}
{"id": "term:max-drawdown", "title": "Maximum Drawdown", "text": "# Maximum Drawdown\n\n**Category:** risk-management · **Level:** intro\n\n**Summary:** The largest peak-to-trough percentage decline in NAV over a specified window.\n\n**Definition:** MDD = max over t,s≤t of (NAV_s − NAV_t) / NAV_s. It is the single most psychologically meaningful risk measure: investors redeem on drawdowns, not on volatility. A 50% drawdown requires a 100% gain to recover, so MDD asymmetry is severe. Hedge funds typically report MDD over the strategy's full life, plus rolling 12- and 36-month windows.\n\n**Intuition:** Worst pain ever felt. The number that triggers redemptions and ends careers.\n\n**In practice:** Allocators model 'time to recovery' alongside MDD: a 15% drawdown that recovers in 3 months is acceptable; the same 15% that takes 3 years is fatal.\n\n**Example:** Fund NAV path: 100 → 110 → 130 → 100 → 120 → 95 → 140 Peaks: 130 then 120. Trough after 130 is 95. (95 − 130)/130 = −26.9% → MDD = 26.9%", "source": "https://hedgefund.wiki/api/glossary/term/max-drawdown.json", "entity": {"type": "term", "id": "max-drawdown"}, "tokens_approx": 232, "tags": ["risk", "drawdown", "psychological", "risk-management", "intro"]}
{"id": "term:ulcer-index", "title": "Ulcer Index", "text": "# Ulcer Index\n\n**Category:** risk-management · **Level:** advanced\n\n**Summary:** Quadratic-mean of percentage drawdowns from running highs — captures depth and duration of pain.\n\n**Definition:** UI = √(Σ D_t² / N), where D_t is the percentage drawdown from the running high at time t. Unlike MDD which is a single point, the Ulcer Index integrates over the entire drawdown experience. Peter Martin (1987) named it for the gastric distress investors feel during prolonged underwater periods.", "source": "https://hedgefund.wiki/api/glossary/term/ulcer-index.json", "entity": {"type": "term", "id": "ulcer-index"}, "tokens_approx": 122, "tags": ["risk", "drawdown", "duration", "risk-management", "advanced"]}
{"id": "term:value-at-risk", "title": "Value at Risk (VaR)", "text": "# Value at Risk (VaR)\n_(VaR)_\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** The loss threshold that will not be exceeded with a specified probability over a specified horizon.\n\n**Definition:** 1-day 99% VaR of $10m means: 'On 99 of 100 trading days, we expect to lose less than $10m.' VaR is computed three ways: (1) parametric (assume normal returns, use σ × Z-score), (2) historical (read the percentile off actual return history), (3) Monte Carlo (simulate from a fitted distribution). All three are coherent only under restrictive assumptions; none captures tail dependence well. VaR's most cited critique: it tells you nothing about *how bad* the 1% looks. That's where Expected Shortfall steps in.\n\n**Intuition:** On a 'normal bad day', this is the most you should lose. On an abnormal bad day, all bets are off.\n\n**Example:** Portfolio value $100m, daily volatility 1.2%, normal distribution assumed, 99% confidence. VaR_99 = $100m × 1.2% × 2.326 = $2.79m → 1-day 99% VaR ≈ $2.79m\n\n**Pitfalls:** • Treating VaR as a worst-case loss — it is explicitly NOT the worst case. • Using a normal distribution for fat-tailed return series. • Ignoring that VaR is not subadditive — it can violate diversification logic.", "source": "https://hedgefund.wiki/api/glossary/term/value-at-risk.json", "entity": {"type": "term", "id": "value-at-risk"}, "tokens_approx": 310, "tags": ["risk", "tail", "regulatory", "risk-management", "intermediate"]}
{"id": "term:expected-shortfall", "title": "Expected Shortfall", "text": "# Expected Shortfall\n_(ES / CVaR)_\n\n**Category:** risk-management · **Level:** advanced\n\n**Summary:** Average loss in the worst α% of cases — the conditional expectation of loss given that loss exceeds VaR.\n\n**Definition:** ES_α = E[L | L > VaR_α]. Unlike VaR, ES is coherent (subadditive) and sensitive to tail shape. Basel III FRTB replaced VaR with ES at the 97.5% level for market risk capital. For a normal distribution at the 99% level, ES ≈ 1.146 × VaR.", "source": "https://hedgefund.wiki/api/glossary/term/expected-shortfall.json", "entity": {"type": "term", "id": "expected-shortfall"}, "tokens_approx": 115, "tags": ["risk", "tail", "regulatory", "basel", "risk-management", "advanced"]}
{"id": "term:stress-test", "title": "Stress Test", "text": "# Stress Test\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** Re-pricing the book under hypothetical or historical shock scenarios to estimate tail loss.\n\n**Definition:** Stress tests bypass distributional assumptions and ask 'what if?' Common scenarios: (1) historical replays — Oct 1987, Aug 1998 LTCM, Sep 2008 Lehman, Feb 2018 Volmageddon, March 2020 COVID, Sep 2022 UK gilts. (2) hypothetical — rates +200bp, oil −50%, USD/JPY +10%. (3) reverse stress — find the smallest shock that breaches a survival threshold. Regulators (Form PF, AIFMD) require regular stress reporting.", "source": "https://hedgefund.wiki/api/glossary/term/stress-test.json", "entity": {"type": "term", "id": "stress-test"}, "tokens_approx": 150, "tags": ["risk", "scenario", "regulatory", "risk-management", "intermediate"]}
{"id": "term:two-and-twenty", "title": "Two-and-Twenty", "text": "# Two-and-Twenty\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** The classic hedge fund fee structure: 2% annual management fee plus 20% of profits above a hurdle.\n\n**Definition:** Originated with A.W. Jones in 1949 (who took 20% but no management fee, mirroring 16th-century Phoenician sea-captain shares). Standard for decades, now under sustained pressure: industry-average effective fees by 2025 sat closer to 1.4 / 17. Multi-strat pod shops use 'pass-through' expense structures that often exceed 2/20 in absolute cost. The 20% is typically subject to a high-water mark and sometimes a hurdle rate.\n\n**Intuition:** Two cents on the dollar each year just for showing up. Twenty cents on every dollar of profit you make.\n\n**In practice:** Allocators negotiate fees down via founder share classes (1/10), seed deals (revenue share), and capacity rights. Pod shops counter with pass-through fees that may run 5-8% all-in but produce uncorrelated 12-15% net returns.", "source": "https://hedgefund.wiki/api/glossary/term/two-and-twenty.json", "entity": {"type": "term", "id": "two-and-twenty"}, "tokens_approx": 245, "tags": ["fees", "compensation", "structure", "fund-operations", "intro"]}
{"id": "term:high-water-mark", "title": "High-Water Mark", "text": "# High-Water Mark\n_(HWM)_\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** The highest NAV per share an investor's capital has ever reached, above which performance fees may again be charged.\n\n**Definition:** Performance fees are charged only on NAV increases above the investor's HWM. After a drawdown, the manager must first earn back to the HWM before any further incentive fee accrues. HWMs are typically computed per investor (or per contribution lot) and per share class. After deep drawdowns, HWMs become unattainable and PMs/teams often spin off to reset them — 'HWM washout' is a common cause of fund closures post-crisis.", "source": "https://hedgefund.wiki/api/glossary/term/high-water-mark.json", "entity": {"type": "term", "id": "high-water-mark"}, "tokens_approx": 161, "tags": ["fees", "structure", "incentive", "fund-operations", "intro"]}
{"id": "term:hurdle-rate", "title": "Hurdle Rate", "text": "# Hurdle Rate\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** A minimum return that must be achieved before performance fees accrue.\n\n**Definition:** Two flavors: (1) hard hurdle — performance fees only on returns above the hurdle (e.g., return = 12%, hurdle = 6%, fee on 6%); (2) soft hurdle with catch-up — once the hurdle is cleared, performance fee applies to the entire return. Hurdles are commonly set at the risk-free rate, T-bills + a spread, or a benchmark index. Increasingly common in private credit, infrastructure, and 2020s vintage hedge funds raising in a high-rate world.", "source": "https://hedgefund.wiki/api/glossary/term/hurdle-rate.json", "entity": {"type": "term", "id": "hurdle-rate"}, "tokens_approx": 150, "tags": ["fees", "structure", "fund-operations", "intro"]}
{"id": "term:crystallisation", "title": "Crystallisation", "text": "# Crystallisation\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** The point at which accrued performance fees become payable to the manager and the high-water mark resets.\n\n**Definition:** Most hedge funds crystallise annually (Dec 31), but quarterly and monthly crystallisations exist for higher-frequency vehicles. Once crystallised, the performance fee leaves investor capital permanently — even a subsequent drawdown does not claw it back. This mechanic is a key source of GP–LP friction in volatile years.", "source": "https://hedgefund.wiki/api/glossary/term/crystallisation.json", "entity": {"type": "term", "id": "crystallisation"}, "tokens_approx": 133, "tags": ["fees", "accounting", "fund-operations", "intermediate"]}
{"id": "term:nav", "title": "Net Asset Value", "text": "# Net Asset Value\n_(NAV)_\n\n**Category:** accounting-valuation · **Level:** intro\n\n**Summary:** Total fund assets minus liabilities, divided by units outstanding — the per-share value of the fund.\n\n**Definition:** NAV is struck by the fund administrator on each valuation date (monthly is standard; weekly or daily for liquid strategies). It uses the fair-value hierarchy (Level 1: quoted prices, Level 2: observable inputs, Level 3: model-based). NAV drives subscriptions, redemptions, performance fees, and investor reporting. NAV manipulation — typically via Level 3 mark stuffing — has been the proximate cause of multiple high-profile blowups.", "source": "https://hedgefund.wiki/api/glossary/term/nav.json", "entity": {"type": "term", "id": "nav"}, "tokens_approx": 161, "tags": ["accounting", "valuation", "operations", "accounting-valuation", "intro"]}
{"id": "term:side-pocket", "title": "Side Pocket", "text": "# Side Pocket\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A separate accounting bucket within a hedge fund holding illiquid or hard-to-value investments, segregated from the main NAV.\n\n**Definition:** When a position becomes illiquid (e.g., delisted, restricted, in litigation), it can be moved to a side pocket. New investors do not participate; existing investors hold their pro-rata share until realization. Side pockets prevent stale-mark dilution between subscribers and redeemers. They proliferated during 2008 — by mid-2009 over 20% of hedge fund assets sat in side pockets — and have since been governed more tightly by SEC guidance and offering documents.", "source": "https://hedgefund.wiki/api/glossary/term/side-pocket.json", "entity": {"type": "term", "id": "side-pocket"}, "tokens_approx": 172, "tags": ["liquidity", "structure", "operations", "fund-operations", "intermediate"]}
{"id": "term:gate", "title": "Gate", "text": "# Gate\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A redemption restriction limiting the percentage of the fund that may be withdrawn on any single redemption date.\n\n**Definition:** Two main types: (1) investor-level gate — caps each LP's redemption at, say, 25% of their stake per quarter; (2) fund-level gate — caps total redemptions at, say, 10% of fund AUM per quarter, pro-rated across redemption requests. Gates protect remaining LPs from a fire-sale that would crystallize losses. Gating is a powerful but reputationally costly tool — once a fund gates, expectations are reset and brand value rarely recovers fully.", "source": "https://hedgefund.wiki/api/glossary/term/gate.json", "entity": {"type": "term", "id": "gate"}, "tokens_approx": 162, "tags": ["liquidity", "structure", "fund-operations", "intermediate"]}
{"id": "term:lock-up", "title": "Lock-up", "text": "# Lock-up\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** A period during which an investor cannot redeem capital from the fund.\n\n**Definition:** Hard lock-up: no redemptions permitted; soft lock-up: redemptions permitted with a fee (typically 2–5%) that is returned to the fund. Standard hedge fund lock-ups are 1 year; activist and credit funds run 2–5 years; PE-style hybrids 5–10 years. Founder share classes often offer lower fees in exchange for longer lock-ups. Lock-ups help managers run higher gross exposure without forced-selling risk.", "source": "https://hedgefund.wiki/api/glossary/term/lock-up.json", "entity": {"type": "term", "id": "lock-up"}, "tokens_approx": 140, "tags": ["liquidity", "structure", "fund-operations", "intro"]}
{"id": "term:side-letter", "title": "Side Letter", "text": "# Side Letter\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A bilateral agreement between the fund and a specific investor granting bespoke terms not in the LPA.\n\n**Definition:** Common side-letter terms: most-favored-nation (MFN), fee discounts, capacity rights, additional reporting (transparency, position-level), shorter notice/lock-up, reduced redemption fees, key-person provisions. The MFN is the central feature — when one LP gets a better term, MFN'd LPs receive it automatically. SEC Rule 206(4)-8 prohibits side letters that materially disadvantage other investors.", "source": "https://hedgefund.wiki/api/glossary/term/side-letter.json", "entity": {"type": "term", "id": "side-letter"}, "tokens_approx": 150, "tags": ["legal", "structure", "negotiation", "fund-operations", "intermediate"]}
{"id": "term:master-feeder", "title": "Master-Feeder", "text": "# Master-Feeder\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** Two or more feeder funds in different jurisdictions that pool assets in a single master fund where trading actually occurs.\n\n**Definition:** Standard structure: (1) Onshore feeder — Delaware LP, for US taxable investors; (2) Offshore feeder — Cayman Ltd, for US tax-exempt and non-US investors; (3) Master — Cayman Ltd, where assets are held and trades booked. Each feeder owns shares of the master proportional to its capital. The structure achieves tax neutrality (US LPs get K-1s, offshore investors get blocker treatment), avoids UBTI for tax-exempts, and allows a single trading book.", "source": "https://hedgefund.wiki/api/glossary/term/master-feeder.json", "entity": {"type": "term", "id": "master-feeder"}, "tokens_approx": 169, "tags": ["structure", "tax", "international", "fund-operations", "intermediate"]}
{"id": "term:fund-of-funds", "title": "Fund of Funds", "text": "# Fund of Funds\n_(FoF)_\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** A fund that allocates to a portfolio of underlying hedge funds rather than trading directly.\n\n**Definition:** FoFs offer diversification, manager-selection expertise, and (for smaller LPs) access to capacity-constrained funds. They charge an additional fee layer (historically 1/10 on top of underlying 2/20). The post-2008 era saw mass FoF redemptions; the model survives in OCIO, retirement, and emerging-manager seeding contexts. Modern variants: 'multi-manager' (single-shop pod platform like Citadel/Millennium/Point72) which is the structural successor to traditional FoF.", "source": "https://hedgefund.wiki/api/glossary/term/fund-of-funds.json", "entity": {"type": "term", "id": "fund-of-funds"}, "tokens_approx": 166, "tags": ["structure", "allocation", "fund-operations", "intro"]}
{"id": "term:prime-broker", "title": "Prime Broker", "text": "# Prime Broker\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** A bank that provides hedge funds with execution, financing, securities lending, custody, and reporting under one roof.\n\n**Definition:** Core services: (1) execution & DMA, (2) margin financing for long positions, (3) securities lending for short positions, (4) custody, (5) consolidated reporting (the 'PB report'). Top-tier PBs in 2026: Goldman, Morgan Stanley, JPMorgan, BofA, Barclays, UBS. Funds typically run 2–4 PBs to diversify counterparty risk after Lehman 2008, when hundreds of funds had assets frozen at Lehman International (London Rule 7).", "source": "https://hedgefund.wiki/api/glossary/term/prime-broker.json", "entity": {"type": "term", "id": "prime-broker"}, "tokens_approx": 158, "tags": ["counterparty", "operations", "infrastructure", "fund-operations", "intro"]}
{"id": "term:long-short-equity", "title": "Long/Short Equity", "text": "# Long/Short Equity\n\n**Category:** hedge-fund-strategies · **Level:** intro\n\n**Summary:** A strategy that holds long positions in expected outperformers and short positions in expected underperformers.\n\n**Definition:** Originating with A.W. Jones (1949), L/S equity is the prototypical hedge fund strategy. Net exposure varies from market-neutral (≈0%) to directional (60–80% net long). Gross exposure typically 150–300%. Alpha sources: stock-picking, sector rotation, timing of net exposure. The strategy's beta is tunable: the manager chooses how much market risk to retain. ~30% of global hedge fund AUM in 2026 follows some L/S equity variant.", "source": "https://hedgefund.wiki/api/glossary/term/long-short-equity.json", "entity": {"type": "term", "id": "long-short-equity"}, "tokens_approx": 161, "tags": ["strategy", "equity", "fundamental", "hedge-fund-strategies", "intro"]}
{"id": "term:market-neutral", "title": "Market Neutral", "text": "# Market Neutral\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** A long/short strategy structured so that net market beta is approximately zero.\n\n**Definition:** Three main flavors: (1) dollar-neutral (long $ = short $); (2) beta-neutral (Σ β_long w_long = Σ β_short w_short); (3) factor-neutral (additional constraints to zero out exposure to size, value, momentum, sector). Returns come from idiosyncratic stock selection, not from market direction. Modern multi-manager pods almost always run beta-neutral and increasingly factor-neutral.", "source": "https://hedgefund.wiki/api/glossary/term/market-neutral.json", "entity": {"type": "term", "id": "market-neutral"}, "tokens_approx": 142, "tags": ["strategy", "equity", "neutral", "hedge-fund-strategies", "intermediate"]}
{"id": "term:merger-arbitrage", "title": "Merger Arbitrage", "text": "# Merger Arbitrage\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** Capturing the spread between an announced acquisition price and the target's market price by going long the target (and short the acquirer in stock deals).\n\n**Definition:** Cash deal: long target only. Stock deal: long target, short acquirer in the announced exchange ratio. P&L = deal price − purchase price, less hedge cost, less the probability-weighted loss if the deal breaks. Skill is in handicapping break risk: regulatory (HSR, FTC, EU, CFIUS, NSIA in UK), shareholder vote, financing condition, MAC clauses. 2024–2026 saw deal-break volatility spike on antitrust scrutiny under FTC Khan and EU Vestager 2.0.", "source": "https://hedgefund.wiki/api/glossary/term/merger-arbitrage.json", "entity": {"type": "term", "id": "merger-arbitrage"}, "tokens_approx": 178, "tags": ["strategy", "event-driven", "arbitrage", "hedge-fund-strategies", "intermediate"]}
{"id": "term:convertible-arbitrage", "title": "Convertible Arbitrage", "text": "# Convertible Arbitrage\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** Long the convertible bond, short the underlying stock in delta-equivalent quantity, harvesting gamma, vega, and credit spread carry.\n\n**Definition:** A convertible bond decomposes into a straight bond plus a long equity call. Convert arbs hedge the equity component (delta-hedging the embedded call) and isolate exposures to: (1) realized vs implied volatility (vega), (2) credit spread tightening, (3) gamma scalping income, (4) bond floor. The strategy nearly died in 2008 when forced deleveraging crushed the asset class, then recovered as new issuance returned. Capacity: limited by issuance pace (~$80–120bn/yr globally).", "source": "https://hedgefund.wiki/api/glossary/term/convertible-arbitrage.json", "entity": {"type": "term", "id": "convertible-arbitrage"}, "tokens_approx": 180, "tags": ["strategy", "relative-value", "convertibles", "hedge-fund-strategies", "advanced"]}
{"id": "term:global-macro", "title": "Global Macro", "text": "# Global Macro\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** Top-down directional and relative-value bets across rates, FX, equities, and commodities driven by macroeconomic theses.\n\n**Definition:** The classical 'big bet' strategy associated with Soros, Druckenmiller, Bacon, Tudor Jones. Trade expression typically uses futures, swaps, and options for capital efficiency. Sub-styles: discretionary macro, systematic macro, EM-focused, rates-focused, commodity-focused. Has historically excelled in regime-change markets (1992 ERM, 2008 GFC, 2022 inflation) and underperformed in compressed-vol bull markets (2014–2019).", "source": "https://hedgefund.wiki/api/glossary/term/global-macro.json", "entity": {"type": "term", "id": "global-macro"}, "tokens_approx": 163, "tags": ["strategy", "macro", "discretionary", "hedge-fund-strategies", "intermediate"]}
{"id": "term:managed-futures", "title": "Managed Futures", "text": "# Managed Futures\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** Systematic trading of liquid futures contracts, predominantly using trend-following or short-term mean-reversion signals.\n\n**Definition:** Regulated by the CFTC under the CTA (Commodity Trading Advisor) registration. The classic strategy is medium-term trend following across 100+ futures markets (rates, FX, equity indices, commodities). The 2022 inflation surge produced the strategy's best year since 2008 (SG Trend Index +27%); the post-2009 zero-rate era was the worst. Capacity is enormous (multi-trillion in liquid futures), but crowding into similar trend signals creates synchronized drawdowns.", "source": "https://hedgefund.wiki/api/glossary/term/managed-futures.json", "entity": {"type": "term", "id": "managed-futures"}, "tokens_approx": 174, "tags": ["strategy", "systematic", "trend", "hedge-fund-strategies", "intermediate"]}
{"id": "term:statistical-arbitrage", "title": "Statistical Arbitrage", "text": "# Statistical Arbitrage\n_(Stat Arb)_\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** High-breadth, short-horizon mean-reversion or relative-value trading driven by statistical signals.\n\n**Definition:** Originated at Morgan Stanley's APT group (Bamberger, Tartaglia) in the 1980s, then commercialized by D.E. Shaw, Renaissance, and PDT. Modern stat arb runs thousands of positions, holding period seconds-to-days, with portfolio-level Sharpe targets of 4–6 net of costs. The original pairs-trading signal has decayed; today's signals come from order-book microstructure, alternative data, and ML-derived embeddings.", "source": "https://hedgefund.wiki/api/glossary/term/statistical-arbitrage.json", "entity": {"type": "term", "id": "statistical-arbitrage"}, "tokens_approx": 159, "tags": ["strategy", "quant", "high-frequency", "hedge-fund-strategies", "advanced"]}
{"id": "term:pairs-trading", "title": "Pairs Trading", "text": "# Pairs Trading\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** Long one security, short a closely related security, betting on convergence of their relative price.\n\n**Definition:** The simplest stat-arb form: identify two cointegrated securities (often within the same sector — Coke/Pepsi, Exxon/Chevron), trade the spread when it diverges from its long-run mean. Signal generation typically uses an Ornstein-Uhlenbeck model. The strategy decayed sharply post-2003 as competition compressed spreads; modern variants use baskets of dozens of names rather than single pairs.", "source": "https://hedgefund.wiki/api/glossary/term/pairs-trading.json", "entity": {"type": "term", "id": "pairs-trading"}, "tokens_approx": 150, "tags": ["strategy", "quant", "mean-reversion", "hedge-fund-strategies", "intermediate"]}
{"id": "term:multi-strategy-pod", "title": "Multi-Strategy Pod", "text": "# Multi-Strategy Pod\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** A platform that allocates capital across many independent portfolio managers (pods), each with strict risk limits, diversifying alpha across uncorrelated bets.\n\n**Definition:** The dominant institutional hedge fund model of the 2020s. Examples: Citadel, Millennium, Point72, ExodusPoint, Balyasny, Schonfeld, Walleye. Each PM (or 'pod') runs a sub-book under a tight stop-loss (typically 5–8% peak-to-trough), with risk and execution centralized. Pass-through expense structures (often 5–8% gross) fund infrastructure, technology, and PM compensation. Net returns of 10–15% with Sharpe of 2–4 have made the model an LP favorite, but capacity is increasingly constrained.", "source": "https://hedgefund.wiki/api/glossary/term/multi-strategy-pod.json", "entity": {"type": "term", "id": "multi-strategy-pod"}, "tokens_approx": 192, "tags": ["strategy", "structure", "multi-manager", "hedge-fund-strategies", "intermediate"]}
{"id": "term:delta", "title": "Delta (Δ)", "text": "# Delta (Δ)\n\n**Category:** derivatives-options · **Level:** intro\n\n**Summary:** The change in option price per unit change in the underlying asset's price.\n\n**Definition:** Δ = ∂V/∂S. For a vanilla call, Δ ranges from 0 (deep OTM) to 1 (deep ITM); for a put, from −1 to 0. ATM options have |Δ| ≈ 0.5. Delta also approximates the risk-neutral probability that the option finishes in the money. Hedgers maintain delta-neutral books by trading the underlying in quantity Δ × N (where N is the option position size).", "source": "https://hedgefund.wiki/api/glossary/term/delta.json", "entity": {"type": "term", "id": "delta"}, "tokens_approx": 128, "tags": ["greeks", "options", "derivatives-options", "intro"]}
{"id": "term:gamma", "title": "Gamma (Γ)", "text": "# Gamma (Γ)\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** The rate of change of delta with respect to the underlying — the option's convexity.\n\n**Definition:** Γ = ∂²V/∂S² = ∂Δ/∂S. Maximum at the strike, decreasing away from it. Long gamma = profit from realized volatility (gamma scalping); short gamma = collect theta but lose if vol arrives. The 'gamma squeeze' phenomenon (e.g., GameStop Jan 2021): dealer short-gamma positioning forces them to buy as price rises, amplifying the move. Dealer gamma positioning (the 'gamma map') has become a watched intraday signal.", "source": "https://hedgefund.wiki/api/glossary/term/gamma.json", "entity": {"type": "term", "id": "gamma"}, "tokens_approx": 149, "tags": ["greeks", "convexity", "derivatives-options", "intermediate"]}
{"id": "term:vega", "title": "Vega (ν)", "text": "# Vega (ν)\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** The change in option price per 1-percentage-point change in implied volatility.\n\n**Definition:** ν = ∂V/∂σ. Vega is highest for ATM options with longer maturities. Vega is not a Greek letter but the convention persists. Vega-trading strategies isolate exposure to implied volatility level and term structure: long vega = long IV; vega-neutral = isolate other Greeks.", "source": "https://hedgefund.wiki/api/glossary/term/vega.json", "entity": {"type": "term", "id": "vega"}, "tokens_approx": 113, "tags": ["greeks", "volatility", "derivatives-options", "intermediate"]}
{"id": "term:theta", "title": "Theta (Θ)", "text": "# Theta (Θ)\n\n**Category:** derivatives-options · **Level:** intro\n\n**Summary:** The rate at which an option loses value with the passage of time, holding everything else constant.\n\n**Definition:** Θ = ∂V/∂t. Almost always negative for long option positions: each day, time value decays. Decay accelerates as expiry approaches (theta is roughly proportional to 1/√(T−t)). Short premium strategies (covered calls, iron condors, short straddles) collect theta but pay realized vol; the trade-off is the central tension of premium selling.", "source": "https://hedgefund.wiki/api/glossary/term/theta.json", "entity": {"type": "term", "id": "theta"}, "tokens_approx": 133, "tags": ["greeks", "time-decay", "derivatives-options", "intro"]}
{"id": "term:rho", "title": "Rho (ρ)", "text": "# Rho (ρ)\n\n**Category:** derivatives-options · **Level:** advanced\n\n**Summary:** The change in option price per 1-percentage-point change in the risk-free rate.\n\n**Definition:** ρ = ∂V/∂r. Calls have positive rho; puts have negative rho. Rho exposure is small for short-dated equity options but significant for long-dated rate options and FX options where the rate differential drives the forward.", "source": "https://hedgefund.wiki/api/glossary/term/rho.json", "entity": {"type": "term", "id": "rho"}, "tokens_approx": 99, "tags": ["greeks", "rates", "derivatives-options", "advanced"]}
{"id": "term:implied-volatility", "title": "Implied Volatility", "text": "# Implied Volatility\n_(IV)_\n\n**Category:** derivatives-options · **Level:** intro\n\n**Summary:** The volatility input to an option pricing model that makes the model's output equal the option's market price.\n\n**Definition:** IV is what the market 'thinks' future realized volatility will be — it is forward-looking and embedded in option prices. The IV surface is a 2D function of strike (skew) and maturity (term structure). The CBOE VIX is the 30-day SPX IV. Hedge funds trade IV vs realized (vol arb), trade IV term structure (calendar spreads), and trade IV skew (risk reversals). When realized > implied, premium sellers lose; when realized < implied, they win.", "source": "https://hedgefund.wiki/api/glossary/term/implied-volatility.json", "entity": {"type": "term", "id": "implied-volatility"}, "tokens_approx": 166, "tags": ["volatility", "options", "options-pricing", "derivatives-options", "intro"]}
{"id": "term:vix", "title": "VIX", "text": "# VIX\n\n**Category:** derivatives-options · **Level:** intro\n\n**Summary:** The CBOE Volatility Index — 30-day implied volatility of the S&P 500, derived from a strip of SPX options.\n\n**Definition:** Computed continuously from out-of-the-money SPX option prices using a model-free formula related to the variance swap rate. Often called the 'fear index': spikes during equity selloffs (87 in Oct 2008, 82 in March 2020). Tradable via VIX futures (VX), VIX options, and ETPs (VXX, UVXY). The VIX term structure (front to back) typically slopes upward (contango) — leading to negative roll yield in long-vol ETPs, the source of long-vol's structural drag.", "source": "https://hedgefund.wiki/api/glossary/term/vix.json", "entity": {"type": "term", "id": "vix"}, "tokens_approx": 162, "tags": ["volatility", "index", "derivatives-options", "intro"]}
{"id": "term:vol-skew", "title": "Volatility Skew", "text": "# Volatility Skew\n\n**Category:** derivatives-options · **Level:** advanced\n\n**Summary:** The pattern by which implied volatility varies with strike, holding maturity constant.\n\n**Definition:** In equity index options, OTM puts trade at higher IV than OTM calls — a 'put skew' or 'risk reversal' that reflects demand for downside hedging. Single stocks often show smile (high IV both wings). FX options show smile or smirk. Skew is itself tradeable: long the wings vs short the body (a butterfly). The skew steepened structurally after Black Monday 1987.", "source": "https://hedgefund.wiki/api/glossary/term/vol-skew.json", "entity": {"type": "term", "id": "vol-skew"}, "tokens_approx": 138, "tags": ["volatility", "options", "structure", "derivatives-options", "advanced"]}
{"id": "term:carry-trade", "title": "Carry Trade", "text": "# Carry Trade\n\n**Category:** global-markets · **Level:** intro\n\n**Summary:** Borrow in a low-yielding currency, invest in a high-yielding one, harvest the rate differential.\n\n**Definition:** The canonical FX carry trade: short JPY, long AUD or BRL or TRY, earn the rate differential. The trade is profitable on average (covered interest parity is violated empirically) but suffers periodic violent unwinds when risk-off triggers reversal — the so-called 'carry crash'. The 1998 LTCM/Russia and 2008 GFC carry unwinds were textbook. Generalized 'carry' applies to fixed income (long the curve), commodities (long backwardated assets), and equities (long high-dividend names).", "source": "https://hedgefund.wiki/api/glossary/term/carry-trade.json", "entity": {"type": "term", "id": "carry-trade"}, "tokens_approx": 168, "tags": ["macro", "fx", "carry", "global-markets", "intro"]}
{"id": "term:contango", "title": "Contango", "text": "# Contango\n\n**Category:** commodities-futures · **Level:** intro\n\n**Summary:** A futures curve in which longer-dated contracts trade at higher prices than nearer-dated ones.\n\n**Definition:** Typical of storable commodities where storage costs and convenience yield combine to produce upward-sloping curves. Long-only commodity holders (passive ETFs, index funds) suffer negative roll yield in contango: each month they sell the front month cheap and buy the next month expensive. The infamous April 2020 WTI front-month went negative on storage saturation while the back of the curve stayed positive — extreme contango.", "source": "https://hedgefund.wiki/api/glossary/term/contango.json", "entity": {"type": "term", "id": "contango"}, "tokens_approx": 154, "tags": ["commodities", "term-structure", "commodities-futures", "intro"]}
{"id": "term:backwardation", "title": "Backwardation", "text": "# Backwardation\n\n**Category:** commodities-futures · **Level:** intro\n\n**Summary:** A futures curve in which longer-dated contracts trade at lower prices than nearer-dated ones.\n\n**Definition:** Typical when near-term supply is tight (high convenience yield) — physical holders pay a premium for immediate delivery. Long futures holders earn positive roll yield in backwardation. Crude oil, copper, and natural gas frequently exhibit backwardation in tight markets.", "source": "https://hedgefund.wiki/api/glossary/term/backwardation.json", "entity": {"type": "term", "id": "backwardation"}, "tokens_approx": 116, "tags": ["commodities", "term-structure", "commodities-futures", "intro"]}
{"id": "term:duration", "title": "Duration", "text": "# Duration\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** The price sensitivity of a bond to a 1-percentage-point change in interest rates, expressed in years.\n\n**Definition:** Macaulay duration is the weighted average time to a bond's cash flows. Modified duration = Macaulay / (1 + y/n) and approximates % price change for a 1% rate move: ΔP/P ≈ −D_mod × Δy. Effective duration accounts for embedded options (callable/puttable bonds, MBS). Portfolio duration aggregates by market-value weights. The 2022 bond rout (US Aggregate −13%) was a textbook duration shock as 30-year Treasuries fell ~30% on a 200bp rate move.", "source": "https://hedgefund.wiki/api/glossary/term/duration.json", "entity": {"type": "term", "id": "duration"}, "tokens_approx": 161, "tags": ["fixed-income", "rates", "sensitivity", "fixed-income-credit", "intermediate"]}
{"id": "term:convexity", "title": "Convexity", "text": "# Convexity\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** The second-order rate sensitivity of a bond price — captures the curvature of the price-yield relationship.\n\n**Definition:** ΔP/P ≈ −D × Δy + ½ × C × (Δy)². Convexity is positive for vanilla bonds (price rises faster than it falls for symmetric yield moves), negative for callable bonds and MBS at certain yields. Long convexity is a structural advantage; convexity hedging by mortgage portfolios drives episodic 'convexity events' — large rate moves that force MBS holders to rebalance, amplifying the move.", "source": "https://hedgefund.wiki/api/glossary/term/convexity.json", "entity": {"type": "term", "id": "convexity"}, "tokens_approx": 147, "tags": ["fixed-income", "rates", "convexity", "fixed-income-credit", "advanced"]}
{"id": "term:credit-default-swap", "title": "Credit Default Swap", "text": "# Credit Default Swap\n_(CDS)_\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** An OTC contract in which the protection buyer pays a periodic premium and receives a payout if a reference entity defaults.\n\n**Definition:** Protection buyer pays the running spread (in bps/yr); seller pays par minus recovery upon a credit event (failure to pay, restructuring, bankruptcy). Standardized post-2009 with Big Bang and Small Bang protocols, central clearing via ICE Clear Credit / LCH. The CDS market (≈$8tn notional in 2026) is dominated by index trades on CDX (US) and iTraxx (Europe). Single-name CDS volumes have shrunk dramatically since 2014. CDS pricing implies default probability under risk-neutral measure: PD ≈ spread / (1 − R).", "source": "https://hedgefund.wiki/api/glossary/term/credit-default-swap.json", "entity": {"type": "term", "id": "credit-default-swap"}, "tokens_approx": 189, "tags": ["credit", "derivatives", "swap", "fixed-income-credit", "intermediate"]}
{"id": "term:distressed-debt", "title": "Distressed Debt", "text": "# Distressed Debt\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** Investing in the debt of companies trading at deeply discounted prices due to actual or perceived financial distress.\n\n**Definition:** Sub-strategies: (1) trading distressed — buying secondary debt in stressed names; (2) loan-to-own — accumulating fulcrum debt to convert to equity through restructuring; (3) DIP financing — providing capital during Chapter 11. Returns driven by event timing (file/exit), recovery analysis, fulcrum security identification, and committee work. Major practitioners: Oaktree, Apollo, Elliott, Davidson Kempner, King Street, Silver Point.", "source": "https://hedgefund.wiki/api/glossary/term/distressed-debt.json", "entity": {"type": "term", "id": "distressed-debt"}, "tokens_approx": 165, "tags": ["strategy", "credit", "distressed", "event-driven", "hedge-fund-strategies", "advanced"]}
{"id": "term:form-adv", "title": "Form ADV", "text": "# Form ADV\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** The SEC registration form for investment advisers, with public disclosures (Part 1) and a brochure (Part 2).\n\n**Definition:** Required of all SEC-registered investment advisers. Part 1A: structured data on AUM, employee count, advisory business, custody, disciplinary history. Part 1B: state filers. Part 2A: client-facing brochure on services, fees, conflicts. Part 2B: brochure supplement on supervised persons. Part 3 (Form CRS): retail-relationship summary. Filed annually within 90 days of fiscal year end via IARD. Public access via SEC IAPD.", "source": "https://hedgefund.wiki/api/glossary/term/form-adv.json", "entity": {"type": "term", "id": "form-adv"}, "tokens_approx": 159, "tags": ["regulation", "filing", "sec", "regulatory-compliance", "intermediate"]}
{"id": "term:form-pf", "title": "Form PF", "text": "# Form PF\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** Confidential SEC filing by private fund advisers reporting fund-level risk, leverage, and exposure data.\n\n**Definition:** Required of investment advisers with > $150m in private fund AUM. Frequency depends on size: large hedge fund advisers (> $1.5bn) file quarterly; large liquidity fund advisers monthly; others annually. Reports gross/net assets, exposures by asset class, leverage, counterparty concentrations, liquidity terms, performance. Confidential — used by SEC and FSOC for systemic risk monitoring. Significantly expanded in 2024 amendments requiring 72-hour event reporting on stress (e.g., 20% drawdown, large redemptions, prime broker termination).", "source": "https://hedgefund.wiki/api/glossary/term/form-pf.json", "entity": {"type": "term", "id": "form-pf"}, "tokens_approx": 186, "tags": ["regulation", "filing", "sec", "systemic", "regulatory-compliance", "advanced"]}
{"id": "term:regulation-d", "title": "Regulation D", "text": "# Regulation D\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** SEC rules permitting private placement of securities to accredited investors without full SEC registration.\n\n**Definition:** Most hedge funds rely on Rule 506(b) (no general solicitation, sold to accredited investors) or 506(c) (general solicitation permitted, all purchasers must be verified-accredited). Rule 504 covers smaller offerings up to $10m. Filing requirement: Form D within 15 days of first sale. Most hedge funds simultaneously rely on Section 3(c)(1) or 3(c)(7) of the Investment Company Act to avoid registration as investment companies.", "source": "https://hedgefund.wiki/api/glossary/term/regulation-d.json", "entity": {"type": "term", "id": "regulation-d"}, "tokens_approx": 161, "tags": ["regulation", "exemption", "sec", "regulatory-compliance", "intermediate"]}
{"id": "term:accredited-investor", "title": "Accredited Investor", "text": "# Accredited Investor\n\n**Category:** regulatory-compliance · **Level:** intro\n\n**Summary:** Per SEC Rule 501, an investor meeting income, net-worth, professional, or entity thresholds qualifying for unregistered securities.\n\n**Definition:** Individual: $200k income (single, $300k joint) for 2 years with expectation of same OR $1m net worth ex primary residence. Professional: holders of Series 7, 65, 82 licenses; knowledgeable employees of the issuer. Entity: $5m in assets OR all owners are accredited. The 2020 SEC amendment expanded the professional path. ~13% of US households qualify (2024 estimate).", "source": "https://hedgefund.wiki/api/glossary/term/accredited-investor.json", "entity": {"type": "term", "id": "accredited-investor"}, "tokens_approx": 152, "tags": ["regulation", "investor", "sec", "regulatory-compliance", "intro"]}
{"id": "term:qualified-purchaser", "title": "Qualified Purchaser", "text": "# Qualified Purchaser\n_(QP)_\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Per ICA Section 2(a)(51), an investor with $5m+ in investments (individual) or $25m+ (entity) eligible for 3(c)(7) funds.\n\n**Definition:** QP is a higher bar than accredited investor. Funds relying on 3(c)(7) (rather than 3(c)(1)) can take an unlimited number of QPs and avoid the 100-investor cap. Most institutional-grade hedge funds are 3(c)(7) QP-only. The QP threshold ($5m investments, not assets — primary residence excluded, retirement accounts include only direct vested portion) has not been indexed to inflation since 1996.", "source": "https://hedgefund.wiki/api/glossary/term/qualified-purchaser.json", "entity": {"type": "term", "id": "qualified-purchaser"}, "tokens_approx": 160, "tags": ["regulation", "investor", "sec", "regulatory-compliance", "intermediate"]}
{"id": "term:aifmd", "title": "AIFMD", "text": "# AIFMD\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** EU directive (2011/61/EU) governing managers of non-UCITS funds — the European hedge fund regulatory regime.\n\n**Definition:** Effective July 2013. Requires AIFMs to be authorized, hold capital, employ independent depositaries, comply with leverage and remuneration rules, and report risk and exposure data to national regulators. Marketing in the EU requires either an EU AIFM with passport or compliance with national private placement regimes (NPPR) under Article 42. AIFMD II (2024 amendments) tightens rules on loan-originating funds, delegation, and liquidity management.", "source": "https://hedgefund.wiki/api/glossary/term/aifmd.json", "entity": {"type": "term", "id": "aifmd"}, "tokens_approx": 165, "tags": ["regulation", "eu", "afm", "regulatory-compliance", "intermediate"]}
{"id": "term:mifid-ii", "title": "MiFID II", "text": "# MiFID II\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** EU framework regulating trading venues, transparency, best execution, and (most contentiously) research unbundling.\n\n**Definition:** Effective Jan 2018. The unbundling rule required asset managers to pay for sell-side research separately from execution — slashing sell-side research budgets by 30–50% and reducing analyst headcount industry-wide. The 2024 EU Listing Act partially reversed unbundling, allowing rebundling by manager election. Other MiFID II provisions: MTF/OTF venue categories, systematic internalisers, Best Ex reporting, transaction reporting (RTS 22).", "source": "https://hedgefund.wiki/api/glossary/term/mifid-ii.json", "entity": {"type": "term", "id": "mifid-ii"}, "tokens_approx": 164, "tags": ["regulation", "eu", "trading", "regulatory-compliance", "advanced"]}
{"id": "term:dodd-frank", "title": "Dodd-Frank Act", "text": "# Dodd-Frank Act\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** 2010 US legislation overhauling financial regulation post-GFC; required hedge fund advisers > $150m AUM to register with the SEC.\n\n**Definition:** Signed July 2010. Key hedge fund provisions: (1) Title IV — eliminated the 'private adviser' exemption, mandating SEC registration for advisers > $150m; (2) Form PF reporting; (3) Volcker Rule limiting bank prop trading and hedge fund sponsorship; (4) Title VII — derivatives clearing and reporting (CFTC/SEC). Subsequent rollbacks under EGRRCPA (2018) raised some thresholds but left the core hedge fund provisions intact.", "source": "https://hedgefund.wiki/api/glossary/term/dodd-frank.json", "entity": {"type": "term", "id": "dodd-frank"}, "tokens_approx": 166, "tags": ["regulation", "us", "post-gfc", "regulatory-compliance", "intermediate"]}
{"id": "term:mnpi", "title": "Material Non-Public Information", "text": "# Material Non-Public Information\n_(MNPI)_\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Information about a security that is both material (would influence a reasonable investor) and not yet public.\n\n**Definition:** Trading on MNPI is insider trading under US securities law (Rule 10b-5). The Newman/Salman/Blaszczak line of cases shapes tipper/tippee liability — the tipper must receive a personal benefit, real or implied, for the tippee to be liable. Hedge funds maintain MNPI controls: restricted lists, watch lists, expert network protocols, information barriers. Compliance training and surveillance have become enormous fund-level investments since the 2009–2014 SAC Capital era.", "source": "https://hedgefund.wiki/api/glossary/term/mnpi.json", "entity": {"type": "term", "id": "mnpi"}, "tokens_approx": 179, "tags": ["compliance", "ethics", "regulation", "regulatory-compliance", "intermediate"]}
{"id": "term:expert-network", "title": "Expert Network", "text": "# Expert Network\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** A firm that connects investors with industry experts for paid consultations, tightly governed to prevent MNPI transfer.\n\n**Definition:** Major firms: GLG, AlphaSights, Guidepoint, Third Bridge. Calls are typically scheduled, recorded (or not), and chaperoned by the network's compliance team. Funds maintain pre-clearance protocols and avoid current employees of the consult subject. The expert network industry was implicated in the SAC Capital prosecution and has since adopted heavy MNPI controls — but the practice remains a regulatory hotspot.", "source": "https://hedgefund.wiki/api/glossary/term/expert-network.json", "entity": {"type": "term", "id": "expert-network"}, "tokens_approx": 160, "tags": ["research", "compliance", "regulatory-compliance", "intermediate"]}
{"id": "term:ubti", "title": "Unrelated Business Taxable Income", "text": "# Unrelated Business Taxable Income\n_(UBTI)_\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** Income that subjects otherwise tax-exempt entities (pensions, foundations, IRAs) to US federal income tax.\n\n**Definition:** UBTI arises from income from debt-financed property and trade/business activities. Hedge fund use of leverage generates UBTI for tax-exempts unless they invest through a 'corporate blocker' — typically the offshore Cayman feeder of a master-feeder structure. The blocker absorbs the UBTI at the entity level (paying ~21% US corporate tax on US-source income) while the tax-exempt LP receives a clean dividend. The 2017 TCJA's silo rule (Section 512(a)(6)) requires UBTI to be computed separately per activity.", "source": "https://hedgefund.wiki/api/glossary/term/ubti.json", "entity": {"type": "term", "id": "ubti"}, "tokens_approx": 187, "tags": ["tax", "structure", "regulatory-compliance", "advanced"]}
{"id": "term:vwap", "title": "VWAP", "text": "# VWAP\n\n**Category:** trading-execution · **Level:** intro\n\n**Summary:** The intraday average price weighted by volume — a standard execution benchmark.\n\n**Definition:** VWAP = Σ(P_i × V_i) / Σ V_i over the trading session. VWAP-targeting algos slice an order through the day in proportion to historical volume curves to minimize tracking error to the day's VWAP. Beating VWAP is a standard execution-quality metric. Caveat: a manager can game VWAP by trading patiently when their own order moves the market — improving against VWAP at the cost of opportunity.", "source": "https://hedgefund.wiki/api/glossary/term/vwap.json", "entity": {"type": "term", "id": "vwap"}, "tokens_approx": 140, "tags": ["execution", "benchmark", "trading-execution", "intro"]}
{"id": "term:twap", "title": "TWAP", "text": "# TWAP\n\n**Category:** trading-execution · **Level:** intro\n\n**Summary:** The simple time-weighted intraday average price — slices orders evenly through a window.\n\n**Definition:** TWAP = mean(prices sampled at equal time intervals). TWAP algos break an order into equal-sized child slices over a chosen window. Useful when minimizing market impact in a single name with steady volume; less optimal in U-shaped intraday volume curves. Both TWAP and VWAP are 'naive' algos relative to optimal execution under a transient market impact model (Almgren-Chriss).", "source": "https://hedgefund.wiki/api/glossary/term/twap.json", "entity": {"type": "term", "id": "twap"}, "tokens_approx": 138, "tags": ["execution", "benchmark", "trading-execution", "intro"]}
{"id": "term:implementation-shortfall", "title": "Implementation Shortfall", "text": "# Implementation Shortfall\n\n**Category:** trading-execution · **Level:** intermediate\n\n**Summary:** The difference between the price at which a trading decision is made and the average price actually realized, including all costs.\n\n**Definition:** IS = (P_decision − P_avg_executed) × side + commissions + opportunity cost on unfilled. The Perold (1988) formulation broke it into delay cost, market impact, and opportunity cost. IS is the institutional standard for execution quality because it captures the full cost — including the 'paper' loss from price drift while the order works. TCA reports decompose IS by asset, venue, algo, and PM.", "source": "https://hedgefund.wiki/api/glossary/term/implementation-shortfall.json", "entity": {"type": "term", "id": "implementation-shortfall"}, "tokens_approx": 160, "tags": ["execution", "benchmark", "trading-execution", "intermediate"]}
{"id": "term:tca", "title": "Transaction Cost Analysis", "text": "# Transaction Cost Analysis\n_(TCA)_\n\n**Category:** trading-execution · **Level:** intermediate\n\n**Summary:** Post-trade analysis of execution quality against benchmarks like VWAP, arrival price, and implementation shortfall.\n\n**Definition:** Standard TCA reports include: spread cost, market impact, timing cost, opportunity cost. Pre-trade TCA forecasts these costs to inform broker/algo selection. Post-trade TCA evaluates outcomes. Algo-wheel TCA randomly routes orders across competing algos and measures relative performance — the institutional way to keep brokers honest. MiFID II Article 27 requires Best Ex monitoring and reporting (RTS 27/28, partially repealed 2024).", "source": "https://hedgefund.wiki/api/glossary/term/tca.json", "entity": {"type": "term", "id": "tca"}, "tokens_approx": 169, "tags": ["execution", "analysis", "best-ex", "trading-execution", "intermediate"]}
{"id": "term:dark-pool", "title": "Dark Pool", "text": "# Dark Pool\n\n**Category:** market-microstructure · **Level:** intermediate\n\n**Summary:** An off-exchange trading venue that does not display quotes pre-trade; trades print to the consolidated tape post-trade.\n\n**Definition:** Dark pools serve institutions wanting to trade size without signaling. Major US ATSs: UBS ATS, Sigma X, IEX, MS Pool, Liquidnet. Trades execute typically at NBBO midpoint. Dark pool share of US equity volume has hovered around 12–15% for the past decade. Regulatory scrutiny intensified after the Barclays LX case (2014) and Pipeline Trading (2011) settlements over misleading liquidity claims.", "source": "https://hedgefund.wiki/api/glossary/term/dark-pool.json", "entity": {"type": "term", "id": "dark-pool"}, "tokens_approx": 155, "tags": ["microstructure", "venue", "execution", "market-microstructure", "intermediate"]}
{"id": "term:bid-ask-spread", "title": "Bid-Ask Spread", "text": "# Bid-Ask Spread\n\n**Category:** market-microstructure · **Level:** intro\n\n**Summary:** The difference between the best buy quote (bid) and best sell quote (ask) in an order book.\n\n**Definition:** The spread compensates market makers for inventory risk, adverse selection, and operating costs. Effective spread (paid spread, accounting for hidden liquidity and price improvement) is typically narrower than quoted. Quoted spread is a noisy proxy for liquidity; effective spread, realized spread, and queue depth are better. Spreads have compressed dramatically since decimalization (2001) and the rise of HFT.", "source": "https://hedgefund.wiki/api/glossary/term/bid-ask-spread.json", "entity": {"type": "term", "id": "bid-ask-spread"}, "tokens_approx": 152, "tags": ["microstructure", "liquidity", "market-microstructure", "intro"]}
{"id": "term:adverse-selection", "title": "Adverse Selection", "text": "# Adverse Selection\n\n**Category:** market-microstructure · **Level:** advanced\n\n**Summary:** The risk that a market maker's counterparty has private information, causing the maker to systematically lose to informed flow.\n\n**Definition:** Glosten-Milgrom (1985) modeled the market maker's spread as compensation for adverse selection from informed traders. PIN (Probability of Informed Trading), VPIN (Volume-synchronized PIN, Easley/López de Prado/O'Hara), and order flow toxicity metrics estimate adverse selection in real time and are used by HFTs to manage quote width and depth.", "source": "https://hedgefund.wiki/api/glossary/term/adverse-selection.json", "entity": {"type": "term", "id": "adverse-selection"}, "tokens_approx": 145, "tags": ["microstructure", "information", "hft", "market-microstructure", "advanced"]}
{"id": "term:kelly-criterion", "title": "Kelly Criterion", "text": "# Kelly Criterion\n\n**Category:** portfolio-construction · **Level:** advanced\n\n**Summary:** The bet-sizing fraction that maximizes the long-run logarithm of wealth.\n\n**Definition:** For a binary bet with edge e and odds o: f* = e / o. For continuous returns with mean μ and variance σ²: f* = (μ − r) / σ². Full Kelly is volatile (drawdowns of 80–90% are routine); fractional Kelly (typically half-Kelly) is the practitioner's compromise. The criterion underlies many quant fund risk allocation frameworks and is the foundational concept of Edward Thorp's Princeton/Newport Partners.", "source": "https://hedgefund.wiki/api/glossary/term/kelly-criterion.json", "entity": {"type": "term", "id": "kelly-criterion"}, "tokens_approx": 145, "tags": ["sizing", "portfolio", "growth-optimal", "portfolio-construction", "advanced"]}
{"id": "term:risk-parity", "title": "Risk Parity", "text": "# Risk Parity\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** An allocation framework that sizes positions so each asset contributes equally to total portfolio risk.\n\n**Definition:** Equal-risk contribution: w_i × MRC_i = constant for all i, where MRC is marginal risk contribution. Often levered to match a target volatility (e.g., 10% annualized). Bridgewater's All Weather pioneered the institutional version in the 1990s; AQR, PanAgora, and many others followed. Performance: strong in 2000s (positive bond/equity correlation regime), weak in 2022 when bonds and equities sold off together. Sensitive to leverage availability and rate-vol regime.", "source": "https://hedgefund.wiki/api/glossary/term/risk-parity.json", "entity": {"type": "term", "id": "risk-parity"}, "tokens_approx": 170, "tags": ["allocation", "portfolio", "leverage", "portfolio-construction", "intermediate"]}
{"id": "term:mean-variance-optimization", "title": "Mean-Variance Optimization", "text": "# Mean-Variance Optimization\n_(MVO)_\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** Markowitz's framework: choose portfolio weights to maximize expected return for a given level of variance (or vice versa).\n\n**Definition:** Markowitz (1952) introduced the efficient frontier. The unconstrained tangency portfolio is w ∝ Σ⁻¹(μ − r). Famously sensitive to inputs: small estimation errors in μ produce extreme weights. Practical fixes: shrinkage (Ledoit-Wolf, James-Stein), Black-Litterman blending of priors with views, resampling, robust optimization, and direct constraints (long-only, position limits).", "source": "https://hedgefund.wiki/api/glossary/term/mean-variance-optimization.json", "entity": {"type": "term", "id": "mean-variance-optimization"}, "tokens_approx": 158, "tags": ["allocation", "portfolio", "optimization", "portfolio-construction", "intermediate"]}
{"id": "term:black-litterman", "title": "Black-Litterman Model", "text": "# Black-Litterman Model\n\n**Category:** portfolio-construction · **Level:** advanced\n\n**Summary:** A Bayesian framework that combines an equilibrium prior (CAPM-implied returns) with investor views to produce stable optimal portfolios.\n\n**Definition:** Developed at Goldman in 1990 by Fischer Black and Robert Litterman. The posterior expected return vector is a weighted blend of the implied equilibrium return Π = δΣw_mkt and the analyst's view portfolios P with confidence Ω. The result: weights that deviate from market caps only in proportion to view strength, eliminating MVO's corner-solution pathology.", "source": "https://hedgefund.wiki/api/glossary/term/black-litterman.json", "entity": {"type": "term", "id": "black-litterman"}, "tokens_approx": 152, "tags": ["allocation", "bayesian", "optimization", "portfolio-construction", "advanced"]}
{"id": "term:fama-french-factors", "title": "Fama-French Factors", "text": "# Fama-French Factors\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Multi-factor models extending CAPM with size (SMB), value (HML), profitability (RMW), investment (CMA), and momentum (MOM).\n\n**Definition:** Fama-French 3-factor (1992): Market, SMB, HML. 5-factor (2015): adds RMW and CMA. Carhart (1997): adds MOM. Hedge fund performance attribution increasingly uses these factors plus alternative-risk premia (carry, defensive, low-vol) to identify true alpha. Many strategies marketed as alpha are simply long known factor exposures.", "source": "https://hedgefund.wiki/api/glossary/term/fama-french-factors.json", "entity": {"type": "term", "id": "fama-french-factors"}, "tokens_approx": 142, "tags": ["factor", "quant", "performance", "quantitative-methods", "intermediate"]}
{"id": "term:cointegration", "title": "Cointegration", "text": "# Cointegration\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** A statistical relationship in which two or more non-stationary series share a common stochastic trend, so their linear combination is stationary.\n\n**Definition:** Engle-Granger (1987) and Johansen (1991) tests detect cointegration. Cointegrated pairs/baskets form the basis of pairs trading and stat-arb: the spread mean-reverts to its long-run equilibrium. Cointegration is fragile — relationships break in regime shifts (M&A, sector rotation, fundamental change). Robust strategies use rolling re-estimation and statistical-significance gates.", "source": "https://hedgefund.wiki/api/glossary/term/cointegration.json", "entity": {"type": "term", "id": "cointegration"}, "tokens_approx": 158, "tags": ["statistics", "time-series", "quant", "quantitative-methods", "advanced"]}
{"id": "term:ornstein-uhlenbeck", "title": "Ornstein-Uhlenbeck Process", "text": "# Ornstein-Uhlenbeck Process\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** A continuous-time mean-reverting stochastic process used to model spreads, vol, rates, and basis.\n\n**Definition:** dX_t = θ(μ − X_t)dt + σ dW_t. Parameters: θ (mean-reversion speed), μ (long-run mean), σ (volatility). Half-life of mean reversion = ln(2)/θ. Used in pairs trading (spread), Vasicek/CIR rate models, and vol modeling. Fitting via OLS on ΔX_t = α + βX_{t-1} + ε; θ = −β/Δt, μ = α/(−β), σ from residuals.", "source": "https://hedgefund.wiki/api/glossary/term/ornstein-uhlenbeck.json", "entity": {"type": "term", "id": "ornstein-uhlenbeck"}, "tokens_approx": 129, "tags": ["statistics", "continuous-time", "quant", "quantitative-methods", "advanced"]}
{"id": "term:monte-carlo", "title": "Monte Carlo Simulation", "text": "# Monte Carlo Simulation\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Numerical method that estimates outcomes by repeated random sampling from input distributions.\n\n**Definition:** In hedge fund risk: simulate thousands of forward paths under a fitted model (geometric Brownian, jump-diffusion, regime-switching, GARCH), then read percentiles for VaR/ES, drawdown distributions, and capacity. In option pricing: simulate underlying paths, average discounted payoffs. Variance reduction techniques (antithetic variates, control variates, importance sampling, quasi-MC) materially cut compute requirements.", "source": "https://hedgefund.wiki/api/glossary/term/monte-carlo.json", "entity": {"type": "term", "id": "monte-carlo"}, "tokens_approx": 159, "tags": ["simulation", "risk", "compute", "quantitative-methods", "intermediate"]}
{"id": "term:leverage", "title": "Leverage", "text": "# Leverage\n\n**Category:** risk-management · **Level:** intro\n\n**Summary:** The use of borrowed capital to amplify portfolio exposure beyond invested equity.\n\n**Definition:** Measured several ways: (1) gross leverage = (long + |short|) / equity; (2) net leverage = (long − |short|) / equity; (3) regulatory leverage (CFTC commitments method, AIFMD gross/commitment methods, SEC Form PF method). Equity L/S typically 2–4× gross; macro 5–15×; rates relative-value 20–60×; convertible arb 4–8×. Leverage is procyclical — margin calls force selling at the worst time, creating the deleveraging cascade pattern of 2008 and March 2020.", "source": "https://hedgefund.wiki/api/glossary/term/leverage.json", "entity": {"type": "term", "id": "leverage"}, "tokens_approx": 157, "tags": ["risk", "exposure", "risk-management", "intro"]}
{"id": "term:gross-exposure", "title": "Gross Exposure", "text": "# Gross Exposure\n\n**Category:** risk-management · **Level:** intro\n\n**Summary:** The sum of long market value plus the absolute value of short market value, as a percentage of NAV.\n\n**Definition:** Gross = (L + |S|) / NAV. Captures the total economic capital at risk regardless of direction. Equity L/S 150–250%; multi-strat pods 400–800%; rates RV 10–60×.", "source": "https://hedgefund.wiki/api/glossary/term/gross-exposure.json", "entity": {"type": "term", "id": "gross-exposure"}, "tokens_approx": 89, "tags": ["risk", "exposure", "risk-management", "intro"]}
{"id": "term:net-exposure", "title": "Net Exposure", "text": "# Net Exposure\n\n**Category:** risk-management · **Level:** intro\n\n**Summary:** Long market value minus absolute value of short market value, as a percentage of NAV.\n\n**Definition:** Net = (L − |S|) / NAV. Approximates portfolio's directional market beta if longs and shorts have similar betas. A market-neutral fund targets net ≈ 0; a directional L/S fund 30–80% net long.", "source": "https://hedgefund.wiki/api/glossary/term/net-exposure.json", "entity": {"type": "term", "id": "net-exposure"}, "tokens_approx": 93, "tags": ["risk", "exposure", "risk-management", "intro"]}
{"id": "term:counterparty-risk", "title": "Counterparty Risk", "text": "# Counterparty Risk\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** The risk that the other side of a trade or contract fails to perform its obligations.\n\n**Definition:** Hedge funds face counterparty risk in OTC derivatives, prime brokerage, securities lending, and tri-party repo. Mitigants: ISDA Master + CSA with daily VM/IM, central clearing where mandated (UMR phases 1–6 since 2016), netting, multi-PB diversification, and segregated custody. The 2008 Lehman bankruptcy froze ~$70bn of hedge fund assets at LBIE under the UK 'Rule 7' insolvency regime — the moment that ended single-PB practice for the institutional industry.", "source": "https://hedgefund.wiki/api/glossary/term/counterparty-risk.json", "entity": {"type": "term", "id": "counterparty-risk"}, "tokens_approx": 164, "tags": ["risk", "counterparty", "operations", "risk-management", "intermediate"]}
{"id": "term:liquidity-risk", "title": "Liquidity Risk", "text": "# Liquidity Risk\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** The risk of being unable to exit a position at a fair price within a needed timeframe.\n\n**Definition:** Two dimensions: (1) market liquidity — bid-ask, market depth, time-to-liquidate; (2) funding liquidity — access to financing, margin terms, redemption pressure. Mismatches between asset liquidity and fund redemption terms cause runs (LTCM, Bear Stearns hedge funds 2007, Woodford 2019, Archegos 2021). Standard metrics: average daily volume coverage, ETF/index inclusion, bid-ask, time-to-15%-impact. Funds maintain liquidity ladders matching asset liquidity to investor terms.", "source": "https://hedgefund.wiki/api/glossary/term/liquidity-risk.json", "entity": {"type": "term", "id": "liquidity-risk"}, "tokens_approx": 167, "tags": ["risk", "liquidity", "operations", "risk-management", "intermediate"]}
{"id": "term:rehypothecation", "title": "Rehypothecation", "text": "# Rehypothecation\n\n**Category:** fund-operations · **Level:** advanced\n\n**Summary:** A prime broker's right to re-pledge or re-lend assets posted by its hedge fund clients as collateral.\n\n**Definition:** US: Reg T limits rehyp to 140% of customer debit balance. UK historically (pre-Lehman) had no limit, which is why ~$70bn of hedge fund assets at Lehman International were unrecoverable for years. EU: under MiFID II/CRR, requires explicit client consent and disclosure. Funds today negotiate hard rehyp limits and often elect 'segregated' (Type 1 SIPC or fully-segregated cash custody) for excess collateral.", "source": "https://hedgefund.wiki/api/glossary/term/rehypothecation.json", "entity": {"type": "term", "id": "rehypothecation"}, "tokens_approx": 152, "tags": ["operations", "counterparty", "regulation", "fund-operations", "advanced"]}
{"id": "term:isda", "title": "ISDA Master Agreement", "text": "# ISDA Master Agreement\n\n**Category:** fund-operations · **Level:** advanced\n\n**Summary:** The standardized bilateral agreement governing OTC derivatives between two counterparties.\n\n**Definition:** Published by the International Swaps and Derivatives Association. The Master, supplemented by a Schedule (negotiated bilaterally), Credit Support Annex (CSA, governing collateral), and trade-level Confirmations, governs every OTC derivatives relationship. Key concepts: netting (single net obligation under default), close-out (early termination on event of default), set-off, and cross-default. The 2002 Master replaced the 1992 Master and is the standard.", "source": "https://hedgefund.wiki/api/glossary/term/isda.json", "entity": {"type": "term", "id": "isda"}, "tokens_approx": 164, "tags": ["legal", "derivatives", "counterparty", "fund-operations", "advanced"]}
{"id": "term:ucits", "title": "UCITS", "text": "# UCITS\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** EU regulated investment fund vehicle with passporting across the EEA — used for liquid alternative strategies.\n\n**Definition:** UCITS V (2014) is the current framework. Constraints: daily liquidity, max 10% in any single security (5/10/40 rule), max 200% gross VaR-based leverage, no direct commodity exposure. 'Liquid alts' / 'newcits' adapted hedge fund strategies (L/S equity, market neutral, macro, managed futures) into UCITS. AUM in alternative-UCITS reached €700bn in 2025.", "source": "https://hedgefund.wiki/api/glossary/term/ucits.json", "entity": {"type": "term", "id": "ucits"}, "tokens_approx": 139, "tags": ["regulation", "eu", "structure", "fund-operations", "intermediate"]}
{"id": "term:perpetual-futures", "title": "Perpetual Futures", "text": "# Perpetual Futures\n\n**Category:** crypto-digital-assets · **Level:** intermediate\n\n**Summary:** Crypto futures contracts with no expiry, with a periodic funding rate paid between longs and shorts to anchor price to spot.\n\n**Definition:** Invented by BitMEX (Hayes) in 2016 and now the dominant crypto derivative ($100tn+ annual notional in 2025). Funding rate ≈ (perp price − spot index price) / spot, paid every 8 hours from the side at premium to the side at discount. Fundings can persist at 30–100% annualized in bull markets. Hedge funds run cash-and-carry (long spot / short perp) to harvest funding, generating one of the highest-Sharpe crypto trades when funding is positive.", "source": "https://hedgefund.wiki/api/glossary/term/perpetual-futures.json", "entity": {"type": "term", "id": "perpetual-futures"}, "tokens_approx": 171, "tags": ["crypto", "derivatives", "perp", "crypto-digital-assets", "intermediate"]}
{"id": "term:funding-rate", "title": "Funding Rate", "text": "# Funding Rate\n\n**Category:** crypto-digital-assets · **Level:** intermediate\n\n**Summary:** Periodic payment between longs and shorts in a perpetual futures contract that anchors the perp price to spot.\n\n**Definition:** Each exchange (Binance, OKX, Bybit, Deribit) computes its own funding rate from the perp-vs-index basis plus an interest-rate component. Settled every 8 hours on most venues, every 1 hour on Hyperliquid. Annualized funding rates have ranged from −50% (extreme bearish) to +200% (mania) over the past 5 years. Funding-rate arbitrage runs cash-and-carry (long spot, short perp) when funding is positive.", "source": "https://hedgefund.wiki/api/glossary/term/funding-rate.json", "entity": {"type": "term", "id": "funding-rate"}, "tokens_approx": 155, "tags": ["crypto", "derivatives", "funding", "crypto-digital-assets", "intermediate"]}
{"id": "term:basis-trade", "title": "Basis Trade", "text": "# Basis Trade\n\n**Category:** crypto-digital-assets · **Level:** intermediate\n\n**Summary:** Long spot / short futures (or vice versa) to harvest the spread between spot and futures prices.\n\n**Definition:** In crypto: long spot BTC, short BTC perpetual or quarterly future, earn the basis. In Treasuries: long cash bond, short futures, harvest the cheapest-to-deliver basis (the canonical hedge fund trade now ~$1tn in size, the focus of Fed and Treasury concerns about market stability since 2020). In commodities: cash-and-carry where storage cost < contango.", "source": "https://hedgefund.wiki/api/glossary/term/basis-trade.json", "entity": {"type": "term", "id": "basis-trade"}, "tokens_approx": 139, "tags": ["arbitrage", "basis", "crypto", "rates", "crypto-digital-assets", "intermediate"]}
{"id": "term:level-3-asset", "title": "Level 3 Asset", "text": "# Level 3 Asset\n\n**Category:** accounting-valuation · **Level:** intermediate\n\n**Summary:** Per ASC 820 / IFRS 13, an asset whose fair value is determined using significant unobservable inputs (model-based marks).\n\n**Definition:** Fair value hierarchy: Level 1 (quoted prices in active markets — equities), Level 2 (observable inputs — most fixed income, swaps), Level 3 (unobservable inputs — private equity, illiquid loans, esoteric structured credit). Level 3 marks are subject to model risk and management bias. Independent pricing services (IHS Markit, Solve Advisors, Bloomberg BVAL) and audit valuation committees provide checks. Funds with > 30% Level 3 typically run side pockets and impose long lock-ups.", "source": "https://hedgefund.wiki/api/glossary/term/level-3-asset.json", "entity": {"type": "term", "id": "level-3-asset"}, "tokens_approx": 178, "tags": ["valuation", "accounting", "illiquid", "accounting-valuation", "intermediate"]}
{"id": "term:fair-value", "title": "Fair Value", "text": "# Fair Value\n\n**Category:** accounting-valuation · **Level:** intermediate\n\n**Summary:** Per ASC 820, the price that would be received to sell an asset or paid to transfer a liability in an orderly transaction between market participants at the measurement date.\n\n**Definition:** An exit-price standard, not entry. Applies to all financial instruments held by US private funds. The hierarchy (Level 1/2/3) determines disclosure requirements but not the measurement standard itself. Fair value uses 'highest and best use' for non-financial assets, 'unit of account' as defined by the asset class, and a 'principal market' (or absent that, 'most advantageous market') determination.", "source": "https://hedgefund.wiki/api/glossary/term/fair-value.json", "entity": {"type": "term", "id": "fair-value"}, "tokens_approx": 170, "tags": ["valuation", "accounting", "accounting-valuation", "intermediate"]}
{"id": "term:j-curve", "title": "J-Curve", "text": "# J-Curve\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** The pattern of negative early returns followed by rising returns over time, characteristic of private fund vintages.\n\n**Definition:** PE/VC funds draw capital and pay fees in early years (the dip of the J), then realize gains as portfolio companies mature (the rising leg). Hedge fund extensions: long-dated activist funds, distressed-debt vehicles, and credit lockups exhibit shallow J-curves. NAV-based metrics (DPI, RVPI, TVPI) are designed to evaluate funds across the J-curve.", "source": "https://hedgefund.wiki/api/glossary/term/j-curve.json", "entity": {"type": "term", "id": "j-curve"}, "tokens_approx": 142, "tags": ["private", "lifecycle", "performance", "alternative-investments", "intermediate"]}
{"id": "term:irr", "title": "Internal Rate of Return", "text": "# Internal Rate of Return\n_(IRR)_\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** The discount rate that makes the NPV of a cash flow stream equal to zero — the standard PE/VC return metric.\n\n**Definition:** Solved iteratively from Σ CF_t / (1+r)^t = 0. IRR is sensitive to timing — early distributions inflate IRR. Practitioners pair IRR with multiple-on-invested-capital (MOIC/TVPI) and DPI to triangulate true performance. Pitfall: IRR assumes reinvestment at the IRR itself, often unrealistic — Modified IRR (MIRR) corrects this.", "source": "https://hedgefund.wiki/api/glossary/term/irr.json", "entity": {"type": "term", "id": "irr"}, "tokens_approx": 141, "tags": ["performance", "private", "cash-flow", "alternative-investments", "intermediate"]}
{"id": "term:tvpi", "title": "TVPI", "text": "# TVPI\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** Sum of distributions plus residual value, divided by paid-in capital — the 'multiple' on invested capital.\n\n**Definition:** TVPI = (Distributions + NAV) / Paid-In Capital. Decomposes into DPI (realized) + RVPI (unrealized). Less time-sensitive than IRR — a TVPI of 2.0× is unambiguous regardless of when cash flowed. Together with IRR, TVPI is the standard PE/VC performance pair.", "source": "https://hedgefund.wiki/api/glossary/term/tvpi.json", "entity": {"type": "term", "id": "tvpi"}, "tokens_approx": 116, "tags": ["performance", "private", "multiple", "alternative-investments", "intermediate"]}
{"id": "term:yield-curve-inversion", "title": "Yield Curve Inversion", "text": "# Yield Curve Inversion\n\n**Category:** macroeconomics · **Level:** intermediate\n\n**Summary:** When short-term rates exceed long-term rates — historically a leading indicator of US recession.\n\n**Definition:** The 2s10s and 3M-10Y spreads have been the most reliable recession signals: every US recession since 1970 was preceded by inversion of one or both. The 2022–2024 inversion was the deepest (peak −108bp on 2s10s) and longest (~22 months) on record, eventually un-inverted ahead of growth slowdown in 2024. Mechanism debate: signal of Fed tightness, signal of falling future inflation/growth, or self-fulfilling via bank lending margin compression.", "source": "https://hedgefund.wiki/api/glossary/term/yield-curve-inversion.json", "entity": {"type": "term", "id": "yield-curve-inversion"}, "tokens_approx": 163, "tags": ["macro", "rates", "recession", "macroeconomics", "intermediate"]}
{"id": "term:treasury-basis-trade", "title": "Treasury Basis Trade", "text": "# Treasury Basis Trade\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** Long cash Treasury, short Treasury futures, financed via repo — earning the basis at high leverage.\n\n**Definition:** Hedge funds (primarily relative-value rates funds) hold long cash bonds and short the cheapest-to-deliver Treasury futures, financed in tri-party repo at 50–100× leverage. P&L = (carry on bond − futures roll cost − repo cost), typically a few bps × leverage. Estimated $1.0–1.2tn outstanding in 2026, concentrated at Citadel, Millennium, ExodusPoint, and a handful of others. Identified by FSOC and the BIS as a systemic vulnerability — the March 2020 'dash for cash' saw forced unwinds amplify Treasury market dysfunction. Subject to escalating regulatory scrutiny: SEC's UST clearing mandate (effective 2026 for cash, 2027 for repo) materially changes the trade's economics.", "source": "https://hedgefund.wiki/api/glossary/term/treasury-basis-trade.json", "entity": {"type": "term", "id": "treasury-basis-trade"}, "tokens_approx": 221, "tags": ["rates", "basis", "systemic", "fixed-income-credit", "advanced"]}
{"id": "term:trend-following", "title": "Trend Following", "text": "# Trend Following\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** Systematic strategy that buys assets with positive past returns and sells assets with negative past returns.\n\n**Definition:** The dominant CTA strategy. Signal generation: moving-average crossovers (e.g., 50/200 day), breakout systems (Donchian channel), or smoothed momentum (e.g., 12-month return ex-recent-month). Position sizing: inverse volatility, equalized risk contribution. Returns historically positive across asset classes and centuries (Hurst et al., 'Two Centuries of Trend Following'). Crisis alpha: trend tends to outperform in extended bear markets (2008, 2022) when sustained moves develop.", "source": "https://hedgefund.wiki/api/glossary/term/trend-following.json", "entity": {"type": "term", "id": "trend-following"}, "tokens_approx": 175, "tags": ["strategy", "systematic", "trend", "hedge-fund-strategies", "intermediate"]}
{"id": "term:momentum", "title": "Momentum", "text": "# Momentum\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** The tendency for assets that have outperformed in the recent past to continue outperforming in the near future.\n\n**Definition:** Established as a robust factor by Jegadeesh-Titman (1993) for cross-sectional equity momentum (12-1 month return). Time-series momentum (Moskowitz-Ooi-Pedersen 2012) showed it works across asset classes. Behavioral explanations: under-reaction to news, herding, anchoring. Risk explanations: business-cycle exposure. Momentum suffers severe crashes (2009 'momentum crash' as junk rallied) and is typically combined with value, quality, and trend filters in practice.", "source": "https://hedgefund.wiki/api/glossary/term/momentum.json", "entity": {"type": "term", "id": "momentum"}, "tokens_approx": 170, "tags": ["factor", "quant", "momentum", "quantitative-methods", "intermediate"]}
{"id": "term:capm", "title": "Capital Asset Pricing Model", "text": "# Capital Asset Pricing Model\n_(CAPM)_\n\n**Category:** quantitative-methods · **Level:** intro\n\n**Summary:** Sharpe-Lintner-Mossin model: expected return = risk-free rate + β × (market return − risk-free rate).\n\n**Definition:** E[R_i] = R_f + β_i (E[R_m] − R_f). The simplest factor model; β is the sole priced source of risk. Empirically rejected as the sole driver of cross-sectional returns (size, value, momentum all add explanatory power), yet survives as a useful baseline and the foundation of the cost-of-capital calculation. Hedge fund attribution still begins with a CAPM regression before adding factors.", "source": "https://hedgefund.wiki/api/glossary/term/capm.json", "entity": {"type": "term", "id": "capm"}, "tokens_approx": 153, "tags": ["asset-pricing", "factor", "academic", "quantitative-methods", "intro"]}
{"id": "term:black-scholes", "title": "Black-Scholes Model", "text": "# Black-Scholes Model\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** A continuous-time model for European option pricing assuming geometric Brownian underlying and constant volatility.\n\n**Definition:** C = S Φ(d1) − K e^{−rT} Φ(d2), where d1 = [ln(S/K) + (r + σ²/2)T] / (σ√T), d2 = d1 − σ√T. The model assumes: no dividends (or continuous yield q), constant r and σ, no transaction costs, continuous trading, log-normal returns. Despite known violations (vol smile, jumps, fat tails), Black-Scholes remains the lingua franca for options — quotes are routinely expressed in implied vol terms via inversion of the formula.", "source": "https://hedgefund.wiki/api/glossary/term/black-scholes.json", "entity": {"type": "term", "id": "black-scholes"}, "tokens_approx": 162, "tags": ["options", "pricing", "academic", "derivatives-options", "intermediate"]}
{"id": "term:smart-beta", "title": "Smart Beta", "text": "# Smart Beta\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** Rules-based strategies that systematically tilt portfolios toward known risk factors (value, size, momentum, quality, low-vol).\n\n**Definition:** The packaging of academic factor research into low-cost, transparent products. The category exploded post-2010 ($2tn+ AUM by 2024) but performance has been mixed: the post-2018 'value drought' challenged the canonical multi-factor pitch. Hedge funds increasingly view smart beta as a benchmark for true alpha — anything a $5bp ETF can replicate is not paying 2/20.", "source": "https://hedgefund.wiki/api/glossary/term/smart-beta.json", "entity": {"type": "term", "id": "smart-beta"}, "tokens_approx": 150, "tags": ["factor", "etf", "passive", "portfolio-construction", "intermediate"]}
{"id": "term:alternative-risk-premia", "title": "Alternative Risk Premia", "text": "# Alternative Risk Premia\n_(ARP)_\n\n**Category:** portfolio-construction · **Level:** advanced\n\n**Summary:** Systematic strategies that harvest persistent risk premia (carry, momentum, value, defensive, volatility) across asset classes.\n\n**Definition:** ARP unbundles hedge-fund-style returns into transparent, replicable building blocks at lower fees (typically 50–100bp). Carry, momentum, value, low-vol, and quality across equities, FX, rates, and commodities are the standard sleeves. Performance has been disappointing post-2018 (extended drawdowns in cross-asset value, FX carry crashes), prompting questions about premia decay versus genuine premium variation. Major providers: AQR, Man AHL, Goldman QIS, JPMQIS.", "source": "https://hedgefund.wiki/api/glossary/term/alternative-risk-premia.json", "entity": {"type": "term", "id": "alternative-risk-premia"}, "tokens_approx": 179, "tags": ["factor", "premia", "systematic", "portfolio-construction", "advanced"]}
{"id": "term:tracking-error", "title": "Tracking Error", "text": "# Tracking Error\n\n**Category:** quantitative-methods · **Level:** intro\n\n**Summary:** The standard deviation of the return difference between a portfolio and its benchmark.\n\n**Definition:** TE = σ(R_p − R_b), annualized. Index funds target TE near 0; enhanced-index funds 50–150bp; active managers 300–800bp; hedge funds typically don't measure TE because they aren't benchmark-constrained. The denominator of the information ratio.", "source": "https://hedgefund.wiki/api/glossary/term/tracking-error.json", "entity": {"type": "term", "id": "tracking-error"}, "tokens_approx": 108, "tags": ["benchmark", "risk", "quantitative-methods", "intro"]}
{"id": "term:deal-spread", "title": "Deal Spread", "text": "# Deal Spread\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** In merger arbitrage, the percentage gap between the announced acquisition price and the target's current trading price.\n\n**Definition:** Spread = (Deal Price / Target Price − 1) × 100%. Reflects the market's probability-weighted view of deal completion, time to close, and downside if the deal breaks. Wider spreads imply more break risk; narrower spreads imply higher confidence (or less return). Annualized spread = (Deal Price/Current Price − 1) × (365/Days to Close), useful for sizing.", "source": "https://hedgefund.wiki/api/glossary/term/deal-spread.json", "entity": {"type": "term", "id": "deal-spread"}, "tokens_approx": 145, "tags": ["event-driven", "merger-arb", "hedge-fund-strategies", "intermediate"]}
{"id": "term:break-risk", "title": "Break Risk", "text": "# Break Risk\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** The risk that an announced merger or acquisition fails to close.\n\n**Definition:** Major drivers: regulatory (HSR/FTC, EU Commission, CMA, CFIUS, NSIA), shareholder vote, financing condition, MAC/MAE invocation, hostile interloper. Break-risk modeling estimates: P(close), P(retrade), P(broken), expected price under each scenario. Recent break-risk shocks: Microsoft/Activision (CMA initial block, ultimately approved); Adobe/Figma (EU/UK objections, abandoned); Albertsons/Kroger (FTC blocked).", "source": "https://hedgefund.wiki/api/glossary/term/break-risk.json", "entity": {"type": "term", "id": "break-risk"}, "tokens_approx": 146, "tags": ["event-driven", "merger-arb", "regulation", "hedge-fund-strategies", "intermediate"]}
{"id": "term:mac-clause", "title": "Material Adverse Change Clause", "text": "# Material Adverse Change Clause\n_(MAC / MAE)_\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** A merger agreement provision allowing the buyer to walk if a 'material adverse change' occurs at the target between signing and closing.\n\n**Definition:** MAC clauses are heavily negotiated and typically carve out market-wide, industry-wide, and pandemic-related events. Delaware courts have rarely upheld MAC invocations (Akorn v. Fresenius, 2018, was the landmark exception). The COVID-era cases (Tiffany/LVMH, Forescout/Advent, etc.) largely settled or were resolved by closing. Merger arbs assess MAC risk by reading the agreement's exact carve-out language.", "source": "https://hedgefund.wiki/api/glossary/term/mac-clause.json", "entity": {"type": "term", "id": "mac-clause"}, "tokens_approx": 170, "tags": ["event-driven", "merger-arb", "legal", "hedge-fund-strategies", "advanced"]}
{"id": "term:fulcrum-security", "title": "Fulcrum Security", "text": "# Fulcrum Security\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** The class of securities in a distressed company's capital structure that will be converted to equity in a restructuring.\n\n**Definition:** Identifying the fulcrum (typically the most senior class to take a haircut and receive equity) is the central skill of distressed investing. Practitioners build a 'waterfall' of expected recoveries from EV at exit, working down the cap stack until residual value runs out. Loan-to-own strategies accumulate fulcrum debt at distressed prices to control the post-reorg equity. Famous fulcrum trades: Caesars 2017 (TPG/Apollo battle), J.Crew 2020 (PIK toggles), Frontier 2020 (unsecured bonds → 100% equity).", "source": "https://hedgefund.wiki/api/glossary/term/fulcrum-security.json", "entity": {"type": "term", "id": "fulcrum-security"}, "tokens_approx": 183, "tags": ["distressed", "credit", "capital-structure", "hedge-fund-strategies", "advanced"]}
{"id": "term:credit-spread", "title": "Credit Spread", "text": "# Credit Spread\n\n**Category:** fixed-income-credit · **Level:** intro\n\n**Summary:** The yield premium of a credit-risky bond over a risk-free benchmark of the same maturity.\n\n**Definition:** Common spread measures: G-spread (over interpolated Treasury), I-spread (over interpolated swap), Z-spread (zero-volatility static spread), OAS (option-adjusted spread, removing the value of embedded options). Credit spreads compensate investors for default risk, liquidity premium, and risk premium. Decomposition: PD × (1−R) + risk premium.", "source": "https://hedgefund.wiki/api/glossary/term/credit-spread.json", "entity": {"type": "term", "id": "credit-spread"}, "tokens_approx": 133, "tags": ["credit", "yield", "fixed-income-credit", "intro"]}
{"id": "term:oas", "title": "Option-Adjusted Spread", "text": "# Option-Adjusted Spread\n_(OAS)_\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** The constant spread added to the risk-free rate path that equates a bond's model price with its market price, after stripping out embedded options.\n\n**Definition:** Computed via Monte Carlo or lattice over a calibrated interest rate model. OAS isolates pure credit/liquidity premium from the value of callability, prepayment, or putability. For MBS, OAS is the standard relative-value metric. Negative OAS occasionally appears for highly negative-convexity MBS in low-rate regimes — model artifact more than economic insight.", "source": "https://hedgefund.wiki/api/glossary/term/oas.json", "entity": {"type": "term", "id": "oas"}, "tokens_approx": 157, "tags": ["credit", "model", "mbs", "fixed-income-credit", "advanced"]}
{"id": "term:vol-surface", "title": "Volatility Surface", "text": "# Volatility Surface\n\n**Category:** derivatives-options · **Level:** advanced\n\n**Summary:** The two-dimensional grid of implied volatilities by strike (skew) and maturity (term structure).\n\n**Definition:** Constructed from market prices of liquid options. Used for pricing exotic options (interpolation), risk reporting (vega bucketing), and trading (skew/term-structure RV). Common parametrizations: SABR, SVI (Stochastic Volatility Inspired, Gatheral), Heston. Dynamics — how the surface moves when spot moves — matters for hedging: 'sticky strike' vs 'sticky delta' assumptions yield different vega hedges.", "source": "https://hedgefund.wiki/api/glossary/term/vol-surface.json", "entity": {"type": "term", "id": "vol-surface"}, "tokens_approx": 152, "tags": ["volatility", "options", "model", "derivatives-options", "advanced"]}
{"id": "term:realized-volatility", "title": "Realized Volatility", "text": "# Realized Volatility\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** The actual volatility of an asset's returns over a historical window.\n\n**Definition:** RV = √(252/N × Σ r_t²) for daily log returns. High-frequency realized variance estimators (5-min, jump-robust) are more accurate than daily for short horizons. The realized-vs-implied spread (the 'variance risk premium') is positive on average — selling vol is a positive-EV but negatively-skewed strategy.", "source": "https://hedgefund.wiki/api/glossary/term/realized-volatility.json", "entity": {"type": "term", "id": "realized-volatility"}, "tokens_approx": 122, "tags": ["volatility", "estimation", "derivatives-options", "intermediate"]}
{"id": "term:primary-research", "title": "Primary Research", "text": "# Primary Research\n\n**Category:** equities-analysis · **Level:** intermediate\n\n**Summary:** Original investigative work — channel checks, satellite imagery, alternative data, expert calls — conducted directly by the fund, not sourced from sell-side reports.\n\n**Definition:** The differentiating activity of fundamental hedge funds. Standard tools: alternative data (credit card panel data, web-scraped pricing, satellite/aerial imagery, app downloads, foot traffic), expert network calls, channel checks (calling distributors, suppliers, customers), industry conference attendance, management meetings. Compliance scrutinizes for MNPI risk; data-vendor diligence is a multi-month process.", "source": "https://hedgefund.wiki/api/glossary/term/primary-research.json", "entity": {"type": "term", "id": "primary-research"}, "tokens_approx": 172, "tags": ["research", "fundamental", "equities-analysis", "intermediate"]}
{"id": "term:alternative-data", "title": "Alternative Data", "text": "# Alternative Data\n_(Alt Data)_\n\n**Category:** equities-analysis · **Level:** intermediate\n\n**Summary:** Non-traditional datasets used as inputs to investment decisions — credit card transactions, satellite imagery, app usage, web scraping, geolocation.\n\n**Definition:** Industry from $0 in 2010 to $10bn+ vendor revenue by 2025. Major categories: consumer (Yodlee, Earnest, Second Measure), web (similarweb, semrush), location (advan, placer), satellite (Planet, Maxar, Orbital Insight), supply chain (Panjiva, ImportGenius), social (Estimize, BotsForge, sentiment scoring). Compliance: MNPI screening, GDPR/CCPA review, vendor T&Cs review. Alpha decay is steep — datasets that produced 5% alpha in 2018 typically produce < 1% by 2024.", "source": "https://hedgefund.wiki/api/glossary/term/alternative-data.json", "entity": {"type": "term", "id": "alternative-data"}, "tokens_approx": 184, "tags": ["data", "research", "quant", "equities-analysis", "intermediate"]}
{"id": "term:alpha-decay", "title": "Alpha Decay", "text": "# Alpha Decay\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** The phenomenon by which an alpha signal's predictive power degrades as it is discovered and traded by more participants.\n\n**Definition:** Alpha decay rates vary by signal type: microstructure signals decay in months; alt-data signals in 1–3 years; fundamental quality signals over decades or never. Hedge funds maintain rolling research pipelines that constantly seed new signals to replace decaying ones. Decay accelerates with: signal publication, vendor data commercialization, capacity additions to a strategy.", "source": "https://hedgefund.wiki/api/glossary/term/alpha-decay.json", "entity": {"type": "term", "id": "alpha-decay"}, "tokens_approx": 150, "tags": ["quant", "research", "lifecycle", "quantitative-methods", "advanced"]}
{"id": "term:capacity", "title": "Capacity", "text": "# Capacity\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** The maximum AUM at which a strategy can be deployed without meaningfully degrading expected returns.\n\n**Definition:** Capacity is set by some combination of: market depth (% of ADV that can be traded without slippage), the number of independent bets available, and competition for the same signals. Stat arb capacity at a single shop: $5–15bn. Trend-following capacity: $100bn+ across many CTAs. Activist capacity: $20bn at a single fund. Closed-to-new-capital is the institutional credibility marker.", "source": "https://hedgefund.wiki/api/glossary/term/capacity.json", "entity": {"type": "term", "id": "capacity"}, "tokens_approx": 147, "tags": ["allocation", "scale", "portfolio-construction", "intermediate"]}
{"id": "term:pass-through-expenses", "title": "Pass-Through Expenses", "text": "# Pass-Through Expenses\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** Multi-strat platform fee model where actual operating expenses (PM comp, technology, financing, infrastructure) are charged to the fund instead of (or in addition to) a fixed management fee.\n\n**Definition:** Pass-through structures emerged at multi-strategy platforms (Citadel, Millennium, Point72) to fund the enormous cost of running pod businesses with elite PM compensation. Total expense ratios commonly run 5-8% gross. Investors receive itemized expense reports. The 2023 SEC Private Fund Adviser Rules sought to mandate enhanced disclosure; the rules were vacated by the Fifth Circuit in June 2024, but disclosure practices remain elevated. LP demand for the strategy has continued despite high gross fees because net Sharpe ratios of 2-4 still leave best-in-class net IRRs.", "source": "https://hedgefund.wiki/api/glossary/term/pass-through-expenses.json", "entity": {"type": "term", "id": "pass-through-expenses"}, "tokens_approx": 219, "tags": ["fees", "platform", "operations", "fund-operations", "intermediate"]}
{"id": "term:roll-yield", "title": "Roll Yield", "text": "# Roll Yield\n\n**Category:** commodities-futures · **Level:** intermediate\n\n**Summary:** The return component from rolling a futures position from one expiry to the next.\n\n**Definition:** When a long position rolls a back-month future cheaper than it sells the front month (backwardation), it earns positive roll yield; in contango it earns negative roll yield. Annualized roll yield for a passive long-only commodity index can swing ±15% depending on regime. The dominant driver of long-only commodity ETF returns over the long run.", "source": "https://hedgefund.wiki/api/glossary/term/roll-yield.json", "entity": {"type": "term", "id": "roll-yield"}, "tokens_approx": 133, "tags": ["commodities", "futures", "carry", "commodities-futures", "intermediate"]}
{"id": "term:dpi", "title": "DPI (Distributions to Paid-In)", "text": "# DPI (Distributions to Paid-In)\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** Cumulative cash distributions divided by paid-in capital — the realized portion of TVPI.\n\n**Definition:** DPI = Distributions / Paid-In. A DPI of 1.0× means investors have received their capital back in cash; DPI > 1.0× is realized profit. PE/VC funds aim for DPI > 1.0× by year 7-8 of a 10-year fund. DPI is the most rigorous performance metric because it measures only realized cash, free of mark-to-market judgment.", "source": "https://hedgefund.wiki/api/glossary/term/dpi.json", "entity": {"type": "term", "id": "dpi"}, "tokens_approx": 132, "tags": ["private", "performance", "alternative-investments", "intermediate"]}
{"id": "term:rvpi", "title": "RVPI (Residual Value to Paid-In)", "text": "# RVPI (Residual Value to Paid-In)\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** Unrealized NAV divided by paid-in capital — the unrealized portion of TVPI.\n\n**Definition:** RVPI = NAV / Paid-In. Together with DPI sums to TVPI. Subject to manager judgment on Level 3 marks; verified at exit but estimated until then.", "source": "https://hedgefund.wiki/api/glossary/term/rvpi.json", "entity": {"type": "term", "id": "rvpi"}, "tokens_approx": 87, "tags": ["private", "performance", "alternative-investments", "intermediate"]}
{"id": "term:founders-share-class", "title": "Founders Share Class", "text": "# Founders Share Class\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A discounted share class (e.g., 1/10 vs 1.5/20) for early or large investors who anchor a new fund's launch in exchange for a longer lock-up.\n\n**Definition:** Standard founders terms: 1% management / 10% performance, 2-year hard lock, capacity rights up to a threshold. Often capped at the lesser of 15% of fund or $25-50m. Some funds phase founders' investors into standard fees after a launch period; others offer perpetual founders economics.", "source": "https://hedgefund.wiki/api/glossary/term/founders-share-class.json", "entity": {"type": "term", "id": "founders-share-class"}, "tokens_approx": 134, "tags": ["fees", "launch", "fund-operations", "intermediate"]}
{"id": "term:administrator", "title": "Fund Administrator", "text": "# Fund Administrator\n\n**Category:** fund-operations · **Level:** intro\n\n**Summary:** Independent third-party that strikes NAV, processes subscriptions/redemptions, and provides investor reporting.\n\n**Definition:** Major administrators in 2026: SS&C GlobeOp, Citco, Apex, NAV Consulting, IQ-EQ, MUFG. Independent administration is post-Madoff baseline. Functions: NAV calculation (typically T+5 to T+15), AML/KYC of investors, capital activity processing, P&L allocation across share classes. Adminstrator selection is a focus of LP operational due diligence.", "source": "https://hedgefund.wiki/api/glossary/term/administrator.json", "entity": {"type": "term", "id": "administrator"}, "tokens_approx": 139, "tags": ["operations", "ops-dd", "fund-operations", "intro"]}
{"id": "term:mean-reversion", "title": "Mean Reversion", "text": "# Mean Reversion\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** The tendency for a series to return toward its long-run average.\n\n**Definition:** Statistical foundation of pairs trading, stat arb, and many short-horizon equity strategies. Tests: Augmented Dickey-Fuller (ADF), variance ratio (Lo-MacKinlay). Half-life in an OU process: ln(2)/θ. Mean reversion in returns coexists with long-horizon momentum — the term-structure of return autocorrelation matters.", "source": "https://hedgefund.wiki/api/glossary/term/mean-reversion.json", "entity": {"type": "term", "id": "mean-reversion"}, "tokens_approx": 122, "tags": ["quant", "time-series", "quantitative-methods", "intermediate"]}
{"id": "term:covered-interest-parity", "title": "Covered Interest Parity", "text": "# Covered Interest Parity\n_(CIP)_\n\n**Category:** global-markets · **Level:** intermediate\n\n**Summary:** The forward FX rate equals the spot rate adjusted by the interest rate differential between the two currencies.\n\n**Definition:** F/S = (1 + i_d) / (1 + i_f). Holds tightly in normal times (arbitrage by banks). CIP deviations have persisted post-2008 due to Basel III balance sheet costs, year-end window dressing, and FX swap market segmentation — measurable in cross-currency basis. The 'CIP failure' literature (Du-Tepper-Verdelhan) documents 30-100bp persistent deviations in major currency pairs.", "source": "https://hedgefund.wiki/api/glossary/term/covered-interest-parity.json", "entity": {"type": "term", "id": "covered-interest-parity"}, "tokens_approx": 151, "tags": ["fx", "arbitrage", "global-markets", "intermediate"]}
{"id": "term:uncovered-interest-parity", "title": "Uncovered Interest Parity", "text": "# Uncovered Interest Parity\n_(UIP)_\n\n**Category:** global-markets · **Level:** intermediate\n\n**Summary:** Theoretical equality where expected change in spot FX equals interest rate differential.\n\n**Definition:** E[ΔS] = i_d − i_f. Fails empirically — the 'forward premium puzzle' (Fama 1984). High-yielding currencies do not depreciate as theory predicts on average, generating the carry trade premium.", "source": "https://hedgefund.wiki/api/glossary/term/uncovered-interest-parity.json", "entity": {"type": "term", "id": "uncovered-interest-parity"}, "tokens_approx": 100, "tags": ["fx", "carry", "global-markets", "intermediate"]}
{"id": "term:section-3c1", "title": "Section 3(c)(1) Exemption", "text": "# Section 3(c)(1) Exemption\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Investment Company Act exclusion for funds with no more than 100 beneficial owners.\n\n**Definition:** Hedge funds rely on either 3(c)(1) (≤100 owners, all accredited) or 3(c)(7) (all QPs, no count cap) to avoid registering as investment companies. 3(c)(1) is suitable for emerging managers; 3(c)(7) for institutional scale.", "source": "https://hedgefund.wiki/api/glossary/term/section-3c1.json", "entity": {"type": "term", "id": "section-3c1"}, "tokens_approx": 106, "tags": ["regulation", "exemption", "regulatory-compliance", "intermediate"]}
{"id": "term:section-3c7", "title": "Section 3(c)(7) Exemption", "text": "# Section 3(c)(7) Exemption\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Investment Company Act exclusion for funds whose investors are all Qualified Purchasers.\n\n**Definition:** QP-only exemption removes the 100-investor cap of 3(c)(1). Practical scale limit is the 1934 Act's Section 12(g) record-holder threshold (2,000 holders / 500 non-accredited). Standard for institutional-scale funds.", "source": "https://hedgefund.wiki/api/glossary/term/section-3c7.json", "entity": {"type": "term", "id": "section-3c7"}, "tokens_approx": 106, "tags": ["regulation", "exemption", "regulatory-compliance", "intermediate"]}
{"id": "term:almgren-chriss", "title": "Almgren-Chriss Model", "text": "# Almgren-Chriss Model\n\n**Category:** trading-execution · **Level:** advanced\n\n**Summary:** Optimal execution framework that minimizes expected cost plus risk-aversion-weighted variance of cost.\n\n**Definition:** Trader minimizes E[X] + λ Var[X], producing a closed-form trading schedule with sinh decay. The foundational model behind institutional execution algorithms. Extensions: stochastic vol, transient impact (Obizhaeva-Wang), self-financing constraints.", "source": "https://hedgefund.wiki/api/glossary/term/almgren-chriss.json", "entity": {"type": "term", "id": "almgren-chriss"}, "tokens_approx": 115, "tags": ["execution", "model", "trading-execution", "advanced"]}
{"id": "term:algo-wheel", "title": "Algo Wheel", "text": "# Algo Wheel\n\n**Category:** trading-execution · **Level:** intermediate\n\n**Summary:** An execution-management system feature that randomly routes orders across competing broker algorithms to keep brokers honest via measured TCA.\n\n**Definition:** Buy-side traders configure a wheel with eligible algos for each order type (e.g., low-touch IS, VWAP). Orders are randomly allocated according to weights; performance is measured ex-post by TCA; weights shift toward better-performing algos. Major EMS providers: Bloomberg EMSX, FlexTrade, Charles River, Liquidnet.", "source": "https://hedgefund.wiki/api/glossary/term/algo-wheel.json", "entity": {"type": "term", "id": "algo-wheel"}, "tokens_approx": 140, "tags": ["execution", "best-ex", "trading-execution", "intermediate"]}
{"id": "term:iceberg-order", "title": "Iceberg Order", "text": "# Iceberg Order\n\n**Category:** market-microstructure · **Level:** intermediate\n\n**Summary:** An order that displays only a small portion of total size at the top of book, replenishing as fills occur.\n\n**Definition:** Allows institutions to work large orders without revealing intention. Most exchanges support native iceberg functionality with configurable visible size. HFTs use iceberg-detection signals to identify and front-run hidden interest, eroding the strategy's edge over time.", "source": "https://hedgefund.wiki/api/glossary/term/iceberg-order.json", "entity": {"type": "term", "id": "iceberg-order"}, "tokens_approx": 121, "tags": ["microstructure", "execution", "market-microstructure", "intermediate"]}
{"id": "term:kyle-lambda", "title": "Kyle's Lambda", "text": "# Kyle's Lambda\n\n**Category:** market-microstructure · **Level:** advanced\n\n**Summary:** The price-impact coefficient in Albert Kyle's (1985) microstructure model: ΔP = λ × Q.\n\n**Definition:** λ measures market depth; higher λ implies thinner liquidity. Estimable via regression of price changes on signed order flow. Used in execution-cost forecasting and as a relative-liquidity metric across stocks or time.", "source": "https://hedgefund.wiki/api/glossary/term/kyle-lambda.json", "entity": {"type": "term", "id": "kyle-lambda"}, "tokens_approx": 102, "tags": ["microstructure", "model", "market-microstructure", "advanced"]}
{"id": "term:vpin", "title": "VPIN (Volume-Synchronized PIN)", "text": "# VPIN (Volume-Synchronized PIN)\n\n**Category:** market-microstructure · **Level:** advanced\n\n**Summary:** Easley-López de Prado-O'Hara measure of order flow toxicity, designed for high-frequency markets.\n\n**Definition:** VPIN sub-samples by volume-equal buckets and computes |buy − sell| / (buy + sell). High VPIN signals informed flow / toxic conditions. Easley et al. argued VPIN spiked ahead of the 2010 Flash Crash.", "source": "https://hedgefund.wiki/api/glossary/term/vpin.json", "entity": {"type": "term", "id": "vpin"}, "tokens_approx": 104, "tags": ["microstructure", "hft", "market-microstructure", "advanced"]}
{"id": "term:geometric-brownian-motion", "title": "Geometric Brownian Motion", "text": "# Geometric Brownian Motion\n_(GBM)_\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Continuous-time stochastic process underlying the Black-Scholes model: dS = μS dt + σS dW.\n\n**Definition:** Log-returns are normally distributed with mean (μ−σ²/2)dt. Used as the baseline asset-price model in option pricing. Empirical violations: fat tails, jumps, vol clustering — addressed by extensions (Heston, Bates, GARCH, Lévy processes).", "source": "https://hedgefund.wiki/api/glossary/term/geometric-brownian-motion.json", "entity": {"type": "term", "id": "geometric-brownian-motion"}, "tokens_approx": 114, "tags": ["stochastic", "model", "quantitative-methods", "intermediate"]}
{"id": "term:csa", "title": "Credit Support Annex", "text": "# Credit Support Annex\n_(CSA)_\n\n**Category:** fund-operations · **Level:** advanced\n\n**Summary:** ISDA Master annex that governs collateral exchange between OTC derivatives counterparties.\n\n**Definition:** CSA terms specify eligible collateral types, haircuts, thresholds, minimum transfer amounts, settlement currency, and dispute resolution. Variation Margin is exchanged daily based on MTM moves; Initial Margin (since UMR phases 1-6) protects against the 10-day MPOR. Standardizing CSAs (1995, 2016 VM CSA) has been the backbone of post-2008 counterparty risk reduction.", "source": "https://hedgefund.wiki/api/glossary/term/csa.json", "entity": {"type": "term", "id": "csa"}, "tokens_approx": 143, "tags": ["legal", "derivatives", "collateral", "fund-operations", "advanced"]}
{"id": "term:asc-820", "title": "ASC 820", "text": "# ASC 820\n\n**Category:** accounting-valuation · **Level:** advanced\n\n**Summary:** FASB standard governing fair value measurement, including the Level 1/2/3 hierarchy and required disclosures.\n\n**Definition:** Originally SFAS 157 (2006), now ASC 820. Defines fair value as exit price in the principal market (or most advantageous market). Requires hierarchy categorization, transfer disclosures, and Level 3 roll-forward. The IFRS analogue is IFRS 13.", "source": "https://hedgefund.wiki/api/glossary/term/asc-820.json", "entity": {"type": "term", "id": "asc-820"}, "tokens_approx": 112, "tags": ["accounting", "valuation", "standards", "accounting-valuation", "advanced"]}
{"id": "term:channel-checks", "title": "Channel Checks", "text": "# Channel Checks\n\n**Category:** equities-analysis · **Level:** intermediate\n\n**Summary:** Direct outreach to a company's customers, suppliers, distributors, and former employees to validate or challenge management's narrative.\n\n**Definition:** Standard fundamental research practice. Compliance regulates: who can be contacted, what may be discussed, how findings are documented. MNPI risk is non-trivial; some funds restrict channel checks to former-employee panels and aggregated data.", "source": "https://hedgefund.wiki/api/glossary/term/channel-checks.json", "entity": {"type": "term", "id": "channel-checks"}, "tokens_approx": 121, "tags": ["research", "fundamental", "compliance", "equities-analysis", "intermediate"]}
{"id": "term:crowding", "title": "Crowding", "text": "# Crowding\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** The phenomenon where many funds hold similar positions, creating fragility on coordinated unwinds.\n\n**Definition:** Measured via 13F overlap, position concentration in alt-data, factor exposure regressions, and explicit broker crowding indices. Crowded shorts (high days-to-cover, high % of float) are more vulnerable to squeezes; crowded longs (high HF ownership %) underperform in deleveraging episodes. Goldman, Morgan Stanley, and JPM publish proprietary crowding indices used by macro overlay teams.", "source": "https://hedgefund.wiki/api/glossary/term/crowding.json", "entity": {"type": "term", "id": "crowding"}, "tokens_approx": 147, "tags": ["risk", "positioning", "quantitative-methods", "intermediate"]}
{"id": "term:cat-bond", "title": "Catastrophe Bond", "text": "# Catastrophe Bond\n\n**Category:** insurance-reinsurance · **Level:** intermediate\n\n**Summary:** A risk-linked security in which principal repayment is contingent on a defined catastrophe (named storm, earthquake, etc.) not occurring.\n\n**Definition:** Investor receives a coupon (typically T-bill + 4-12%) while the principal is held in a collateral trust. If a triggering event occurs (modeled, parametric, or industry-loss), principal is paid to the sponsor (typically a reinsurer or government). Outstanding cat bond market: ~$45bn (2025). Major sponsors: Munich Re, Swiss Re, USAA, FEMA, World Bank. ILS Capital Markets, Twelve Capital, Nephila are active investors.", "source": "https://hedgefund.wiki/api/glossary/term/cat-bond.json", "entity": {"type": "term", "id": "cat-bond"}, "tokens_approx": 167, "tags": ["insurance", "credit", "insurance-reinsurance", "intermediate"]}
{"id": "term:ils", "title": "Insurance-Linked Securities", "text": "# Insurance-Linked Securities\n_(ILS)_\n\n**Category:** insurance-reinsurance · **Level:** intermediate\n\n**Summary:** Securities whose performance is linked to insurance risk — cat bonds, ILWs, sidecars, collateralized reinsurance.\n\n**Definition:** Total ILS market ~$110bn (2025). Diversification appeal is genuine: catastrophe risk is uncorrelated with financial markets. The 'hard market' of 2023-24 (post 2017-22 loss-heavy years) produced multi-year double-digit returns. Key risk: model/parametric basis between modeled losses and actual claims.", "source": "https://hedgefund.wiki/api/glossary/term/ils.json", "entity": {"type": "term", "id": "ils"}, "tokens_approx": 137, "tags": ["insurance", "alternative", "insurance-reinsurance", "intermediate"]}
{"id": "term:cdx", "title": "CDX Index", "text": "# CDX Index\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** North American CDS index family: CDX.NA.IG (125 IG names), CDX.NA.HY (100 HY names). Standardized rolling on March 20 / September 20.\n\n**Definition:** Most liquid expression of broad US credit risk. Index spread is a weighted average of constituent CDS spreads. Trading typically focuses on the on-the-run series (highest liquidity). European analogue: iTraxx (Europe Main, Crossover). Major participants: hedge fund credit, dealers, and crossover macro funds.", "source": "https://hedgefund.wiki/api/glossary/term/cdx.json", "entity": {"type": "term", "id": "cdx"}, "tokens_approx": 136, "tags": ["credit", "index", "fixed-income-credit", "intermediate"]}
{"id": "term:delta-hedging", "title": "Delta Hedging", "text": "# Delta Hedging\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** Maintaining offsetting positions in the underlying so that the portfolio's delta is approximately zero.\n\n**Definition:** Long Δ × N shares per option for short option positions, short for long option positions. Rehedge frequency trades off tracking error vs transaction cost. Continuous hedging is the BS assumption; discrete hedging produces P&L variance proportional to gamma × σ² × Δt² (gamma scalping when long gamma).", "source": "https://hedgefund.wiki/api/glossary/term/delta-hedging.json", "entity": {"type": "term", "id": "delta-hedging"}, "tokens_approx": 128, "tags": ["options", "hedging", "derivatives-options", "intermediate"]}
{"id": "term:gamma-scalping", "title": "Gamma Scalping", "text": "# Gamma Scalping\n\n**Category:** derivatives-options · **Level:** advanced\n\n**Summary:** Actively delta-hedging a long-gamma position to monetize realized volatility.\n\n**Definition:** When long gamma, the delta becomes longer as spot rises and shorter as spot falls — selling high and buying low at each rebalance. Cumulative P&L from gamma scalping ≈ ½ × Γ × Σ(ΔS)². Profitable when realized > implied vol; loses theta when realized < implied. The fundamental long-vol P&L mechanism.", "source": "https://hedgefund.wiki/api/glossary/term/gamma-scalping.json", "entity": {"type": "term", "id": "gamma-scalping"}, "tokens_approx": 120, "tags": ["options", "trading", "derivatives-options", "advanced"]}
{"id": "term:volmageddon", "title": "Volmageddon", "text": "# Volmageddon\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** The Feb 5, 2018 vol spike that destroyed inverse-VIX ETPs (XIV, SVXY) overnight.\n\n**Definition:** VIX spiked from 17 to 38 intraday on Feb 5, 2018. Short-vol ETPs that rebalanced near close had to buy VIX futures, accelerating the move. XIV lost 96% in minutes; Credit Suisse retired the product days later. ~$3bn unwound. Marked the high-water mark of pre-COVID short-vol popularity.", "source": "https://hedgefund.wiki/api/glossary/term/volmageddon.json", "entity": {"type": "term", "id": "volmageddon"}, "tokens_approx": 118, "tags": ["vol", "etp", "case-study", "derivatives-options", "intermediate"]}
{"id": "term:risk-reversal", "title": "Risk Reversal", "text": "# Risk Reversal\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** Long an OTM call and short an OTM put (or vice versa) at equal delta — a synthetic forward exposure with vol-skew P&L.\n\n**Definition:** FX market quotes vol skew explicitly as risk-reversal pricing. Equity-index risk reversals tend to be short on the call side / long on the put — reflecting the structural put bid. Trading risk reversals isolates skew exposure.", "source": "https://hedgefund.wiki/api/glossary/term/risk-reversal.json", "entity": {"type": "term", "id": "risk-reversal"}, "tokens_approx": 113, "tags": ["options", "skew", "derivatives-options", "intermediate"]}
{"id": "term:vol-of-vol", "title": "Vol of Vol", "text": "# Vol of Vol\n\n**Category:** derivatives-options · **Level:** advanced\n\n**Summary:** The volatility of implied volatility itself; quantified by indices like the VVIX.\n\n**Definition:** When vol-of-vol is high, vega risk is large and the smile is more curved. CBOE publishes VVIX (vol of VIX). Stochastic vol models (Heston, SABR) parameterize vol-of-vol explicitly.", "source": "https://hedgefund.wiki/api/glossary/term/vol-of-vol.json", "entity": {"type": "term", "id": "vol-of-vol"}, "tokens_approx": 90, "tags": ["vol", "options", "derivatives-options", "advanced"]}
{"id": "term:premium-selling", "title": "Premium Selling", "text": "# Premium Selling\n\n**Category:** derivatives-options · **Level:** intermediate\n\n**Summary:** Strategies that systematically sell options to harvest the variance risk premium.\n\n**Definition:** Covered calls, cash-secured puts, iron condors, short straddles. Earns positive expected value (RV < IV on average) but with negatively-skewed payoff. Popular in retail (covered call ETFs ~$50bn AUM in 2025) and in institutional 'put-write' indexed strategies.", "source": "https://hedgefund.wiki/api/glossary/term/premium-selling.json", "entity": {"type": "term", "id": "premium-selling"}, "tokens_approx": 113, "tags": ["options", "income", "derivatives-options", "intermediate"]}
{"id": "term:interest-rate", "title": "Interest Rate", "text": "# Interest Rate\n\n**Category:** fixed-income-credit · **Level:** intro\n\n**Summary:** The price of money over time, expressed as a percentage per period.\n\n**Definition:** Multiple rate concepts: nominal vs real, short vs long, risk-free vs credit-risky, simple vs compound, spot vs forward. Hedge fund rates strategies trade across all these dimensions.", "source": "https://hedgefund.wiki/api/glossary/term/interest-rate.json", "entity": {"type": "term", "id": "interest-rate"}, "tokens_approx": 87, "tags": ["rates", "fixed-income-credit", "intro"]}
{"id": "term:carry", "title": "Carry", "text": "# Carry\n\n**Category:** global-markets · **Level:** intermediate\n\n**Summary:** The expected return of an asset assuming prices stay constant — yield, dividend, or roll income.\n\n**Definition:** FX carry = rate differential. Bond carry = coupon + roll-down. Commodity carry = roll yield - storage cost. Equity carry = dividend yield. Cross-asset carry strategies (Koijen-Moskowitz-Pedersen-Vrugt 2018) deliver positive Sharpe on average across asset classes.", "source": "https://hedgefund.wiki/api/glossary/term/carry.json", "entity": {"type": "term", "id": "carry"}, "tokens_approx": 113, "tags": ["macro", "factor", "global-markets", "intermediate"]}
{"id": "term:convenience-yield", "title": "Convenience Yield", "text": "# Convenience Yield\n\n**Category:** commodities-futures · **Level:** advanced\n\n**Summary:** The non-monetary benefit of holding a physical commodity rather than a derivative on it.\n\n**Definition:** Embedded in commodity term structure: F = S × e^((r + storage − convenience) × T). High convenience yield (tight physical) drives backwardation; low convenience yield drives contango.", "source": "https://hedgefund.wiki/api/glossary/term/convenience-yield.json", "entity": {"type": "term", "id": "convenience-yield"}, "tokens_approx": 95, "tags": ["commodities", "term-structure", "commodities-futures", "advanced"]}
{"id": "term:yield-to-maturity", "title": "Yield to Maturity", "text": "# Yield to Maturity\n_(YTM)_\n\n**Category:** fixed-income-credit · **Level:** intro\n\n**Summary:** The single discount rate that equates a bond's PV of cash flows to its current price.\n\n**Definition:** Solved iteratively (no closed form for coupon bonds). Assumes reinvestment of all coupons at YTM and holding to maturity. For zero-coupon bonds, YTM = (Face/Price)^(1/T) − 1.", "source": "https://hedgefund.wiki/api/glossary/term/yield-to-maturity.json", "entity": {"type": "term", "id": "yield-to-maturity"}, "tokens_approx": 93, "tags": ["fixed-income", "fixed-income-credit", "intro"]}
{"id": "term:key-rate-duration", "title": "Key Rate Duration", "text": "# Key Rate Duration\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** Sensitivity of a bond's price to a 1bp shift at a single point on the yield curve, holding other points fixed.\n\n**Definition:** Decomposes total duration into rate-bucket contributions (typically 2y, 5y, 10y, 30y). Used for non-parallel curve risk management — a portfolio can be duration-neutral on average yet exposed to slope/curvature shifts.", "source": "https://hedgefund.wiki/api/glossary/term/key-rate-duration.json", "entity": {"type": "term", "id": "key-rate-duration"}, "tokens_approx": 109, "tags": ["rates", "sensitivity", "fixed-income-credit", "advanced"]}
{"id": "term:negative-convexity", "title": "Negative Convexity", "text": "# Negative Convexity\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** When a bond's price falls faster as rates rise than it rises as rates fall — the inverse of standard bond behavior.\n\n**Definition:** Characteristic of MBS (prepayment option held by borrowers) and callable bonds (call option held by issuer). At low rates, prepayment/call option moves into the money, curtailing upside. Convexity-hedging by MBS portfolios drives episodic 'convexity events' that amplify rate moves.", "source": "https://hedgefund.wiki/api/glossary/term/negative-convexity.json", "entity": {"type": "term", "id": "negative-convexity"}, "tokens_approx": 126, "tags": ["rates", "mbs", "convexity", "fixed-income-credit", "advanced"]}
{"id": "term:recovery-rate", "title": "Recovery Rate", "text": "# Recovery Rate\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** The fraction of par recovered by a bondholder after a default.\n\n**Definition:** Standard recovery assumptions: 40% senior unsecured (US), 25% subordinated, 70% senior secured loans. Actual recoveries vary widely by industry and cycle. CDS settlement recovery is set by ISDA Determinations Committee auctions.", "source": "https://hedgefund.wiki/api/glossary/term/recovery-rate.json", "entity": {"type": "term", "id": "recovery-rate"}, "tokens_approx": 99, "tags": ["credit", "fixed-income-credit", "intermediate"]}
{"id": "term:vasicek-model", "title": "Vasicek Model", "text": "# Vasicek Model\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** Single-factor mean-reverting Gaussian short-rate model: dr = a(b − r)dt + σdW.\n\n**Definition:** First widely-used short-rate model (Vasicek 1977). Closed-form bond and option pricing. Allows negative rates (a feature post-2014). Calibration via OLS on historical rates or to swap surfaces. Successors: CIR, Hull-White, Black-Karasinski, LIBOR Market Model, SABR.", "source": "https://hedgefund.wiki/api/glossary/term/vasicek-model.json", "entity": {"type": "term", "id": "vasicek-model"}, "tokens_approx": 112, "tags": ["rates", "model", "fixed-income-credit", "advanced"]}
{"id": "term:cash-and-carry", "title": "Cash-and-Carry", "text": "# Cash-and-Carry\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** Long the cash asset, short the corresponding derivative, financed via repo to harvest the basis.\n\n**Definition:** Classic Treasury basis trade: long cash bond, short futures, financed via tri-party repo. In commodities: buy spot, store, short futures (only profitable if contango exceeds storage cost). In crypto: long spot, short perp, harvest funding rate.", "source": "https://hedgefund.wiki/api/glossary/term/cash-and-carry.json", "entity": {"type": "term", "id": "cash-and-carry"}, "tokens_approx": 112, "tags": ["arbitrage", "basis", "fixed-income-credit", "intermediate"]}
{"id": "term:crypto-cash-and-carry", "title": "Crypto Cash-and-Carry", "text": "# Crypto Cash-and-Carry\n\n**Category:** crypto-digital-assets · **Level:** intermediate\n\n**Summary:** Long spot crypto, short perpetual or quarterly futures to harvest basis or funding rate.\n\n**Definition:** When crypto perpetuals trade above spot (positive funding), longs pay shorts — a hedge fund running long spot / short perp earns the funding. Annualized rates of 10-50% have been common in bull markets. Returns to the basis trade collapse in bear markets when funding inverts.", "source": "https://hedgefund.wiki/api/glossary/term/crypto-cash-and-carry.json", "entity": {"type": "term", "id": "crypto-cash-and-carry"}, "tokens_approx": 120, "tags": ["crypto", "basis", "crypto-digital-assets", "intermediate"]}
{"id": "term:tri-party-repo", "title": "Tri-Party Repo", "text": "# Tri-Party Repo\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** A repo trade where a third-party agent (BNY Mellon, JPM) custodies and values collateral on behalf of both legs.\n\n**Definition:** US tri-party market is ~$5tn outstanding (2025). Reduces operational friction and provides standardized eligibility schedules. The 2008 GFC exposed wholesale funding fragility — daily unwind reform in 2010-2014 improved resilience. Major counterparties: hedge funds (basis trade financing), MMFs (cash investors), bank dealers (intermediation).", "source": "https://hedgefund.wiki/api/glossary/term/tri-party-repo.json", "entity": {"type": "term", "id": "tri-party-repo"}, "tokens_approx": 140, "tags": ["funding", "repo", "fixed-income-credit", "advanced"]}
{"id": "term:dip-financing", "title": "DIP Financing", "text": "# DIP Financing\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** Debtor-in-possession financing: super-senior loans extended to a Chapter 11 debtor to fund operations during reorganization.\n\n**Definition:** DIP loans are super-senior to all pre-petition debt. Court-approved priming. Yields typically 8-15% with hefty fees and warrants. Lenders are often the existing fulcrum holders (defensive DIP) or third parties (offensive DIP). Distressed funds compete aggressively for DIP roles — gaining information access and downstream restructuring leverage.", "source": "https://hedgefund.wiki/api/glossary/term/dip-financing.json", "entity": {"type": "term", "id": "dip-financing"}, "tokens_approx": 144, "tags": ["distressed", "credit", "restructuring", "hedge-fund-strategies", "advanced"]}
{"id": "term:loan-to-own", "title": "Loan-to-Own", "text": "# Loan-to-Own\n\n**Category:** hedge-fund-strategies · **Level:** advanced\n\n**Summary:** Distressed strategy of accumulating fulcrum debt with intent to convert to controlling equity through restructuring.\n\n**Definition:** The 21st century replacement for Carl Icahn-style activist equity raids. Distressed funds (Apollo, Oaktree, Elliott, Centerbridge) buy in at distressed prices, drive a plan of reorganization that converts their position to majority equity, then sell or relist post-emergence.", "source": "https://hedgefund.wiki/api/glossary/term/loan-to-own.json", "entity": {"type": "term", "id": "loan-to-own"}, "tokens_approx": 124, "tags": ["distressed", "restructuring", "hedge-fund-strategies", "advanced"]}
{"id": "term:waterfall", "title": "Waterfall", "text": "# Waterfall\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** The order in which a company's enterprise value is distributed across capital structure on liquidation or restructuring.\n\n**Definition:** Senior secured first, then senior unsecured, then subordinated, then preferred, then common. The fulcrum security is the class that runs out of recovery — the seniors above receive par, the juniors below receive nothing or new equity. Distressed waterfall analysis is the central skill of restructuring investing.", "source": "https://hedgefund.wiki/api/glossary/term/waterfall.json", "entity": {"type": "term", "id": "waterfall"}, "tokens_approx": 135, "tags": ["distressed", "capital-structure", "hedge-fund-strategies", "intermediate"]}
{"id": "term:13d-filing", "title": "Schedule 13D Filing", "text": "# Schedule 13D Filing\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** SEC filing required within 5 business days of acquiring more than 5% of a public company with active intent.\n\n**Definition:** 13D requires disclosure of identity, source of funds, purpose, and intentions (passive vs activist). Schedule 13G is a less-disclosure alternative for purely passive holders. The 2024 SEC amendment compressed the deadline from 10 to 5 business days. Activist funds typically time their position-build to file just inside the window for maximum surprise impact.", "source": "https://hedgefund.wiki/api/glossary/term/13d-filing.json", "entity": {"type": "term", "id": "13d-filing"}, "tokens_approx": 146, "tags": ["regulation", "activist", "regulatory-compliance", "intermediate"]}
{"id": "term:proxy-contest", "title": "Proxy Contest", "text": "# Proxy Contest\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** Solicitation of shareholder votes against management's slate, typically to elect dissident directors.\n\n**Definition:** Activist primary tool. Mailings, websites, ISS/Glass Lewis recommendations. The 2022 SEC universal proxy card rule required all nominees on a single ballot, lowering the cost of contests. Major proxy battles 2024-26: Disney/Peltz, Salesforce/Starboard, Norfolk Southern/Ancora.", "source": "https://hedgefund.wiki/api/glossary/term/proxy-contest.json", "entity": {"type": "term", "id": "proxy-contest"}, "tokens_approx": 121, "tags": ["activist", "governance", "regulatory-compliance", "advanced"]}
{"id": "term:poison-pill", "title": "Poison Pill", "text": "# Poison Pill\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** A shareholder rights plan that deters hostile acquisitions or activist campaigns by triggering severe dilution above a threshold.\n\n**Definition:** Typical trigger: 10-15% accumulation. On trigger, all shareholders except the triggerer receive rights to buy stock at deep discount. Used defensively in M&A and against activists. Delaware courts apply Unocal/Revlon scrutiny; modern 'NOL pills' are upheld more readily than traditional anti-takeover pills.", "source": "https://hedgefund.wiki/api/glossary/term/poison-pill.json", "entity": {"type": "term", "id": "poison-pill"}, "tokens_approx": 136, "tags": ["governance", "defense", "regulatory-compliance", "intermediate"]}
{"id": "term:mfn", "title": "Most Favored Nation Clause", "text": "# Most Favored Nation Clause\n_(MFN)_\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A side-letter provision granting an LP the right to elect into any superior terms granted to other LPs.\n\n**Definition:** MFNs are typically tiered (MFN with respect to LPs of equal or smaller commitment; MFN with all LPs only for specific term types). Administered by the GP, who provides each MFN'd LP a periodic schedule of competing terms. The most heavily negotiated clause in any side letter.", "source": "https://hedgefund.wiki/api/glossary/term/mfn.json", "entity": {"type": "term", "id": "mfn"}, "tokens_approx": 126, "tags": ["legal", "negotiation", "fund-operations", "intermediate"]}
{"id": "term:ocio", "title": "Outsourced CIO", "text": "# Outsourced CIO\n_(OCIO)_\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** An external manager hired to handle full investment management — manager selection, asset allocation, reporting — for an institutional asset owner.\n\n**Definition:** Replaced traditional FoFs for many endowments, foundations, and family offices post-2008. ~$3.5tn under OCIO management globally (2024). Major providers: Mercer, BlackRock, Russell, NEPC, Cambridge, Wilshire. Fees: 30-100bp on assets, generally lower than the historical FoF 1/10.", "source": "https://hedgefund.wiki/api/glossary/term/ocio.json", "entity": {"type": "term", "id": "ocio"}, "tokens_approx": 135, "tags": ["allocation", "institutional", "fund-operations", "intermediate"]}
{"id": "term:cta", "title": "Commodity Trading Advisor", "text": "# Commodity Trading Advisor\n_(CTA)_\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** A CFTC-regulated person providing advice or trading on futures, options on futures, or swaps.\n\n**Definition:** Registration with CFTC and NFA. Rule 4.7 exempts advisors to qualified eligible persons (QEPs) from much of the disclosure burden. Most managed futures funds operate as CTAs.", "source": "https://hedgefund.wiki/api/glossary/term/cta.json", "entity": {"type": "term", "id": "cta"}, "tokens_approx": 99, "tags": ["regulation", "futures", "regulatory-compliance", "intermediate"]}
{"id": "term:risk-budget", "title": "Risk Budget", "text": "# Risk Budget\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** An allocation of total portfolio risk (often expressed as VaR or vol contribution) across PMs, strategies, or factors.\n\n**Definition:** Multi-strat platforms allocate risk budgets to each PM (e.g., 40-80bp daily vol contribution). PMs can use leverage to monetize their budget; cuts cascade as drawdowns accumulate. Risk budgeting > capital budgeting because risk allocation respects diversification.", "source": "https://hedgefund.wiki/api/glossary/term/risk-budget.json", "entity": {"type": "term", "id": "risk-budget"}, "tokens_approx": 123, "tags": ["risk", "allocation", "portfolio-construction", "intermediate"]}
{"id": "term:marginal-risk-contribution", "title": "Marginal Risk Contribution", "text": "# Marginal Risk Contribution\n_(MRC)_\n\n**Category:** portfolio-construction · **Level:** advanced\n\n**Summary:** The contribution of an asset to total portfolio risk: w_i × (Σw)_i / σ_p.\n\n**Definition:** Sum of MRC × weight equals σ_p (Euler decomposition). Risk parity sets MRC equal across assets. Identifies which positions are 'expensive' from a risk perspective at the margin — useful in active risk management.", "source": "https://hedgefund.wiki/api/glossary/term/marginal-risk-contribution.json", "entity": {"type": "term", "id": "marginal-risk-contribution"}, "tokens_approx": 103, "tags": ["risk", "decomposition", "portfolio-construction", "advanced"]}
{"id": "term:efficient-frontier", "title": "Efficient Frontier", "text": "# Efficient Frontier\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** The set of portfolios offering the maximum expected return for each level of risk.\n\n**Definition:** Markowitz (1952). With a risk-free asset, the frontier becomes a straight line — the Capital Market Line — through the tangency portfolio. Empirically the unconstrained tangency is unstable; practical implementations use constraints, shrinkage, and Black-Litterman blending.", "source": "https://hedgefund.wiki/api/glossary/term/efficient-frontier.json", "entity": {"type": "term", "id": "efficient-frontier"}, "tokens_approx": 118, "tags": ["portfolio", "theory", "portfolio-construction", "intermediate"]}
{"id": "term:shrinkage-estimator", "title": "Shrinkage Estimator", "text": "# Shrinkage Estimator\n\n**Category:** portfolio-construction · **Level:** advanced\n\n**Summary:** An estimator that shrinks a sample covariance matrix toward a structured target to reduce estimation error.\n\n**Definition:** Ledoit-Wolf (2003) shrinkage toward a constant-correlation target is the standard. James-Stein shrinkage of the mean reduces optimization sensitivity. Both improve out-of-sample portfolio Sharpe meaningfully.", "source": "https://hedgefund.wiki/api/glossary/term/shrinkage-estimator.json", "entity": {"type": "term", "id": "shrinkage-estimator"}, "tokens_approx": 107, "tags": ["statistics", "portfolio", "portfolio-construction", "advanced"]}
{"id": "term:bayesian-prior", "title": "Bayesian Prior", "text": "# Bayesian Prior\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** A probability distribution representing pre-data beliefs, combined with the likelihood to produce a posterior.\n\n**Definition:** In portfolio construction (Black-Litterman), the equilibrium-implied returns serve as the prior; analyst views update it. In risk modeling, priors regularize parameter estimates when sample sizes are limited.", "source": "https://hedgefund.wiki/api/glossary/term/bayesian-prior.json", "entity": {"type": "term", "id": "bayesian-prior"}, "tokens_approx": 107, "tags": ["statistics", "quantitative-methods", "intermediate"]}
{"id": "term:value-factor", "title": "Value Factor", "text": "# Value Factor\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** The cross-sectional return spread between cheap and expensive stocks (typically by book/price, earnings/price, or composite multiples).\n\n**Definition:** HML in Fama-French. Documented since Graham-Dodd. Suffered a deep drawdown 2017-2020 ('value's lost decade'), partial recovery 2021-22, mixed since. Decomposed into: value-of-value (relative cheapness), structural value (industry mix), value-trap risk.", "source": "https://hedgefund.wiki/api/glossary/term/value-factor.json", "entity": {"type": "term", "id": "value-factor"}, "tokens_approx": 124, "tags": ["factor", "quantitative-methods", "intermediate"]}
{"id": "term:momentum-crash", "title": "Momentum Crash", "text": "# Momentum Crash\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** Severe drawdowns in cross-sectional momentum strategies, typically when low-quality losers suddenly outperform.\n\n**Definition:** Major events: Q1 2009 (junk rally off March lows), Aug 2007, Mar-Apr 2020. Daniel-Moskowitz (2016) identified bear-market reversals as the dominant driver. Modern momentum implementations include 'momentum crash insurance' via low-vol filters or vol scaling.", "source": "https://hedgefund.wiki/api/glossary/term/momentum-crash.json", "entity": {"type": "term", "id": "momentum-crash"}, "tokens_approx": 119, "tags": ["factor", "tail", "quantitative-methods", "advanced"]}
{"id": "term:stationarity", "title": "Stationarity", "text": "# Stationarity\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** A stochastic process whose statistical properties (mean, variance, autocorrelation) do not vary over time.\n\n**Definition:** Strong stationarity: full distribution invariant. Weak (covariance) stationarity: first two moments invariant. Most financial returns are weakly stationary; prices and yields are not (must be differenced or modeled as I(1)). Tests: ADF, KPSS, Phillips-Perron.", "source": "https://hedgefund.wiki/api/glossary/term/stationarity.json", "entity": {"type": "term", "id": "stationarity"}, "tokens_approx": 118, "tags": ["statistics", "time-series", "quantitative-methods", "intermediate"]}
{"id": "term:kalman-filter", "title": "Kalman Filter", "text": "# Kalman Filter\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** Recursive algorithm that estimates the hidden state of a linear-Gaussian system from noisy observations.\n\n**Definition:** Used in finance for: dynamic beta estimation, latent factor extraction, dynamic hedge ratio in pairs trading, state-space term-structure models. Computationally O(n³) per step — practical for moderate state dimensions.", "source": "https://hedgefund.wiki/api/glossary/term/kalman-filter.json", "entity": {"type": "term", "id": "kalman-filter"}, "tokens_approx": 107, "tags": ["statistics", "filter", "quantitative-methods", "advanced"]}
{"id": "term:log-optimal-portfolio", "title": "Log-Optimal Portfolio", "text": "# Log-Optimal Portfolio\n\n**Category:** portfolio-construction · **Level:** advanced\n\n**Summary:** The portfolio that maximizes the expected logarithm of wealth — Kelly's growth-optimal solution.\n\n**Definition:** Kelly (1956), Latane (1959), Thorp (1969). Maximizes long-run geometric growth rate. Outperforms any other strategy almost surely as N → ∞. In practice, fractional Kelly is preferred to control drawdowns.", "source": "https://hedgefund.wiki/api/glossary/term/log-optimal-portfolio.json", "entity": {"type": "term", "id": "log-optimal-portfolio"}, "tokens_approx": 104, "tags": ["portfolio", "growth", "portfolio-construction", "advanced"]}
{"id": "term:fractional-kelly", "title": "Fractional Kelly", "text": "# Fractional Kelly\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** A scaled-down Kelly bet (typically half-Kelly) that trades growth for drawdown reduction.\n\n**Definition:** Half-Kelly delivers ~75% of the expected log growth with ~25% of the variance. Quarter-Kelly is common for institutional allocators. The compromise reflects that estimation error in μ and σ makes full Kelly significantly riskier than the math suggests.", "source": "https://hedgefund.wiki/api/glossary/term/fractional-kelly.json", "entity": {"type": "term", "id": "fractional-kelly"}, "tokens_approx": 114, "tags": ["portfolio", "sizing", "portfolio-construction", "intermediate"]}
{"id": "term:fundamental-law-active-management", "title": "Fundamental Law of Active Management", "text": "# Fundamental Law of Active Management\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** Grinold's identity: IR ≈ IC × √breadth.\n\n**Definition:** Decomposes information ratio into per-bet skill (IC) and number of independent bets per year (breadth). Implies: a low-IC signal applied to thousands of names can outperform a high-IC signal on a few. The math reason quants chase breadth.", "source": "https://hedgefund.wiki/api/glossary/term/fundamental-law-active-management.json", "entity": {"type": "term", "id": "fundamental-law-active-management"}, "tokens_approx": 101, "tags": ["quant", "theory", "quantitative-methods", "advanced"]}
{"id": "term:amihud-illiquidity", "title": "Amihud Illiquidity", "text": "# Amihud Illiquidity\n\n**Category:** market-microstructure · **Level:** advanced\n\n**Summary:** Average absolute return per dollar of volume — a low-frequency proxy for market impact.\n\n**Definition:** ILLIQ = mean(|return| / dollar volume). Higher = more illiquid. Robust across regimes and asset classes; the workhorse illiquidity measure in academic literature. Amihud-weighted long-short portfolios capture an illiquidity premium.", "source": "https://hedgefund.wiki/api/glossary/term/amihud-illiquidity.json", "entity": {"type": "term", "id": "amihud-illiquidity"}, "tokens_approx": 107, "tags": ["microstructure", "liquidity", "market-microstructure", "advanced"]}
{"id": "term:ats", "title": "Alternative Trading System", "text": "# Alternative Trading System\n_(ATS)_\n\n**Category:** market-microstructure · **Level:** intermediate\n\n**Summary:** A non-exchange trading venue regulated under SEC Reg ATS — includes dark pools and ECNs.\n\n**Definition:** ATSs file Form ATS-N detailing operations, subscriber types, and order handling. Major US ATSs in 2026: UBS ATS, Sigma X, IEX, Liquidnet, MS Pool, Crossfinder. Aggregate ATS share ~12-15% of US equity volume.", "source": "https://hedgefund.wiki/api/glossary/term/ats.json", "entity": {"type": "term", "id": "ats"}, "tokens_approx": 107, "tags": ["microstructure", "venue", "market-microstructure", "intermediate"]}
{"id": "term:midpoint-peg", "title": "Midpoint Peg", "text": "# Midpoint Peg\n\n**Category:** market-microstructure · **Level:** intermediate\n\n**Summary:** An order type that prices at the midpoint of the National Best Bid and Offer (NBBO).\n\n**Definition:** Hidden order type used in dark pools. Earns half-spread relative to taking liquidity, but suffers adverse selection when the midpoint moves before fill. IEX's discretionary peg adds latency arb protection.", "source": "https://hedgefund.wiki/api/glossary/term/midpoint-peg.json", "entity": {"type": "term", "id": "midpoint-peg"}, "tokens_approx": 99, "tags": ["microstructure", "execution", "market-microstructure", "intermediate"]}
{"id": "term:effective-spread", "title": "Effective Spread", "text": "# Effective Spread\n\n**Category:** market-microstructure · **Level:** intermediate\n\n**Summary:** Twice the absolute difference between trade price and the midpoint quote at the time of execution.\n\n**Definition:** Effective spread = 2 × |P_trade − P_mid|. Reflects what the trader actually paid (after price improvement). Always ≤ quoted spread. Realized spread (effective spread minus permanent impact) measures market maker profit.", "source": "https://hedgefund.wiki/api/glossary/term/effective-spread.json", "entity": {"type": "term", "id": "effective-spread"}, "tokens_approx": 107, "tags": ["microstructure", "execution-quality", "market-microstructure", "intermediate"]}
{"id": "term:market-maker", "title": "Market Maker", "text": "# Market Maker\n\n**Category:** market-microstructure · **Level:** intro\n\n**Summary:** A firm that posts continuous two-sided quotes (bid and ask), profiting from the spread net of inventory and adverse-selection costs.\n\n**Definition:** Major US equity market makers in 2026: Citadel Securities, Virtu, Jane Street, Hudson River Trading, Two Sigma Securities. Designated market maker (DMM) on NYSE; lead market maker (LMM) on Nasdaq. Options market makers: Citadel, Susquehanna, Optiver, IMC, Jump.", "source": "https://hedgefund.wiki/api/glossary/term/market-maker.json", "entity": {"type": "term", "id": "market-maker"}, "tokens_approx": 124, "tags": ["microstructure", "liquidity", "market-microstructure", "intro"]}
{"id": "term:market-impact", "title": "Market Impact", "text": "# Market Impact\n\n**Category:** trading-execution · **Level:** intermediate\n\n**Summary:** The adverse price movement caused by one's own trading activity.\n\n**Definition:** Decomposed into temporary (recovers post-trade) and permanent (persists) impact. Square-root impact model: ΔP/σ ≈ Y × σ × √(Q/V), where Y ≈ 1 for equities (Almgren et al. 2005). Capacity is largely a market-impact constraint.", "source": "https://hedgefund.wiki/api/glossary/term/market-impact.json", "entity": {"type": "term", "id": "market-impact"}, "tokens_approx": 99, "tags": ["execution", "cost", "trading-execution", "intermediate"]}
{"id": "term:variance-risk-premium", "title": "Variance Risk Premium", "text": "# Variance Risk Premium\n_(VRP)_\n\n**Category:** derivatives-options · **Level:** advanced\n\n**Summary:** The persistent gap between implied and realized variance — investors pay a premium to hedge volatility.\n\n**Definition:** VRP = E[implied² − realized²] > 0 on average across most markets. The fundamental return source for short-vol strategies (variance swaps, short straddles, put writing). Punctuated by sharp losses during vol spikes — the textbook negatively-skewed strategy.", "source": "https://hedgefund.wiki/api/glossary/term/variance-risk-premium.json", "entity": {"type": "term", "id": "variance-risk-premium"}, "tokens_approx": 120, "tags": ["vol", "premium", "derivatives-options", "advanced"]}
{"id": "term:skew", "title": "Skew", "text": "# Skew\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** The third standardized moment of a distribution; in options, the slope of the implied-vol smile.\n\n**Definition:** Statistical skew: positive = long right tail, negative = long left tail. Equity returns are negatively skewed. Options market skew (put-call IV asymmetry) reflects demand for downside hedging. SKEW index from CBOE measures the implied skewness in SPX options.", "source": "https://hedgefund.wiki/api/glossary/term/skew.json", "entity": {"type": "term", "id": "skew"}, "tokens_approx": 114, "tags": ["statistics", "options", "quantitative-methods", "intermediate"]}
{"id": "term:term-structure", "title": "Term Structure", "text": "# Term Structure\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** The relationship between yields/prices and time to maturity, holding credit/instrument type fixed.\n\n**Definition:** Yield curve in rates; futures curve in commodities; vol term structure in options. Decomposed (Nelson-Siegel, Svensson) into level, slope, and curvature components. Three-factor PCA explains > 99% of curve moves.", "source": "https://hedgefund.wiki/api/glossary/term/term-structure.json", "entity": {"type": "term", "id": "term-structure"}, "tokens_approx": 105, "tags": ["rates", "commodities", "term-structure", "fixed-income-credit", "intermediate"]}
{"id": "term:term-premium", "title": "Term Premium", "text": "# Term Premium\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** The compensation for holding longer-duration bonds beyond what expected future short rates would imply.\n\n**Definition:** Long yield = average expected short rate + term premium. Negative term premium prevailed 2014-2021 due to QE. Modeling: ACM (Adrian-Crump-Moench) and KW (Kim-Wright) are the standard Fed estimates.", "source": "https://hedgefund.wiki/api/glossary/term/term-premium.json", "entity": {"type": "term", "id": "term-premium"}, "tokens_approx": 101, "tags": ["rates", "macro", "fixed-income-credit", "advanced"]}
{"id": "term:recession-indicator", "title": "Recession Indicator", "text": "# Recession Indicator\n\n**Category:** macroeconomics · **Level:** intermediate\n\n**Summary:** Economic or market signal historically associated with subsequent recession onset.\n\n**Definition:** Most-cited: 2s10s and 3M-10Y inversions, Sahm Rule (3-month average unemployment rate > 0.5pp above 12-month low), LEI six-month change negative, NY Fed yield-curve recession probability model. None has a perfect track record — the post-2022 inversion was the longest without a follow-on recession.", "source": "https://hedgefund.wiki/api/glossary/term/recession-indicator.json", "entity": {"type": "term", "id": "recession-indicator"}, "tokens_approx": 122, "tags": ["macro", "cycle", "macroeconomics", "intermediate"]}
{"id": "term:fiscal-dominance", "title": "Fiscal Dominance", "text": "# Fiscal Dominance\n\n**Category:** macroeconomics · **Level:** advanced\n\n**Summary:** A regime in which monetary policy is constrained by fiscal needs — central banks cannot raise rates without triggering debt-service crises.\n\n**Definition:** Sargent-Wallace 'unpleasant monetarist arithmetic'. Becomes acute at high debt/GDP and short debt average maturity. The 2024-26 US fiscal trajectory has put fiscal dominance back in the macro discussion. Policy implications: structurally higher inflation tolerance, larger central bank balance sheets, and YCC-adjacent interventions.", "source": "https://hedgefund.wiki/api/glossary/term/fiscal-dominance.json", "entity": {"type": "term", "id": "fiscal-dominance"}, "tokens_approx": 143, "tags": ["macro", "policy", "macroeconomics", "advanced"]}
{"id": "term:monetary-policy", "title": "Monetary Policy", "text": "# Monetary Policy\n\n**Category:** macroeconomics · **Level:** intro\n\n**Summary:** Central bank actions to influence money supply, interest rates, credit conditions, and inflation.\n\n**Definition:** Tools: policy rate, balance sheet (QE/QT), forward guidance, reserve requirements, FX intervention, macroprudential measures. The 2008-2024 era saw central bank balance sheets expand from 5% to 30%+ of GDP across major economies.", "source": "https://hedgefund.wiki/api/glossary/term/monetary-policy.json", "entity": {"type": "term", "id": "monetary-policy"}, "tokens_approx": 106, "tags": ["macro", "macroeconomics", "intro"]}
{"id": "term:neutral-rate", "title": "Neutral Rate", "text": "# Neutral Rate\n_(r*)_\n\n**Category:** macroeconomics · **Level:** advanced\n\n**Summary:** The real interest rate consistent with full employment and stable inflation — neither stimulative nor restrictive.\n\n**Definition:** Unobserved; estimated via macro models (Laubach-Williams, Holston-Laubach-Williams). Estimates fell from ~3% in 1990s to ~0.5% in 2010s, debated to be rising again post-pandemic. Central to Fed framework: policy is restrictive when real fed funds > r*.", "source": "https://hedgefund.wiki/api/glossary/term/neutral-rate.json", "entity": {"type": "term", "id": "neutral-rate"}, "tokens_approx": 118, "tags": ["macro", "theory", "macroeconomics", "advanced"]}
{"id": "term:em-debt", "title": "Emerging Market Debt", "text": "# Emerging Market Debt\n\n**Category:** global-markets · **Level:** intermediate\n\n**Summary:** Sovereign and corporate debt issued by emerging market countries, in either hard currency (USD/EUR) or local currency.\n\n**Definition:** Hard currency (USD): JPM EMBI Global ~$1.5tn outstanding. Local currency: GBI-EM ~$2.5tn. Hedge fund EM debt strategies: long/short sovereign, distressed sovereign (Argentina 2001/2014/2020, Venezuela, Lebanon, Sri Lanka), CDS basis, corporate event-driven.", "source": "https://hedgefund.wiki/api/glossary/term/em-debt.json", "entity": {"type": "term", "id": "em-debt"}, "tokens_approx": 121, "tags": ["em", "credit", "global-markets", "intermediate"]}
{"id": "term:sovereign-cds", "title": "Sovereign CDS", "text": "# Sovereign CDS\n\n**Category:** fixed-income-credit · **Level:** advanced\n\n**Summary:** Credit default swap on sovereign reference entities.\n\n**Definition:** Liquid for top-30 sovereigns; thin elsewhere. ISDA defines specific sovereign credit events. The 2012 Greek sovereign restructuring was the first major sovereign CDS event under standardized documentation. Sovereign CDS spreads embed both default risk and currency redenomination risk.", "source": "https://hedgefund.wiki/api/glossary/term/sovereign-cds.json", "entity": {"type": "term", "id": "sovereign-cds"}, "tokens_approx": 110, "tags": ["credit", "sovereign", "fixed-income-credit", "advanced"]}
{"id": "term:anchoring", "title": "Anchoring", "text": "# Anchoring\n\n**Category:** behavioral-finance · **Level:** intro\n\n**Summary:** Cognitive bias where individuals rely too heavily on the first piece of information encountered when making decisions.\n\n**Definition:** Tversky-Kahneman (1974). In markets: investors anchor on purchase price (disposition effect), 52-week highs/lows, IPO prices, prior analyst targets. Drives sticky valuations and slow adjustment to new information.", "source": "https://hedgefund.wiki/api/glossary/term/anchoring.json", "entity": {"type": "term", "id": "anchoring"}, "tokens_approx": 107, "tags": ["behavioral", "behavioral-finance", "intro"]}
{"id": "term:loss-aversion", "title": "Loss Aversion", "text": "# Loss Aversion\n\n**Category:** behavioral-finance · **Level:** intro\n\n**Summary:** Tendency to feel losses more strongly than equivalent gains, by an empirical factor of ~2x.\n\n**Definition:** Kahneman-Tversky prospect theory (1979). λ ≈ 2.25. Drives the disposition effect (selling winners too soon, holding losers too long), home bias, and reluctance to rebalance.", "source": "https://hedgefund.wiki/api/glossary/term/loss-aversion.json", "entity": {"type": "term", "id": "loss-aversion"}, "tokens_approx": 91, "tags": ["behavioral", "behavioral-finance", "intro"]}
{"id": "term:overconfidence-bias", "title": "Overconfidence Bias", "text": "# Overconfidence Bias\n\n**Category:** behavioral-finance · **Level:** intermediate\n\n**Summary:** Systematic tendency to overestimate one's knowledge, abilities, or precision of estimates.\n\n**Definition:** Manifests in trading as excessive turnover and concentrated bets. Barber-Odean (2000) showed retail traders' overconfidence destroys ~6.5% of returns annually via excess trading. Survives even after expensive feedback — partly because outcomes are noisy enough to confirm any belief.", "source": "https://hedgefund.wiki/api/glossary/term/overconfidence-bias.json", "entity": {"type": "term", "id": "overconfidence-bias"}, "tokens_approx": 121, "tags": ["behavioral", "behavioral-finance", "intermediate"]}
{"id": "term:herding", "title": "Herding", "text": "# Herding\n\n**Category:** behavioral-finance · **Level:** intro\n\n**Summary:** Tendency to follow others' actions rather than acting on private information.\n\n**Definition:** Drives momentum, bubbles, and post-news drift. Banerjee (1992) information cascades model. Manifests in HF crowding (13F overlap), in IPO subscription, in factor exposures.", "source": "https://hedgefund.wiki/api/glossary/term/herding.json", "entity": {"type": "term", "id": "herding"}, "tokens_approx": 86, "tags": ["behavioral", "behavioral-finance", "intro"]}
{"id": "term:narrative-fallacy", "title": "Narrative Fallacy", "text": "# Narrative Fallacy\n\n**Category:** behavioral-finance · **Level:** intermediate\n\n**Summary:** The tendency to construct simple causal stories from complex or random data.\n\n**Definition:** Taleb (2007). In markets: post-hoc 'why the market moved' narratives, attribution of returns to skill rather than noise, dismissal of base rates in favor of compelling case studies.", "source": "https://hedgefund.wiki/api/glossary/term/narrative-fallacy.json", "entity": {"type": "term", "id": "narrative-fallacy"}, "tokens_approx": 92, "tags": ["behavioral", "behavioral-finance", "intermediate"]}
{"id": "term:private-equity", "title": "Private Equity", "text": "# Private Equity\n_(PE)_\n\n**Category:** alternative-investments · **Level:** intro\n\n**Summary:** Investment in private companies, typically via leveraged buyouts (LBOs), growth equity, or venture capital.\n\n**Definition:** PE structure: 10-year closed-end LP, GP commitment 1-2%, 2/20 fee, hurdle ~8%, J-curve. Major firms: Blackstone, KKR, Apollo, CVC, Carlyle, Bain Capital, TPG. Hedge fund / PE convergence: long-dated 'hybrid' vehicles, GP stakes (Petershill, Dyal), co-invest sleeves.", "source": "https://hedgefund.wiki/api/glossary/term/private-equity.json", "entity": {"type": "term", "id": "private-equity"}, "tokens_approx": 121, "tags": ["private", "alternative", "alternative-investments", "intro"]}
{"id": "term:co-investment", "title": "Co-Investment", "text": "# Co-Investment\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** Direct investment alongside a sponsor in a single deal, typically with reduced or zero fees.\n\n**Definition:** Common in PE; less common in hedge funds. LP allocates capital to a specific deal alongside the fund's LP commitment. Fees: typically 0% management / 10-20% promote, or zero on smaller commitments. Major LPs (CalPERS, GIC, ADIA) have built dedicated co-invest programs to reduce blended fees.", "source": "https://hedgefund.wiki/api/glossary/term/co-investment.json", "entity": {"type": "term", "id": "co-investment"}, "tokens_approx": 124, "tags": ["private", "fees", "alternative-investments", "intermediate"]}
{"id": "term:illiquidity-premium", "title": "Illiquidity Premium", "text": "# Illiquidity Premium\n\n**Category:** alternative-investments · **Level:** intermediate\n\n**Summary:** Excess return demanded for holding assets that cannot be quickly converted to cash at a fair price.\n\n**Definition:** Pastor-Stambaugh (2003) found ~3-4%/yr equity illiquidity premium. PE return premium over public equity (the 'illiquidity premium') has compressed over the past decade as PE AUM scaled. Disputed: Phalippon argues the premium has largely disappeared net of fees.", "source": "https://hedgefund.wiki/api/glossary/term/illiquidity-premium.json", "entity": {"type": "term", "id": "illiquidity-premium"}, "tokens_approx": 119, "tags": ["alternative", "premium", "alternative-investments", "intermediate"]}
{"id": "term:ev-ebitda", "title": "EV/EBITDA", "text": "# EV/EBITDA\n\n**Category:** equities-analysis · **Level:** intro\n\n**Summary:** Enterprise value divided by EBITDA — capital-structure-neutral valuation multiple.\n\n**Definition:** EV = Equity Value + Debt − Cash. Better than P/E for cross-leverage comparability. Standard PE multiple in LBO modeling (entry/exit), in M&A precedent transactions, and in trading comp analysis.", "source": "https://hedgefund.wiki/api/glossary/term/ev-ebitda.json", "entity": {"type": "term", "id": "ev-ebitda"}, "tokens_approx": 93, "tags": ["valuation", "equity", "equities-analysis", "intro"]}
{"id": "term:free-cash-flow-yield", "title": "Free Cash Flow Yield", "text": "# Free Cash Flow Yield\n\n**Category:** equities-analysis · **Level:** intro\n\n**Summary:** Free cash flow divided by enterprise value (or market cap) — cash earnings yield.\n\n**Definition:** FCF = CFO − capex (sometimes adjusted for SBC, leases, working capital normalization). FCF yield is the value investor's go-to metric — harder to game than reported earnings.", "source": "https://hedgefund.wiki/api/glossary/term/free-cash-flow-yield.json", "entity": {"type": "term", "id": "free-cash-flow-yield"}, "tokens_approx": 90, "tags": ["valuation", "equity", "equities-analysis", "intro"]}
{"id": "term:roic", "title": "ROIC", "text": "# ROIC\n\n**Category:** equities-analysis · **Level:** intermediate\n\n**Summary:** Return on Invested Capital — NOPAT divided by invested capital.\n\n**Definition:** Measures capital productivity independent of capital structure. Compounding companies sustain ROIC > WACC for decades. Key input to economic-value-added (EVA) and McKinsey's value driver framework.", "source": "https://hedgefund.wiki/api/glossary/term/roic.json", "entity": {"type": "term", "id": "roic"}, "tokens_approx": 89, "tags": ["fundamentals", "quality", "equities-analysis", "intermediate"]}
{"id": "term:sfdr", "title": "SFDR", "text": "# SFDR\n\n**Category:** esg-sustainable · **Level:** intermediate\n\n**Summary:** EU regulation requiring asset managers to classify funds as Article 6, 8, or 9 based on sustainability characteristics.\n\n**Definition:** Article 8: 'promotes' E/S characteristics. Article 9: explicit sustainable investment objective. Major reclassification waves in 2022-23 as ESMA tightened expectations. PAI (Principal Adverse Impact) statements required.", "source": "https://hedgefund.wiki/api/glossary/term/sfdr.json", "entity": {"type": "term", "id": "sfdr"}, "tokens_approx": 108, "tags": ["regulation", "esg", "esg-sustainable", "intermediate"]}
{"id": "term:climate-var", "title": "Climate VaR", "text": "# Climate VaR\n\n**Category:** esg-sustainable · **Level:** advanced\n\n**Summary:** Extension of VaR that incorporates climate-related transition and physical risks.\n\n**Definition:** Methodologies: MSCI Climate VaR, Ortec Finance, Carbon Delta. Measures portfolio NPV impact under transition scenarios (1.5°C / 2°C / 3°C) over 15-year horizons. Increasingly required by EU TCFD/ISSB reporting.", "source": "https://hedgefund.wiki/api/glossary/term/climate-var.json", "entity": {"type": "term", "id": "climate-var"}, "tokens_approx": 97, "tags": ["esg", "risk", "esg-sustainable", "advanced"]}
{"id": "term:transition-risk", "title": "Transition Risk", "text": "# Transition Risk\n\n**Category:** esg-sustainable · **Level:** intermediate\n\n**Summary:** Financial risk from the transition to a low-carbon economy — policy, technology, market preference shifts.\n\n**Definition:** Analytical buckets: policy/legal, technology, market, reputation. Sectors most exposed: energy, materials, autos, utilities. Stranded-asset risk — fossil reserves that cannot be burned under net-zero pathways.", "source": "https://hedgefund.wiki/api/glossary/term/transition-risk.json", "entity": {"type": "term", "id": "transition-risk"}, "tokens_approx": 105, "tags": ["esg", "risk", "esg-sustainable", "intermediate"]}
{"id": "term:scope-3-emissions", "title": "Scope 3 Emissions", "text": "# Scope 3 Emissions\n\n**Category:** esg-sustainable · **Level:** intermediate\n\n**Summary:** Indirect GHG emissions in a company's value chain not under direct operational control.\n\n**Definition:** GHG Protocol Scope 1 (direct operations), Scope 2 (purchased energy), Scope 3 (everything else: supply chain, transport, product use, end-of-life). For most companies Scope 3 dwarfs 1+2. Heavily debated: methodology, data quality, double-counting.", "source": "https://hedgefund.wiki/api/glossary/term/scope-3-emissions.json", "entity": {"type": "term", "id": "scope-3-emissions"}, "tokens_approx": 110, "tags": ["esg", "emissions", "esg-sustainable", "intermediate"]}
{"id": "term:tokenized-fund", "title": "Tokenized Fund", "text": "# Tokenized Fund\n\n**Category:** crypto-digital-assets · **Level:** advanced\n\n**Summary:** Fund interests issued as on-chain tokens, typically ERC-20 or ERC-3643 with permissioning.\n\n**Definition:** BlackRock BUIDL (USD treasuries on Ethereum), Franklin OnChain Money, Ondo OUSG. Total tokenized money market funds ~$2bn (2024). Promises: 24/7 settlement, programmable composability, fractional access. Constraints: KYC/AML still gates investor onboarding; secondary liquidity remains thin.", "source": "https://hedgefund.wiki/api/glossary/term/tokenized-fund.json", "entity": {"type": "term", "id": "tokenized-fund"}, "tokens_approx": 122, "tags": ["crypto", "tokenization", "crypto-digital-assets", "advanced"]}
{"id": "term:mev", "title": "MEV", "text": "# MEV\n\n**Category:** crypto-digital-assets · **Level:** advanced\n\n**Summary:** Profits extractable from reordering, including, or excluding transactions in a block.\n\n**Definition:** Originally 'miner extractable value', renamed for proof-of-stake. Forms: arbitrage, liquidations, sandwich attacks, JIT (just-in-time liquidity). Ethereum MEV ~$700m+ annual extracted (2024). Specialized firms (Flashbots, Wintermute, Jump) compete; MEV-Boost relays separate block building from validation.", "source": "https://hedgefund.wiki/api/glossary/term/mev.json", "entity": {"type": "term", "id": "mev"}, "tokens_approx": 122, "tags": ["crypto", "extraction", "crypto-digital-assets", "advanced"]}
{"id": "term:research-unbundling", "title": "Research Unbundling", "text": "# Research Unbundling\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** MiFID II requirement that asset managers pay for sell-side research separately from execution.\n\n**Definition:** Effective Jan 2018. Reduced sell-side research budgets by 30-50%; analyst coverage of small/mid caps shrunk. The 2024 EU Listing Act allows opt-in rebundling as a partial reversal. SEC granted no-action relief expiring 2023, leaving US managers in regulatory limbo.", "source": "https://hedgefund.wiki/api/glossary/term/research-unbundling.json", "entity": {"type": "term", "id": "research-unbundling"}, "tokens_approx": 118, "tags": ["regulation", "research", "regulatory-compliance", "advanced"]}
{"id": "term:volcker-rule", "title": "Volcker Rule", "text": "# Volcker Rule\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Dodd-Frank Section 619 limiting bank proprietary trading and hedge fund / PE fund sponsorship.\n\n**Definition:** Banks may not engage in short-term prop trading or own > 3% of any HF/PE fund. Exemptions: market-making, hedging, underwriting. The 2020 amendments significantly relaxed several restrictions. Effect: large bank prop desks closed (Goldman PIA, Morgan Stanley PDT spun out, Citi/JPM/MS prop closed) — talent flowed into independent hedge funds and prop firms.", "source": "https://hedgefund.wiki/api/glossary/term/volcker-rule.json", "entity": {"type": "term", "id": "volcker-rule"}, "tokens_approx": 140, "tags": ["regulation", "banking", "regulatory-compliance", "intermediate"]}
{"id": "term:insider-trading", "title": "Insider Trading", "text": "# Insider Trading\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Trading securities while in possession of material non-public information in breach of a fiduciary duty.\n\n**Definition:** US: Rule 10b-5 + extensive case law. Tipper-tippee analysis (Newman, Salman, Blaszczak) requires personal benefit to tipper. Major hedge fund cases: Galleon (2009-2011), SAC (2009-2014), Insys (2017). Penalties: criminal (up to 20 years), civil (treble damages), barring orders.", "source": "https://hedgefund.wiki/api/glossary/term/insider-trading.json", "entity": {"type": "term", "id": "insider-trading"}, "tokens_approx": 123, "tags": ["compliance", "crime", "regulatory-compliance", "intermediate"]}
{"id": "term:restricted-list", "title": "Restricted List", "text": "# Restricted List\n\n**Category:** regulatory-compliance · **Level:** intermediate\n\n**Summary:** Internal list of securities for which a fund's compliance prohibits trading due to MNPI risk or conflicts.\n\n**Definition:** Watch list: monitored, may trade with elevated scrutiny. Restricted list: trading prohibited. Triggers: deal/investment-banking activity, M&A discussions, expert network calls in restricted sectors, board representation.", "source": "https://hedgefund.wiki/api/glossary/term/restricted-list.json", "entity": {"type": "term", "id": "restricted-list"}, "tokens_approx": 109, "tags": ["compliance", "controls", "regulatory-compliance", "intermediate"]}
{"id": "term:blocker-corporation", "title": "Blocker Corporation", "text": "# Blocker Corporation\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** An offshore (typically Cayman) corporation interposed between a US tax-exempt LP and a US trade or business to block UBTI.\n\n**Definition:** ECI/UBTI shielding: the blocker pays US corporate tax on its share of fund income (~21% federal); the tax-exempt LP receives clean dividends. Used in master-feeder structures and PE side-cars holding US partnership interests. The 2017 TCJA's 21% corporate rate made blockers more economic than under the prior 35% rate.", "source": "https://hedgefund.wiki/api/glossary/term/blocker-corporation.json", "entity": {"type": "term", "id": "blocker-corporation"}, "tokens_approx": 138, "tags": ["tax", "structure", "regulatory-compliance", "advanced"]}
{"id": "term:ecil", "title": "Effectively Connected Income", "text": "# Effectively Connected Income\n_(ECI)_\n\n**Category:** regulatory-compliance · **Level:** advanced\n\n**Summary:** Income earned by foreign persons from a US trade or business, taxed on a net basis at graduated US rates.\n\n**Definition:** Foreign LPs investing in US partnerships generally must file US returns and pay US tax on ECI. Hedge fund 'trader' status (vs 'dealer') exempts most non-US investor income from ECI under Section 864(b). PE structures that involve operating businesses or real estate generate ECI — handled via blocker corporations.", "source": "https://hedgefund.wiki/api/glossary/term/ecil.json", "entity": {"type": "term", "id": "ecil"}, "tokens_approx": 137, "tags": ["tax", "international", "regulatory-compliance", "advanced"]}
{"id": "term:newcits", "title": "Newcits", "text": "# Newcits\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** Hedge-fund-style strategies packaged as UCITS funds — daily liquidity, regulated leverage, retail-marketable.\n\n**Definition:** Common newcits: equity L/S, market neutral, macro, managed futures (limited futures sleeves). Constraints: 200% gross VaR or 100% commitment leverage, daily liquidity, no direct commodity exposure. AUM in alt-UCITS reached €700bn by 2025.", "source": "https://hedgefund.wiki/api/glossary/term/newcits.json", "entity": {"type": "term", "id": "newcits"}, "tokens_approx": 111, "tags": ["structure", "retail", "fund-operations", "intermediate"]}
{"id": "term:soft-close", "title": "Soft Close", "text": "# Soft Close\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A fund stops accepting new investors but allows existing investors to add capital.\n\n**Definition:** First step in capacity management. Typically followed by a hard close (no new capital from anyone) when the strategy approaches optimal AUM. The opposite of distress: signals a fund is at or near capacity.", "source": "https://hedgefund.wiki/api/glossary/term/soft-close.json", "entity": {"type": "term", "id": "soft-close"}, "tokens_approx": 97, "tags": ["capacity", "fund-operations", "intermediate"]}
{"id": "term:deleveraging", "title": "Deleveraging", "text": "# Deleveraging\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** Reduction of leverage or risk exposure, often forced by margin calls or risk-limit breaches.\n\n**Definition:** Procyclical: a drawdown triggers risk reduction, which contributes to further selling, which deepens the drawdown. The dynamic behind LTCM 1998, Aug 2007 quant quake, March 2020 dash for cash, and August 2024 yen carry unwind.", "source": "https://hedgefund.wiki/api/glossary/term/deleveraging.json", "entity": {"type": "term", "id": "deleveraging"}, "tokens_approx": 105, "tags": ["risk", "procyclical", "risk-management", "intermediate"]}
{"id": "term:margin-call", "title": "Margin Call", "text": "# Margin Call\n\n**Category:** risk-management · **Level:** intro\n\n**Summary:** A demand from a broker for additional collateral to cover losses on a leveraged position.\n\n**Definition:** Triggered when account equity falls below maintenance margin. Failure to post triggers liquidation at the broker's discretion. The Archegos 2021 case: Hwang refused several margin calls, forcing dealers to unwind ~$160bn notional in days.", "source": "https://hedgefund.wiki/api/glossary/term/margin-call.json", "entity": {"type": "term", "id": "margin-call"}, "tokens_approx": 105, "tags": ["risk", "leverage", "risk-management", "intro"]}
{"id": "term:asset-liability-mismatch", "title": "Asset-Liability Mismatch", "text": "# Asset-Liability Mismatch\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** Difference between the liquidity profile of fund assets and fund redemption terms.\n\n**Definition:** When fund offers monthly liquidity but holds quarterly-or-worse-liquid assets, redemption pressure forces fire sales. Causes of major fund failures (Woodford 2019, H2O 2020, multiple emerging market funds 2018). Liquidity ladders match expected redemption windows to asset liquidation timeframes.", "source": "https://hedgefund.wiki/api/glossary/term/asset-liability-mismatch.json", "entity": {"type": "term", "id": "asset-liability-mismatch"}, "tokens_approx": 123, "tags": ["risk", "liquidity", "risk-management", "intermediate"]}
{"id": "term:close-out-netting", "title": "Close-Out Netting", "text": "# Close-Out Netting\n\n**Category:** fund-operations · **Level:** advanced\n\n**Summary:** ISDA Master mechanism that nets all outstanding obligations between two counterparties on default.\n\n**Definition:** On an event of default, all outstanding trades between counterparties are valued and reduced to a single net amount payable one way. Without close-out netting, gross exposures would dwarf net — multiplying systemic risk. Enforceability of netting was central to Title VII Dodd-Frank reforms.", "source": "https://hedgefund.wiki/api/glossary/term/close-out-netting.json", "entity": {"type": "term", "id": "close-out-netting"}, "tokens_approx": 123, "tags": ["legal", "derivatives", "fund-operations", "advanced"]}
{"id": "term:mar-ratio", "title": "MAR Ratio", "text": "# MAR Ratio\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Original Calmar variant: compound annual return divided by maximum drawdown over the strategy's full history.\n\n**Definition:** Predates Calmar; used by Managed Account Reports (MAR) industry magazine in the 1980s. Calmar typically uses a 36-month rolling window; MAR uses inception-to-date. Both compute return / drawdown.", "source": "https://hedgefund.wiki/api/glossary/term/mar-ratio.json", "entity": {"type": "term", "id": "mar-ratio"}, "tokens_approx": 102, "tags": ["performance", "drawdown", "quantitative-methods", "intermediate"]}
{"id": "term:martin-ratio", "title": "Martin Ratio", "text": "# Martin Ratio\n\n**Category:** quantitative-methods · **Level:** advanced\n\n**Summary:** Excess return divided by the Ulcer Index — Sharpe with drawdown depth-and-duration in the denominator.\n\n**Definition:** Martin = (R_p − R_f) / Ulcer Index. Penalizes both depth and duration of drawdowns, unlike Calmar which only sees the maximum point.", "source": "https://hedgefund.wiki/api/glossary/term/martin-ratio.json", "entity": {"type": "term", "id": "martin-ratio"}, "tokens_approx": 84, "tags": ["performance", "drawdown", "quantitative-methods", "advanced"]}
{"id": "term:time-to-recovery", "title": "Time to Recovery", "text": "# Time to Recovery\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** Number of periods between a drawdown trough and the next NAV high.\n\n**Definition:** A 15% drawdown that recovers in 3 months is qualitatively different from one that takes 36 months — both have the same MDD. Time-to-recovery is a key allocator metric, often presented as the 'underwater chart'.", "source": "https://hedgefund.wiki/api/glossary/term/time-to-recovery.json", "entity": {"type": "term", "id": "time-to-recovery"}, "tokens_approx": 96, "tags": ["risk", "drawdown", "risk-management", "intermediate"]}
{"id": "term:coherent-risk-measure", "title": "Coherent Risk Measure", "text": "# Coherent Risk Measure\n\n**Category:** risk-management · **Level:** advanced\n\n**Summary:** Artzner-Delbaen-Eber-Heath axiomatic class: monotonicity, sub-additivity, positive homogeneity, translation invariance.\n\n**Definition:** VaR fails subadditivity (it can violate diversification logic). Expected Shortfall is coherent — a key reason FRTB replaced VaR with ES.", "source": "https://hedgefund.wiki/api/glossary/term/coherent-risk-measure.json", "entity": {"type": "term", "id": "coherent-risk-measure"}, "tokens_approx": 91, "tags": ["risk", "theory", "risk-management", "advanced"]}
{"id": "term:scenario-analysis", "title": "Scenario Analysis", "text": "# Scenario Analysis\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** Estimating portfolio P&L under specified joint-shock scenarios — historical replays or hypothetical constructs.\n\n**Definition:** Differs from VaR in being deterministic rather than probabilistic. Standard practice: a 5-10 scenario standing book that includes 1987, 1998, 2008, March 2020, plus current-stress hypotheticals (e.g., 'rates +200bp / equities −20% / vol +25').", "source": "https://hedgefund.wiki/api/glossary/term/scenario-analysis.json", "entity": {"type": "term", "id": "scenario-analysis"}, "tokens_approx": 115, "tags": ["risk", "risk-management", "intermediate"]}
{"id": "term:suspension", "title": "Suspension", "text": "# Suspension\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** A fund's right to halt redemptions entirely under conditions specified in the LPA.\n\n**Definition:** More severe than a gate — a complete halt rather than a cap. Triggers usually: market closure, inability to value > 10-25% of assets, regulatory event. Suspensions of major funds (BNP Paribas Aug 2007, Bear Stearns funds 2007, Carmignac/H2O 2020) often signal terminal distress.", "source": "https://hedgefund.wiki/api/glossary/term/suspension.json", "entity": {"type": "term", "id": "suspension"}, "tokens_approx": 115, "tags": ["liquidity", "operations", "fund-operations", "intermediate"]}
{"id": "term:ima", "title": "Investment Management Agreement", "text": "# Investment Management Agreement\n_(IMA)_\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** Bilateral contract under which a manager is granted limited discretionary trading authority over a separately-managed account.\n\n**Definition:** Specifies investment guidelines, risk limits, fees, fee crystallization, termination terms, reporting cadence. Foundation of SMA relationships. Negotiated heavily at inception, less frequently amended thereafter.", "source": "https://hedgefund.wiki/api/glossary/term/ima.json", "entity": {"type": "term", "id": "ima"}, "tokens_approx": 117, "tags": ["legal", "sma", "fund-operations", "intermediate"]}
{"id": "term:anchor-investor", "title": "Anchor Investor", "text": "# Anchor Investor\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** An LP whose commitment provides credibility for a fund's launch, often in exchange for fee discounts, capacity rights, or GP equity.\n\n**Definition:** Distinct from seeders (who take equity in the GP) — anchors typically just take fee discounts and capacity. Common anchors: family offices, sovereign wealth funds, university endowments. A signal of fund quality to other LPs.", "source": "https://hedgefund.wiki/api/glossary/term/anchor-investor.json", "entity": {"type": "term", "id": "anchor-investor"}, "tokens_approx": 116, "tags": ["allocation", "launch", "fund-operations", "intermediate"]}
{"id": "term:transparency", "title": "Transparency", "text": "# Transparency\n\n**Category:** fund-operations · **Level:** intermediate\n\n**Summary:** The level of position-level, exposure, and risk reporting a fund provides to its investors.\n\n**Definition:** Standard transparency: monthly NAV, periodic risk report, attribution. Enhanced transparency: weekly or daily exposure, position-level reporting (often via aggregator like NAV-related FactSet or RiskMetrics). SMAs offer full transparency by definition. Trade-off: position-level disclosure can leak strategy edge.", "source": "https://hedgefund.wiki/api/glossary/term/transparency.json", "entity": {"type": "term", "id": "transparency"}, "tokens_approx": 127, "tags": ["operations", "reporting", "fund-operations", "intermediate"]}
{"id": "term:mbs", "title": "Mortgage-Backed Security", "text": "# Mortgage-Backed Security\n_(MBS)_\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** A bond backed by a pool of residential or commercial mortgages.\n\n**Definition:** Agency MBS (Fannie/Freddie/Ginnie) — credit guaranteed, prepayment risk only. Non-agency MBS — credit and prepayment risk. CMOs slice cash flows into tranches by duration/credit. Negative convexity from prepayment option drives convexity-hedging flow that amplifies rate moves.", "source": "https://hedgefund.wiki/api/glossary/term/mbs.json", "entity": {"type": "term", "id": "mbs"}, "tokens_approx": 117, "tags": ["fixed-income", "mbs", "fixed-income-credit", "intermediate"]}
{"id": "term:default-probability", "title": "Default Probability", "text": "# Default Probability\n_(PD)_\n\n**Category:** fixed-income-credit · **Level:** intermediate\n\n**Summary:** Estimated probability that a borrower will default within a specified horizon.\n\n**Definition:** Risk-neutral PD implied from CDS spreads: PD ≈ s/(1−R). Real-world PD from rating-agency transition matrices, Merton-distance-to-default models, machine learning. Material differences between risk-neutral and real-world PDs reflect risk and liquidity premia.", "source": "https://hedgefund.wiki/api/glossary/term/default-probability.json", "entity": {"type": "term", "id": "default-probability"}, "tokens_approx": 114, "tags": ["credit", "probability", "fixed-income-credit", "intermediate"]}
{"id": "term:factor-tilt", "title": "Factor Tilt", "text": "# Factor Tilt\n\n**Category:** portfolio-construction · **Level:** intermediate\n\n**Summary:** Deliberate over- or under-weighting of factor exposures (size, value, momentum, quality, low-vol) relative to a benchmark.\n\n**Definition:** Smart-beta and quant funds construct portfolios as a deliberate combination of factor tilts. Active managers may unintentionally tilt — performance attribution decomposes returns into market beta + factor tilts + residual alpha.", "source": "https://hedgefund.wiki/api/glossary/term/factor-tilt.json", "entity": {"type": "term", "id": "factor-tilt"}, "tokens_approx": 115, "tags": ["factor", "portfolio", "portfolio-construction", "intermediate"]}
{"id": "term:systemic-risk", "title": "Systemic Risk", "text": "# Systemic Risk\n\n**Category:** risk-management · **Level:** intermediate\n\n**Summary:** The risk that the failure of one institution or strategy triggers cascading failures across the financial system.\n\n**Definition:** Post-2008 framework: SIFIs (systemically important financial institutions), G-SIBs, FSOC designation, Basel surcharges, living wills. Hedge fund systemic risk monitored via Form PF, Office of Financial Research analytics, BIS triennial surveys.", "source": "https://hedgefund.wiki/api/glossary/term/systemic-risk.json", "entity": {"type": "term", "id": "systemic-risk"}, "tokens_approx": 115, "tags": ["risk", "systemic", "risk-management", "intermediate"]}
{"id": "term:risk-off", "title": "Risk-Off", "text": "# Risk-Off\n\n**Category:** macroeconomics · **Level:** intro\n\n**Summary:** Market regime in which investors collectively de-risk, selling risk assets and buying perceived safe havens.\n\n**Definition:** Classic risk-off rotation: equities down, USD/JPY/CHF up, gold up, Treasuries up (most regimes). The 'risk-on / risk-off' duality dominated post-2008 markets but broke down in 2022 when Treasuries sold off alongside equities.", "source": "https://hedgefund.wiki/api/glossary/term/risk-off.json", "entity": {"type": "term", "id": "risk-off"}, "tokens_approx": 106, "tags": ["macro", "regime", "macroeconomics", "intro"]}
{"id": "term:garch", "title": "GARCH", "text": "# GARCH\n\n**Category:** quantitative-methods · **Level:** intermediate\n\n**Summary:** Generalized AutoRegressive Conditional Heteroskedasticity — econometric class modeling time-varying volatility.\n\n**Definition:** Engle (1982 ARCH), Bollerslev (1986 GARCH). Models volatility as a function of past shocks and past variance. Standard tool in vol forecasting; foundation for vol-targeting allocation, dynamic risk budgets, and conditional VaR.", "source": "https://hedgefund.wiki/api/glossary/term/garch.json", "entity": {"type": "term", "id": "garch"}, "tokens_approx": 110, "tags": ["statistics", "vol", "quantitative-methods", "intermediate"]}
{"id": "term:mirr", "title": "Modified IRR", "text": "# Modified IRR\n_(MIRR)_\n\n**Category:** alternative-investments · **Level:** advanced\n\n**Summary:** IRR variant that assumes interim cash flows are reinvested at a specified reinvestment rate (typically the cost of capital).\n\n**Definition:** Corrects IRR's unrealistic reinvestment-at-IRR assumption. MIRR = ((FV of positive CFs at reinvestment rate) / |PV of negative CFs at finance rate|)^(1/n) − 1. Often produces more conservative return estimates than IRR.", "source": "https://hedgefund.wiki/api/glossary/term/mirr.json", "entity": {"type": "term", "id": "mirr"}, "tokens_approx": 115, "tags": ["performance", "private", "alternative-investments", "advanced"]}
{"id": "term:reinsurer-collateralized", "title": "Collateralized Reinsurance", "text": "# Collateralized Reinsurance\n\n**Category:** insurance-reinsurance · **Level:** advanced\n\n**Summary:** Reinsurance contracts fully collateralized by capital posted by hedge fund / ILS investors.\n\n**Definition:** Differs from rated reinsurance by funded-to-the-limit collateral. Reduces counterparty risk for cedents (no rating downgrade risk). Major vehicles: sidecars, segregated-account companies (Bermuda), collateralized reinsurance funds.", "source": "https://hedgefund.wiki/api/glossary/term/reinsurer-collateralized.json", "entity": {"type": "term", "id": "reinsurer-collateralized"}, "tokens_approx": 110, "tags": ["insurance", "insurance-reinsurance", "advanced"]}
{"id": "term:crisis-alpha", "title": "Crisis Alpha", "text": "# Crisis Alpha\n\n**Category:** hedge-fund-strategies · **Level:** intermediate\n\n**Summary:** Returns generated specifically during market crises, when most other strategies are losing.\n\n**Definition:** Greyserman-Kaminski (2014). Trend-following strategies historically deliver crisis alpha — sustained directional moves in crises (2008, 2022) play to trend's strength. True crisis alpha must be uncorrelated with risk assets in stress, not just on average.", "source": "https://hedgefund.wiki/api/glossary/term/crisis-alpha.json", "entity": {"type": "term", "id": "crisis-alpha"}, "tokens_approx": 114, "tags": ["alpha", "tail", "hedge-fund-strategies", "intermediate"]}
{"id": "strategy:long-short-equity", "title": "Long/Short Equity", "text": "# Long/Short Equity (Strategy)\n**Family:** equity-hedge\n\n**Summary:** Hold long positions in expected outperformers, short positions in expected underperformers. Net exposure tunes market beta.\n\n**Mechanism:** Pick stocks (or baskets) on fundamental, quantitative, or hybrid signals. Hedge market exposure by shorting individual names, sector ETFs, or index futures. P&L = idiosyncratic spread of longs over shorts + (residual net exposure × market move).\n\n**Return drivers:** stock selection, sector tilt, factor exposure, net exposure timing\n\n**Instruments:** common stock, single-stock options, sector ETFs, index futures\n\n**Holding period:** weeks to quarters\n\n**Leverage typical:** gross 1.5–4.0× net -0.2–0.7\n\n**Sharpe typical:** 0.5–1.5\n\n**Best environment:** Wide single-stock dispersion, low correlation across names, fundamental research valued by the market.\n\n**Worst environment:** Compressed dispersion, factor crowding, sustained low-vol bull markets where shorts compress alpha.\n\n**Practitioners:** A.W. Jones (originator, 1949), Julian Robertson (Tiger), Stephen Mandel (Lone Pine), John Griffin (Blue Ridge), Lee Ainslie (Maverick)\n\n**History:** Originated by Alfred Winslow Jones in 1949 with the first 'hedged fund' — long undervalued stocks, short overvalued, leverage to amplify. Tiger Management and the 'Tiger Cubs' formalized fundamental L/S in the 1980s-2000s. The 2010s saw factor-decomposition exposing how much of L/S returns were value/quality factor beta. The 2020s saw consolidation: many traditional L/S funds shrank or shut as multi-strat pods absorbed talent.", "source": "https://hedgefund.wiki/api/strategies.json#long-short-equity", "entity": {"type": "strategy", "id": "long-short-equity"}, "tokens_approx": 398, "tags": ["equity", "fundamental", "directional", "equity-hedge"]}
{"id": "strategy:equity-market-neutral", "title": "Equity Market Neutral", "text": "# Equity Market Neutral (Strategy)\n**Family:** equity-hedge\n\n**Summary:** Long/short equity book engineered to zero-out market beta (and often factor exposures), capturing pure idiosyncratic spread.\n\n**Mechanism:** Construct longs and shorts so weighted beta is ~0; in factor-neutral variants, also zero out size, value, momentum, sector. Returns come from cross-sectional stock selection.\n\n**Return drivers:** stock selection (idiosyncratic alpha), fast factor exposures within constraints\n\n**Instruments:** common stock, futures (for hedging residual beta)\n\n**Holding period:** days to weeks\n\n**Leverage typical:** gross 4–12× net -0.05–0.05\n\n**Sharpe typical:** 1.0–2.5\n\n**Best environment:** High dispersion, stable factor regimes.\n\n**Worst environment:** Factor regime shifts (Q1 2009 momentum crash, March 2020 quant carnage).\n\n**Practitioners:** AQR, Two Sigma Compass, PDT Partners (Morgan Stanley/Mike Reed), DE Shaw\n\n**History:** Outgrowth of Bamberger/Tartaglia's stat arb at Morgan Stanley APT in the 1980s. Modern multi-manager pods are the institutional successor.", "source": "https://hedgefund.wiki/api/strategies.json#equity-market-neutral", "entity": {"type": "strategy", "id": "equity-market-neutral"}, "tokens_approx": 269, "tags": ["equity", "neutral", "systematic", "equity-hedge"]}
{"id": "strategy:merger-arbitrage", "title": "Merger Arbitrage", "text": "# Merger Arbitrage (Strategy)\n**Family:** event-driven\n\n**Summary:** Capture the spread between announced acquisition price and target market price; manage the risk that the deal breaks.\n\n**Mechanism:** Cash deal: long target after announcement. Stock deal: long target, short acquirer in the announced exchange ratio. Hedge regulatory and execution-risk subsets via options where economical.\n\n**Return drivers:** base rate of deal closure (>95% historically), spread compression (annualized 4-8% in normal markets), occasional retrades and bumps\n\n**Instruments:** common stock, single-stock options, credit (for LBO targets)\n\n**Holding period:** weeks to months (until deal close or break)\n\n**Leverage typical:** gross 1.5–4× net –\n\n**Sharpe typical:** 0.7–1.5\n\n**Best environment:** High M&A volume, predictable regulators, accommodating financing markets.\n\n**Worst environment:** Hostile antitrust environment (FTC Khan, EU Vestager), tightening credit conditions, surprise rate moves widening all spreads.\n\n**Practitioners:** Paulson & Co (pre-2010), York Capital (event), Kellner Capital, Pentwater, Magnetar\n\n**History:** Practiced informally since the 1940s; institutionalized by Goldman's risk arb desk under Robert Rubin in the 1970s-80s. The 2024-26 era is the most regulator-hostile environment in decades.", "source": "https://hedgefund.wiki/api/strategies.json#merger-arbitrage", "entity": {"type": "strategy", "id": "merger-arbitrage"}, "tokens_approx": 329, "tags": ["event-driven", "arbitrage", "merger-arb", "event-driven"]}
{"id": "strategy:convertible-arbitrage", "title": "Convertible Arbitrage", "text": "# Convertible Arbitrage (Strategy)\n**Family:** relative-value\n\n**Summary:** Long the convertible bond, short the underlying stock in delta-equivalent quantity; harvest gamma, vega, and credit-spread carry.\n\n**Mechanism:** Decompose convert into bond floor + embedded call. Delta-hedge the call by shorting stock; rehedge as delta moves. Capture convex P&L (long gamma), realized vol < implied (long vega vs IV), and bond carry minus stock borrow.\n\n**Return drivers:** gamma scalping, vega (realized > implied), credit spread tightening, bond carry\n\n**Instruments:** convertible bonds, common stock (short hedge), CDS (credit hedge)\n\n**Holding period:** months to a year\n\n**Leverage typical:** gross 3–8× net –\n\n**Sharpe typical:** 0.5–1.5\n\n**Best environment:** Active convert issuance, rising realized vol, tightening credit.\n\n**Worst environment:** 2008-style credit crisis where forced deleveraging crushed all converts simultaneously.\n\n**Practitioners:** Citadel Wellington (early), Highbridge, AQR Convertible, Calamos, Polygon\n\n**History:** Largest hedge fund strategy by AUM in early 2000s. Nearly destroyed in 2008 (HFRI Conv Arb -34% in 2008, +60% in 2009 as forced sellers gave way to fundamental buyers). Steady but smaller strategy since.", "source": "https://hedgefund.wiki/api/strategies.json#convertible-arbitrage", "entity": {"type": "strategy", "id": "convertible-arbitrage"}, "tokens_approx": 312, "tags": ["relative-value", "convertibles", "vol", "relative-value"]}
{"id": "strategy:global-macro", "title": "Global Macro", "text": "# Global Macro (Strategy)\n**Family:** global-macro\n\n**Summary:** Top-down directional and relative-value bets across rates, FX, equity indices, and commodities driven by macroeconomic theses.\n\n**Mechanism:** Form macro views (rate cycles, growth, inflation, central bank policy, geopolitics). Express via futures, swaps, options for capital efficiency. Common trades: rate steepeners/flatteners, FX carry, breakeven inflation, equity-vs-rates RV.\n\n**Return drivers:** regime change, policy surprises, term-structure mispricing, EM sovereign mispricing\n\n**Instruments:** rate futures, swaps, FX forwards/options, equity index futures, commodity futures\n\n**Holding period:** weeks to quarters\n\n**Leverage typical:** gross 3–15× net –\n\n**Sharpe typical:** 0.4–1.5\n\n**Best environment:** Regime change (1992 ERM, 2008 GFC, 2022 inflation surge).\n\n**Worst environment:** Compressed-vol bull markets with no macro turning points (2014-2019 was brutal for discretionary macro).\n\n**Practitioners:** George Soros, Stanley Druckenmiller, Louis Bacon (Moore), Paul Tudor Jones, Alan Howard (Brevan Howard), Said Haidar\n\n**History:** The 'big bet' era (Soros breaks the BoE, 1992) defined the 1990s. Shrunk through the 2010s zero-rate compression. Powerful resurgence in 2022-2024 as inflation broke the regime open.", "source": "https://hedgefund.wiki/api/strategies.json#global-macro", "entity": {"type": "strategy", "id": "global-macro"}, "tokens_approx": 326, "tags": ["macro", "directional", "discretionary", "global-macro"]}
{"id": "strategy:managed-futures", "title": "Managed Futures (CTA)", "text": "# Managed Futures (CTA) (Strategy)\n**Family:** managed-futures\n\n**Summary:** Systematic trading of liquid futures contracts across global markets, dominated by trend-following.\n\n**Mechanism:** Signal generation: typically combinations of trend (multi-timescale moving averages, breakouts, momentum), carry, value, and volatility-scaled positioning. Trade ~100-300 futures markets across rates, FX, equities, and commodities. Risk-allocate via inverse-vol or equal-risk-contribution.\n\n**Return drivers:** sustained directional moves, crisis alpha (long puts via trend), diversification across uncorrelated markets\n\n**Instruments:** futures (rates, FX, equity, commodity), occasional FX forwards, no individual securities\n\n**Holding period:** weeks to months\n\n**Leverage typical:** gross 5–20× net –\n\n**Sharpe typical:** 0.4–1.0\n\n**Best environment:** Sustained directional moves across many markets (1980s rate decline, 2008 GFC, 2022 inflation).\n\n**Worst environment:** Choppy mean-reverting markets without sustained trends (2009-2013 was painful).\n\n**Practitioners:** Man AHL, Winton, BlueTrend (Leda Braga), Aspect Capital, Campbell & Co, Millburn, Graham Global, Lynx Asset Management\n\n**History:** Roots in 1970s commodity trading (Dunn, Henry, Donchian). Exploded in 1980s-90s via institutional adoption (Man Group, Winton). 2022 was the strategy's best year since 2008 (SG Trend Index +27%).", "source": "https://hedgefund.wiki/api/strategies.json#managed-futures", "entity": {"type": "strategy", "id": "managed-futures"}, "tokens_approx": 349, "tags": ["systematic", "trend", "futures", "managed-futures"]}
{"id": "strategy:statistical-arbitrage", "title": "Statistical Arbitrage", "text": "# Statistical Arbitrage (Strategy)\n**Family:** quantitative\n\n**Summary:** High-breadth, short-horizon mean-reversion or relative-value trading driven by statistical signals — typically thousands of small positions held for hours to days.\n\n**Mechanism:** Cross-sectional mean reversion within sector or factor neutralization. Modern signals: order-book imbalance, alt-data nowcasts, ML embeddings, news/text sentiment, microstructure features. Positions sized inverse-vol with portfolio-level beta and factor neutrality.\n\n**Return drivers:** mean reversion in residual returns, microstructure flow, alt-data signals\n\n**Instruments:** common stock, ADRs, ETFs (for hedging)\n\n**Holding period:** minutes to days\n\n**Leverage typical:** gross 4–12× net –\n\n**Sharpe typical:** 1.5–4.0\n\n**Best environment:** Stable microstructure, moderate vol, dispersion across names.\n\n**Worst environment:** August 2007 quant quake; March 2020 deleveraging cascade.\n\n**Practitioners:** DE Shaw, Renaissance Medallion (closed), Two Sigma, PDT Partners, Jane Street (adjacent), Hudson River Trading (adjacent)\n\n**History:** Pioneered at Morgan Stanley APT under Bamberger (early 1980s) and Tartaglia (later 1980s). Spawned a diaspora — DE Shaw, Renaissance, PDT, and the modern HFT firms all trace lineage. The August 2007 'quant quake' (week of Aug 6-10, 2007) saw cross-firm deleveraging produce -10 sigma single-day moves; survivors thrived after.", "source": "https://hedgefund.wiki/api/strategies.json#statistical-arbitrage", "entity": {"type": "strategy", "id": "statistical-arbitrage"}, "tokens_approx": 357, "tags": ["quant", "systematic", "mean-reversion", "quantitative"]}
{"id": "strategy:fixed-income-relative-value", "title": "Fixed Income Relative Value", "text": "# Fixed Income Relative Value (Strategy)\n**Family:** relative-value\n\n**Summary:** Long/short bond and rate-derivative trades exploiting small mispricings — basis trades, swap spreads, on-the-run/off-the-run, butterfly trades.\n\n**Mechanism:** Pair long cheap with short rich (e.g., long off-the-run / short on-the-run), finance via repo, hold to convergence. High leverage (20-100×) is required to make small basis points meaningful.\n\n**Return drivers:** mean reversion of mispricing, carry while waiting, occasional widening when shocks force unwinds\n\n**Instruments:** Treasuries (cash and futures), swaps, repo, options on rates\n\n**Holding period:** weeks to quarters\n\n**Leverage typical:** gross 15–80× net –\n\n**Sharpe typical:** 1.0–2.5\n\n**Best environment:** Stable rate vol, deep repo markets, no forced deleveraging.\n\n**Worst environment:** Liquidity crunches force forced unwinds (LTCM 1998, March 2020).\n\n**Practitioners:** LTCM (defunct), Citadel Fixed Income, Millennium Rates, ExodusPoint, PIMCO Tactical\n\n**History:** John Meriwether's Salomon prop desk → LTCM (1994-98) defined the genre and its risks. The Treasury basis trade has grown to ~$1tn in 2026, a regulatory focus.", "source": "https://hedgefund.wiki/api/strategies.json#fixed-income-relative-value", "entity": {"type": "strategy", "id": "fixed-income-relative-value"}, "tokens_approx": 297, "tags": ["relative-value", "rates", "basis", "relative-value"]}
{"id": "strategy:distressed-debt", "title": "Distressed Debt", "text": "# Distressed Debt (Strategy)\n**Family:** credit\n\n**Summary:** Investing in deeply discounted debt of companies in or near restructuring, often with the intent of converting to equity.\n\n**Mechanism:** Buy fulcrum debt at distressed prices (typically 30-70 cents). Either trade out on news or work through restructuring (committee membership, plan sponsorship, loan-to-own equity). Returns realized on emergence (12-36 months typical).\n\n**Return drivers:** recovery > price paid, fulcrum-to-equity conversion uplift, DIP financing fees, trading distressed names through volatility\n\n**Instruments:** bank debt, high-yield bonds, trade claims, bespoke financings\n\n**Holding period:** 1-3 years (event-driven)\n\n**Leverage typical:** gross 1.0–2.0× net –\n\n**Sharpe typical:** 0.5–1.2\n\n**Best environment:** Default cycle peak (2002, 2009, 2020, 2024-25 partial).\n\n**Worst environment:** Default-rate trough with cheap financing keeping zombie companies alive.\n\n**Practitioners:** Oaktree (Howard Marks), Apollo, Elliott, Davidson Kempner, King Street, Silver Point, Centerbridge\n\n**History:** Pioneered by Drexel alum (Marks at TCW) and bond traders (Tepper at Goldman/Appaloosa). The 2008-2010 cycle made several mega-fortunes; 2020 was a missed cycle (Fed action prevented the workout). 2024-25 commercial real estate distress is the next test.", "source": "https://hedgefund.wiki/api/strategies.json#distressed-debt", "entity": {"type": "strategy", "id": "distressed-debt"}, "tokens_approx": 335, "tags": ["credit", "distressed", "event-driven", "credit"]}
{"id": "strategy:credit-long-short", "title": "Credit Long/Short", "text": "# Credit Long/Short (Strategy)\n**Family:** credit\n\n**Summary:** Long credits with improving fundamentals or attractive carry, short credits at risk of widening; commonly hedged via CDS or index credit.\n\n**Mechanism:** Single-name high yield or IG bond/loan picks long, hedged with CDS, CDX/iTraxx index, or other credits. Capital structure arbitrage (long bond / short equity, or vice versa) is a sub-strategy.\n\n**Return drivers:** spread tightening on longs, spread widening on shorts, carry differential, convexity of credit\n\n**Instruments:** bonds, loans, CDS single-name, CDX/iTraxx index\n\n**Holding period:** months to a year\n\n**Leverage typical:** gross 2–5× net –\n\n**Sharpe typical:** 0.5–1.5\n\n**Best environment:** Mid-cycle dispersion, moderate vol, healthy primary issuance.\n\n**Worst environment:** Credit blow-ups in late cycle when correlations go to 1.\n\n**Practitioners:** Brigade Capital, BlueMountain (defunct), BlueBay, GoldenTree, King Street, Diameter", "source": "https://hedgefund.wiki/api/strategies.json#credit-long-short", "entity": {"type": "strategy", "id": "credit-long-short"}, "tokens_approx": 242, "tags": ["credit", "long-short", "credit"]}
{"id": "strategy:activist", "title": "Activist", "text": "# Activist (Strategy)\n**Family:** event-driven\n\n**Summary:** Take large positions in companies and publicly campaign for changes — capital allocation, board composition, M&A, breakup — to unlock value.\n\n**Mechanism:** Build 5-10% position. File 13D. Issue letters, white papers, board nominees, sometimes proxy contests. Catalysts: cost cuts, divestitures, buybacks, sale of company, new CEO. Holding periods 18-36 months typical.\n\n**Return drivers:** catalyst-driven multiple expansion, improved capital allocation, M&A premium, settlement-driven board changes\n\n**Instruments:** common stock, options (defensive), swaps for stealth accumulation pre-13D\n\n**Holding period:** 18 months to 3 years\n\n**Leverage typical:** gross 1–1.5× net –\n\n**Sharpe typical:** 0.4–1.2\n\n**Best environment:** Mid-cycle when targets are mispriced and management is willing to engage; bull markets that reward catalysts.\n\n**Worst environment:** Bear markets where catalysts are overwhelmed by beta.\n\n**Practitioners:** Carl Icahn (Icahn Enterprises), Bill Ackman (Pershing Square), Nelson Peltz (Trian), Paul Singer (Elliott), Daniel Loeb (Third Point), Jeff Smith (Starboard), ValueAct\n\n**History:** 1980s 'corporate raiders' (Icahn, Pickens, Lindner) → 1990s value activism (Steinhardt, Tisch) → 2000s on engagement-style (Ackman, Loeb, Peltz). The 2024 'universal proxy card' SEC rule lowered barriers for board contests.", "source": "https://hedgefund.wiki/api/strategies.json#activist", "entity": {"type": "strategy", "id": "activist"}, "tokens_approx": 350, "tags": ["event-driven", "activist", "engagement", "event-driven"]}
{"id": "strategy:multi-strategy", "title": "Multi-Strategy (Pod Shop)", "text": "# Multi-Strategy (Pod Shop) (Strategy)\n**Family:** multi-strategy\n\n**Summary:** A platform allocating capital to many independent portfolio managers (pods), each with strict risk limits and short stop-loss leashes.\n\n**Mechanism:** Centralized risk, technology, financing, compliance. Each pod runs a sub-book in a defined strategy (equity sector L/S, rates RV, commodity macro, credit, vol, etc). Risk allocator manages capital and stop-losses. Pass-through expense structure (typically 5-8% gross) funds infrastructure and PM comp.\n\n**Return drivers:** diversification across uncorrelated alpha streams, tight risk control limiting drawdowns, scale economies in technology and financing\n\n**Instruments:** all liquid asset classes — equity, rates, FX, commodity, credit\n\n**Holding period:** varies by pod (days to years)\n\n**Leverage typical:** gross 4–8× net –\n\n**Sharpe typical:** 1.5–3.5\n\n**Best environment:** Almost all environments — the model's diversification is its edge.\n\n**Worst environment:** March 2020-style cross-strategy deleveraging cascades; 'pod-quake' moments when too many pods crowd into the same factor.\n\n**Practitioners:** Citadel (Wellington), Millennium, Point72, ExodusPoint, Balyasny (BAM), Schonfeld, Walleye, Hudson Bay, Verition, Eisler\n\n**History:** Steve Cohen's SAC (1992-2013) was the prototype. Citadel and Millennium institutionalized the platform model. Post-2017 model dominance: 8 of the 10 largest hedge funds by AUM in 2026 are multi-strat platforms. Capacity is the binding constraint: most are closed to new capital.", "source": "https://hedgefund.wiki/api/strategies.json#multi-strategy", "entity": {"type": "strategy", "id": "multi-strategy"}, "tokens_approx": 389, "tags": ["multi-manager", "platform", "diversified", "multi-strategy"]}
{"id": "strategy:volatility-arbitrage", "title": "Volatility Arbitrage", "text": "# Volatility Arbitrage (Strategy)\n**Family:** relative-value\n\n**Summary:** Trade implied vs realized volatility, vol surface relative value, dispersion (index vol vs single-name vol), and tail-vol structures.\n\n**Mechanism:** Sub-strategies: (1) variance swap RV (long realized / short implied); (2) dispersion (short index vol / long basket of single-name vol); (3) skew/term-structure RV; (4) tail vol (long deep OTM puts as portfolio convexity).\n\n**Return drivers:** variance risk premium (RV < IV on average), dispersion premium, skew mispricing\n\n**Instruments:** options, variance swaps, VIX futures, OTC vol structures\n\n**Holding period:** days to months\n\n**Leverage typical:** gross 2–8× net –\n\n**Sharpe typical:** 0.6–2.0\n\n**Best environment:** Modestly volatile range markets — short-vol thrives.\n\n**Worst environment:** Vol spike (Volmageddon Feb 2018, COVID March 2020) destroys short-vol strategies.\n\n**Practitioners:** Capstone (Paul Britton), QVT, LMR Partners, Saba Capital (Boaz Weinstein), Universa (Mark Spitznagel — long-vol counter-example)", "source": "https://hedgefund.wiki/api/strategies.json#volatility-arbitrage", "entity": {"type": "strategy", "id": "volatility-arbitrage"}, "tokens_approx": 264, "tags": ["relative-value", "vol", "options", "relative-value"]}
{"id": "strategy:discretionary-equity-sector", "title": "Discretionary Equity Sector Specialist", "text": "# Discretionary Equity Sector Specialist (Strategy)\n**Family:** equity-hedge\n\n**Summary:** Deep-research single-sector L/S funds (TMT, healthcare, energy, consumer, financials) — concentrated portfolios reflecting expert insight.\n\n**Mechanism:** Sector PMs hold 20-60 names, often with a 70/30 long-short tilt. Edge comes from primary research, expert networks, channel checks, and deep industry contacts.\n\n**Return drivers:** stock selection within sector, sub-sector rotation, earnings-event timing\n\n**Instruments:** common stock, single-stock options\n\n**Holding period:** quarters to years\n\n**Leverage typical:** gross 1.5–3× net –\n\n**Sharpe typical:** 0.5–1.5\n\n**Practitioners:** Coatue (TMT), Whale Rock (TMT), RA Capital (biotech), Perceptive Advisors (biotech), Glenview (healthcare), Tybourne (TMT), Senator (consumer)", "source": "https://hedgefund.wiki/api/strategies.json#discretionary-equity-sector", "entity": {"type": "strategy", "id": "discretionary-equity-sector"}, "tokens_approx": 206, "tags": ["equity", "sector", "discretionary", "equity-hedge"]}
{"id": "strategy:crypto-quantitative", "title": "Crypto Quantitative", "text": "# Crypto Quantitative (Strategy)\n**Family:** digital-assets\n\n**Summary:** Systematic crypto strategies — basis (cash-and-carry), funding-rate harvesting, perpetual futures market making, MEV extraction, on-chain stat arb, spot-perp triangulation.\n\n**Mechanism:** Most common: long spot BTC/ETH, short perpetual to harvest funding (cash-and-carry). Other: cross-exchange arb, vol surface RV (Deribit), DEX-CEX arb, MEV (sandwich, arb, liquidations), validator/staking yield.\n\n**Return drivers:** funding rate carry, spot-perp basis, cross-venue spread, MEV extraction, staking yield\n\n**Instruments:** spot crypto (BTC, ETH, SOL, etc), perpetual futures, crypto options (Deribit), DeFi protocols\n\n**Holding period:** minutes to weeks\n\n**Leverage typical:** gross 1–5× net –\n\n**Sharpe typical:** 1.0–4.0\n\n**Best environment:** Bull markets with persistent positive funding (10-50% annualized basis trade).\n\n**Worst environment:** Funding rate inversions, exchange counterparty events (FTX Nov 2022).\n\n**Practitioners:** Pantera Capital, Galaxy Digital Trading, Wintermute, Jane Street (crypto adjacent), Cumberland (DRW), Genesis Trading (defunct)", "source": "https://hedgefund.wiki/api/strategies.json#crypto-quantitative", "entity": {"type": "strategy", "id": "crypto-quantitative"}, "tokens_approx": 286, "tags": ["crypto", "systematic", "basis", "digital-assets"]}
{"id": "strategy:insurance-linked", "title": "Insurance-Linked Strategies", "text": "# Insurance-Linked Strategies (Strategy)\n**Family:** credit\n\n**Summary:** Allocate to catastrophe bonds, ILS, and reinsurance sidecars to capture insurance risk premium uncorrelated with traditional markets.\n\n**Mechanism:** Cat bonds: investor receives spread, principal at risk if defined catastrophe occurs. Sidecars: minority equity in special-purpose reinsurer. Collateralized reinsurance: provide collateral for specific reinsurance contracts.\n\n**Return drivers:** catastrophe risk premium, diversification (truly uncorrelated), rising rate environment after major losses ('hard market')\n\n**Instruments:** cat bonds, ILW (industry loss warranties), reinsurance sidecars, collateralized reinsurance\n\n**Holding period:** 1-5 years (multi-year reinsurance contracts)\n\n**Leverage typical:** gross 1–1× net –\n\n**Sharpe typical:** 0.5–1.3\n\n**Best environment:** Post-event 'hard market' with rate hardening (2023-2024 was a generational entry point).\n\n**Worst environment:** Major loss years (2017 Atlantic hurricane season, 2022-23 secondary perils).\n\n**Practitioners:** Nephila, Credit Suisse ILS (now Stone Ridge), RenaissanceRe Medici, AlphaCat, Twelve Capital, Aeolus", "source": "https://hedgefund.wiki/api/strategies.json#insurance-linked", "entity": {"type": "strategy", "id": "insurance-linked"}, "tokens_approx": 292, "tags": ["insurance", "uncorrelated", "alternative", "credit"]}
{"id": "formula:sharpe-ratio", "title": "Sharpe Ratio", "text": "# Sharpe Ratio (Formula)\n\n**Summary:** Excess return per unit of total volatility.\n\n**LaTeX:** `S = \\frac{R_p - R_f}{\\sigma_p}`\n\n**Plain text:** `S = (R_p - R_f) / sigma_p`\n\n**Variables:**\n  - R_p: Portfolio return — Mean periodic return of the portfolio.\n  - R_f: Risk-free rate — Periodic risk-free rate (T-bill, OIS, SOFR).\n  - σ_p: Portfolio standard deviation — Standard deviation of excess periodic returns.\n\n**Intuition:** Reward per unit of risk. Higher = better risk-adjusted performance.\n\n**Assumptions:** Returns are i.i.d. and approximately normal; Volatility is a complete summary of risk\n\n**Edge cases:** Skewed return distributions distort Sharpe — use Sortino or Omega.; Illiquid books' reported σ is artificially low (autocorrelated returns) — Sharpe is overstated.; Annualize by multiplying by √(periods per year) only if returns are i.i.d.\n\n**Worked example:**\n  Given: {\"monthly_R_p\": 0.012, \"monthly_R_f\": 0.003, \"monthly_sigma_p\": 0.018}\n  Steps: Compute monthly excess return: 0.012 − 0.003 = 0.009 / Monthly Sharpe: 0.009 / 0.018 = 0.50 / Annualize: 0.50 × √12 = 1.73\n  Result: Annualized Sharpe ≈ 1.73", "source": "https://hedgefund.wiki/api/formulas.json#sharpe-ratio", "entity": {"type": "formula", "id": "sharpe-ratio"}, "tokens_approx": 281, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:sortino-ratio", "title": "Sortino Ratio", "text": "# Sortino Ratio (Formula)\n\n**Summary:** Excess return per unit of downside deviation.\n\n**LaTeX:** `S_o = \\frac{R_p - T}{\\sigma_d}, \\quad \\sigma_d = \\sqrt{\\frac{1}{N}\\sum_{t} \\min(R_t - T, 0)^2}`\n\n**Plain text:** `Sortino = (R_p - T) / sigma_d`\n\n**Variables:**\n  - R_p: Portfolio return — Mean return\n  - T: Target return — Minimum acceptable return (often 0 or R_f)\n  - σ_d: Downside deviation — RMS of returns below target\n\n**Intuition:** Penalize only the bad volatility — don't punish a strategy for upside.", "source": "https://hedgefund.wiki/api/formulas.json#sortino-ratio", "entity": {"type": "formula", "id": "sortino-ratio"}, "tokens_approx": 127, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:calmar-ratio", "title": "Calmar Ratio", "text": "# Calmar Ratio (Formula)\n\n**Summary:** Annualized return divided by absolute max drawdown.\n\n**LaTeX:** `C = \\frac{\\text{Annualized Return}}{|MDD|}`\n\n**Plain text:** `Calmar = Annualized Return / |MDD|`\n\n**Variables:**\n  - MDD: Maximum drawdown — Largest peak-to-trough decline over period\n\n**Intuition:** Return per unit of worst-case loss. Speaks to investors who fear drawdowns more than wiggles.", "source": "https://hedgefund.wiki/api/formulas.json#calmar-ratio", "entity": {"type": "formula", "id": "calmar-ratio"}, "tokens_approx": 99, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:information-ratio", "title": "Information Ratio", "text": "# Information Ratio (Formula)\n\n**Summary:** Active return over benchmark per unit of tracking error.\n\n**LaTeX:** `IR = \\frac{R_p - R_b}{\\sigma(R_p - R_b)}`\n\n**Plain text:** `IR = (R_p - R_b) / TE`\n\n**Variables:**\n  - R_p: Portfolio return — Periodic portfolio return\n  - R_b: Benchmark return — Periodic benchmark return\n  - σ(R_p − R_b): Tracking error — Standard deviation of active returns\n\n**Intuition:** Sharpe of relative performance. Grinold's law: IR ≈ IC × √breadth.", "source": "https://hedgefund.wiki/api/formulas.json#information-ratio", "entity": {"type": "formula", "id": "information-ratio"}, "tokens_approx": 118, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:jensens-alpha", "title": "Jensen's Alpha", "text": "# Jensen's Alpha (Formula)\n\n**Summary:** Excess return over the CAPM-predicted return given the portfolio's beta.\n\n**LaTeX:** `\\alpha = R_p - [R_f + \\beta(R_m - R_f)]`\n\n**Plain text:** `alpha = R_p - [R_f + beta * (R_m - R_f)]`\n\n**Variables:**\n  - R_p: Portfolio return — \n  - R_f: Risk-free rate — \n  - R_m: Market return — \n  - β: Portfolio beta — \n\n**Intuition:** What the portfolio earned above what its beta should have earned.", "source": "https://hedgefund.wiki/api/formulas.json#jensens-alpha", "entity": {"type": "formula", "id": "jensens-alpha"}, "tokens_approx": 108, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:beta-regression", "title": "Beta", "text": "# Beta (Formula)\n\n**Summary:** Slope of regression of asset returns on market returns.\n\n**LaTeX:** `\\beta = \\frac{\\mathrm{Cov}(R_i, R_m)}{\\mathrm{Var}(R_m)}`\n\n**Plain text:** `beta = Cov(R_i, R_m) / Var(R_m)`\n\n**Variables:**\n  - R_i: Asset return — \n  - R_m: Market return — \n\n**Intuition:** Sensitivity of the asset to the market. β=1 moves with the market; β=0 is independent.", "source": "https://hedgefund.wiki/api/formulas.json#beta-regression", "entity": {"type": "formula", "id": "beta-regression"}, "tokens_approx": 94, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:treynor-ratio", "title": "Treynor Ratio", "text": "# Treynor Ratio (Formula)\n\n**Summary:** Excess return per unit of systematic (beta) risk.\n\n**LaTeX:** `T = \\frac{R_p - R_f}{\\beta_p}`\n\n**Plain text:** `T = (R_p - R_f) / beta_p`\n\n**Variables:**\n  - R_p: Portfolio return — \n  - R_f: Risk-free rate — \n  - β_p: Portfolio beta — \n\n**Intuition:** Use when idiosyncratic risk is diversified away — only β matters.", "source": "https://hedgefund.wiki/api/formulas.json#treynor-ratio", "entity": {"type": "formula", "id": "treynor-ratio"}, "tokens_approx": 89, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:parametric-var", "title": "Parametric (Variance-Covariance) VaR", "text": "# Parametric (Variance-Covariance) VaR (Formula)\n\n**Summary:** Closed-form VaR assuming normal portfolio returns.\n\n**LaTeX:** `\\text{VaR}_{\\alpha} = -\\mu + z_{\\alpha} \\cdot \\sigma`\n\n**Plain text:** `VaR_alpha = -mu + z_alpha * sigma`\n\n**Variables:**\n  - μ: Mean return — Often assumed 0 for short horizons\n  - σ: Portfolio volatility — \n  - z_α: Standard-normal quantile — z_0.95 = 1.645, z_0.99 = 2.326\n\n**Intuition:** Convert volatility into a tail-loss number under the normal assumption.\n\n**Edge cases:** Massively underestimates VaR for fat-tailed strategies (credit, commodities, vol).; Ignores skewness and tail dependence.\n\n**Worked example:**\n  Given: {\"portfolio_USD\": 100000000, \"daily_sigma\": 0.012, \"confidence\": 0.99}\n  Steps: z_0.99 = 2.326 / VaR = $100m × 0.012 × 2.326 = $2,791,200\n  Result: 1-day 99% VaR ≈ $2.79m", "source": "https://hedgefund.wiki/api/formulas.json#parametric-var", "entity": {"type": "formula", "id": "parametric-var"}, "tokens_approx": 207, "tags": ["formula", "risk-management"]}
{"id": "formula:expected-shortfall", "title": "Expected Shortfall", "text": "# Expected Shortfall (Formula)\n\n**Summary:** Average loss in the worst (1−α) percent of cases.\n\n**LaTeX:** `\\mathrm{ES}_\\alpha = \\frac{1}{1-\\alpha} \\int_{\\alpha}^{1} \\text{VaR}_u \\, du`\n\n**Plain text:** `ES_alpha = (1/(1-alpha)) * integral_alpha^1 VaR_u du`\n\n**Variables:**\n  - α: Confidence level — e.g., 0.975 for Basel III FRTB\n\n**Intuition:** How bad is bad? VaR tells you the threshold; ES tells you the average beyond it.", "source": "https://hedgefund.wiki/api/formulas.json#expected-shortfall", "entity": {"type": "formula", "id": "expected-shortfall"}, "tokens_approx": 106, "tags": ["formula", "risk-management"]}
{"id": "formula:max-drawdown", "title": "Maximum Drawdown", "text": "# Maximum Drawdown (Formula)\n\n**Summary:** Largest peak-to-trough decline in NAV over a window.\n\n**LaTeX:** `MDD = \\max_{t \\in [0,T]}\\, \\max_{s \\le t}\\, \\frac{V_s - V_t}{V_s}`\n\n**Plain text:** `MDD = max over t of [max over s<=t of (V_s - V_t) / V_s]`\n\n**Variables:**\n  - V_t: NAV at time t — \n\n**Intuition:** Worst pain ever felt by an investor in this strategy.", "source": "https://hedgefund.wiki/api/formulas.json#max-drawdown", "entity": {"type": "formula", "id": "max-drawdown"}, "tokens_approx": 90, "tags": ["formula", "risk-management"]}
{"id": "formula:ulcer-index", "title": "Ulcer Index", "text": "# Ulcer Index (Formula)\n\n**Summary:** Quadratic mean of percentage drawdowns from running peaks.\n\n**LaTeX:** `UI = \\sqrt{\\frac{1}{N}\\sum_{t=1}^{N} D_t^2}, \\quad D_t = \\frac{V_t - \\max_{s \\le t} V_s}{\\max_{s \\le t} V_s} \\times 100`\n\n**Plain text:** `UI = sqrt(mean(D_t^2))`\n\n**Variables:**\n  - D_t: Drawdown from running high (%) — \n\n**Intuition:** Captures depth and duration of drawdowns, not just the worst point.", "source": "https://hedgefund.wiki/api/formulas.json#ulcer-index", "entity": {"type": "formula", "id": "ulcer-index"}, "tokens_approx": 103, "tags": ["formula", "risk-management"]}
{"id": "formula:kelly-criterion", "title": "Kelly Criterion (continuous form)", "text": "# Kelly Criterion (continuous form) (Formula)\n\n**Summary:** Bet size that maximizes long-run log wealth.\n\n**LaTeX:** `f^* = \\frac{\\mu - r}{\\sigma^2}`\n\n**Plain text:** `f* = (mu - r) / sigma^2`\n\n**Variables:**\n  - μ: Expected return — \n  - r: Risk-free rate — \n  - σ²: Variance of return — \n\n**Intuition:** Risk-adjusted growth-optimal bet size. Halve it for psychological survivability (half-Kelly).", "source": "https://hedgefund.wiki/api/formulas.json#kelly-criterion", "entity": {"type": "formula", "id": "kelly-criterion"}, "tokens_approx": 99, "tags": ["formula", "portfolio-construction"]}
{"id": "formula:black-scholes", "title": "Black-Scholes Call", "text": "# Black-Scholes Call (Formula)\n\n**Summary:** Closed-form European call price under geometric Brownian underlying.\n\n**LaTeX:** `C = S_0 \\Phi(d_1) - K e^{-rT} \\Phi(d_2), \\quad d_1 = \\frac{\\ln(S_0/K) + (r + \\sigma^2/2)T}{\\sigma\\sqrt{T}}, \\quad d_2 = d_1 - \\sigma\\sqrt{T}`\n\n**Plain text:** `C = S * N(d1) - K * exp(-rT) * N(d2)`\n\n**Variables:**\n  - S_0: Spot price — \n  - K: Strike — \n  - r: Risk-free rate — \n  - σ: Volatility — \n  - T: Time to expiry (years) — \n  - Φ: Standard normal CDF — \n\n**Intuition:** Replicating portfolio: Δ shares of stock financed by borrowing K·exp(-rT)·N(d2). The hedge ratio Δ = N(d1).\n\n**Assumptions:** Constant σ and r; No dividends (or continuous yield q); Continuous trading; Log-normal returns; No frictions\n\n**Edge cases:** Vol smile shows the constant-σ assumption is wrong — practitioners invert BS to quote in implied-vol terms.; American options require numerical methods (binomial, PSOR, LSM).", "source": "https://hedgefund.wiki/api/formulas.json#black-scholes", "entity": {"type": "formula", "id": "black-scholes"}, "tokens_approx": 233, "tags": ["formula", "derivatives-options"]}
{"id": "formula:delta-bs-call", "title": "Black-Scholes Delta (Call)", "text": "# Black-Scholes Delta (Call) (Formula)\n\n**Summary:** First derivative of call price with respect to spot.\n\n**LaTeX:** `\\Delta_{call} = \\Phi(d_1)`\n\n**Plain text:** `Delta_call = N(d1)`\n\n**Variables:**\n  - d_1: Black-Scholes d1 term — \n\n**Intuition:** Hedge ratio: shares of stock per option to maintain delta neutrality.", "source": "https://hedgefund.wiki/api/formulas.json#delta-bs-call", "entity": {"type": "formula", "id": "delta-bs-call"}, "tokens_approx": 79, "tags": ["formula", "derivatives-options"]}
{"id": "formula:gamma-bs", "title": "Black-Scholes Gamma", "text": "# Black-Scholes Gamma (Formula)\n\n**Summary:** Second derivative of option price with respect to spot.\n\n**LaTeX:** `\\Gamma = \\frac{\\phi(d_1)}{S\\sigma\\sqrt{T}}`\n\n**Plain text:** `Gamma = phi(d1) / (S * sigma * sqrt(T))`\n\n**Variables:**\n  - φ(d_1): Standard normal PDF at d1 — \n  - S: Spot — \n\n**Intuition:** Convexity of option payoff. Maximum at the strike.", "source": "https://hedgefund.wiki/api/formulas.json#gamma-bs", "entity": {"type": "formula", "id": "gamma-bs"}, "tokens_approx": 89, "tags": ["formula", "derivatives-options"]}
{"id": "formula:vega-bs", "title": "Black-Scholes Vega", "text": "# Black-Scholes Vega (Formula)\n\n**Summary:** Derivative of option price with respect to volatility.\n\n**LaTeX:** `\\nu = S\\sqrt{T} \\, \\phi(d_1)`\n\n**Plain text:** `Vega = S * sqrt(T) * phi(d1)`\n\n**Intuition:** Dollar P&L per 1 vol point change. Maximum for ATM, longer-dated options.", "source": "https://hedgefund.wiki/api/formulas.json#vega-bs", "entity": {"type": "formula", "id": "vega-bs"}, "tokens_approx": 70, "tags": ["formula", "derivatives-options"]}
{"id": "formula:duration-modified", "title": "Modified Duration", "text": "# Modified Duration (Formula)\n\n**Summary:** Approximates % price change of a bond per 1% rate change.\n\n**LaTeX:** `D_{mod} = \\frac{D_{Mac}}{1 + y/n}, \\quad \\frac{\\Delta P}{P} \\approx -D_{mod} \\Delta y`\n\n**Plain text:** `D_mod = D_Mac / (1 + y/n);  dP/P ~ -D_mod * dy`\n\n**Variables:**\n  - D_Mac: Macaulay duration — \n  - y: Yield to maturity — \n  - n: Compounding periods per year —", "source": "https://hedgefund.wiki/api/formulas.json#duration-modified", "entity": {"type": "formula", "id": "duration-modified"}, "tokens_approx": 95, "tags": ["formula", "fixed-income-credit"]}
{"id": "formula:convexity", "title": "Convexity", "text": "# Convexity (Formula)\n\n**Summary:** Second-order rate sensitivity of bond price.\n\n**LaTeX:** `C = \\frac{1}{P}\\sum_{t=1}^{N} \\frac{t(t+1) \\, CF_t}{(1+y)^{t+2}}, \\quad \\frac{\\Delta P}{P} \\approx -D_{mod}\\Delta y + \\frac{1}{2} C (\\Delta y)^2`\n\n**Plain text:** `Price change ~ -D_mod * dy + 0.5 * C * (dy)^2`\n\n**Variables:**\n  - CF_t: Cash flow at time t — \n  - y: Yield — \n\n**Intuition:** Curvature of the price-yield relationship. Long convexity = profit from rate volatility.", "source": "https://hedgefund.wiki/api/formulas.json#convexity", "entity": {"type": "formula", "id": "convexity"}, "tokens_approx": 118, "tags": ["formula", "fixed-income-credit"]}
{"id": "formula:yield-to-maturity", "title": "Yield to Maturity", "text": "# Yield to Maturity (Formula)\n\n**Summary:** The IRR of a bond's cash flows that equates PV to current price.\n\n**LaTeX:** `P = \\sum_{t=1}^{N}\\frac{CF_t}{(1+y)^t}`\n\n**Plain text:** `P = sum(CF_t / (1+y)^t)`\n\n**Intuition:** What you earn if you hold the bond to maturity and reinvest coupons at y.", "source": "https://hedgefund.wiki/api/formulas.json#yield-to-maturity", "entity": {"type": "formula", "id": "yield-to-maturity"}, "tokens_approx": 73, "tags": ["formula", "fixed-income-credit"]}
{"id": "formula:cds-pricing", "title": "CDS Spread (simplified)", "text": "# CDS Spread (simplified) (Formula)\n\n**Summary:** Annual CDS premium implied by default probability and recovery.\n\n**LaTeX:** `s \\approx p \\cdot (1 - R)`\n\n**Plain text:** `spread ~ default_probability * (1 - recovery)`\n\n**Variables:**\n  - s: CDS spread (annual) — \n  - p: Annual default probability (risk-neutral) — \n  - R: Recovery rate — \n\n**Intuition:** Premium compensates for expected loss given default times the probability of default.", "source": "https://hedgefund.wiki/api/formulas.json#cds-pricing", "entity": {"type": "formula", "id": "cds-pricing"}, "tokens_approx": 110, "tags": ["formula", "fixed-income-credit"]}
{"id": "formula:merton-distance-default", "title": "Merton Distance to Default", "text": "# Merton Distance to Default (Formula)\n\n**Summary:** Standard deviations between firm asset value and default threshold.\n\n**LaTeX:** `DD = \\frac{\\ln(V/D) + (\\mu_V - \\sigma_V^2/2)T}{\\sigma_V \\sqrt{T}}`\n\n**Plain text:** `DD = [ln(V/D) + (mu - sigma^2/2)*T] / (sigma * sqrt(T))`\n\n**Variables:**\n  - V: Firm asset value — \n  - D: Default barrier (face debt) — \n  - μ_V: Drift of assets — \n  - σ_V: Volatility of assets — \n\n**Intuition:** How many standard deviations the firm sits above default. EDF = N(−DD).", "source": "https://hedgefund.wiki/api/formulas.json#merton-distance-default", "entity": {"type": "formula", "id": "merton-distance-default"}, "tokens_approx": 126, "tags": ["formula", "fixed-income-credit"]}
{"id": "formula:geometric-brownian-motion", "title": "Geometric Brownian Motion", "text": "# Geometric Brownian Motion (Formula)\n\n**Summary:** The continuous-time price process underlying Black-Scholes.\n\n**LaTeX:** `dS_t = \\mu S_t \\, dt + \\sigma S_t \\, dW_t`\n\n**Plain text:** `dS = mu*S*dt + sigma*S*dW`\n\n**Variables:**\n  - S_t: Asset price at time t — \n  - μ: Drift — \n  - σ: Volatility — \n  - dW: Wiener increment — \n\n**Intuition:** Log-returns are normal with mean (μ−σ²/2)dt and variance σ²dt.\n\n**Edge cases:** Returns are not log-normal in practice — fat tails, jumps, vol clustering.; Negative interest rates break GBM-based rate models — Vasicek/HW preferred.", "source": "https://hedgefund.wiki/api/formulas.json#geometric-brownian-motion", "entity": {"type": "formula", "id": "geometric-brownian-motion"}, "tokens_approx": 143, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:ornstein-uhlenbeck", "title": "Ornstein-Uhlenbeck Process", "text": "# Ornstein-Uhlenbeck Process (Formula)\n\n**Summary:** Continuous-time mean-reverting stochastic process.\n\n**LaTeX:** `dX_t = \\theta(\\mu - X_t)\\,dt + \\sigma\\,dW_t`\n\n**Plain text:** `dX = theta*(mu - X)*dt + sigma*dW`\n\n**Variables:**\n  - θ: Mean-reversion speed — \n  - μ: Long-run mean — \n  - σ: Volatility — \n\n**Intuition:** Used for spreads, vol, rates. Half-life of mean reversion = ln(2)/θ.", "source": "https://hedgefund.wiki/api/formulas.json#ornstein-uhlenbeck", "entity": {"type": "formula", "id": "ornstein-uhlenbeck"}, "tokens_approx": 97, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:vasicek-rate", "title": "Vasicek Short-Rate Model", "text": "# Vasicek Short-Rate Model (Formula)\n\n**Summary:** Mean-reverting Gaussian short-rate model.\n\n**LaTeX:** `dr_t = a(b - r_t)\\,dt + \\sigma \\, dW_t`\n\n**Plain text:** `dr = a*(b - r)*dt + sigma*dW`\n\n**Variables:**\n  - a: Mean-reversion speed — \n  - b: Long-run mean rate — \n  - σ: Rate volatility — \n\n**Edge cases:** Allows negative rates (a feature post-2014, an annoyance pre-2014).", "source": "https://hedgefund.wiki/api/formulas.json#vasicek-rate", "entity": {"type": "formula", "id": "vasicek-rate"}, "tokens_approx": 95, "tags": ["formula", "fixed-income-credit"]}
{"id": "formula:garch-1-1", "title": "GARCH(1,1)", "text": "# GARCH(1,1) (Formula)\n\n**Summary:** Conditional variance with persistent volatility clustering.\n\n**LaTeX:** `\\sigma_t^2 = \\omega + \\alpha \\epsilon_{t-1}^2 + \\beta \\sigma_{t-1}^2`\n\n**Plain text:** `sigma^2_t = omega + alpha*eps^2_{t-1} + beta*sigma^2_{t-1}`\n\n**Variables:**\n  - ω: Long-run variance constant — \n  - α: ARCH coefficient (shock impact) — \n  - β: GARCH coefficient (volatility persistence) — \n\n**Edge cases:** α + β < 1 required for stationarity; α + β ≈ 1 is the IGARCH case (RiskMetrics EWMA).", "source": "https://hedgefund.wiki/api/formulas.json#garch-1-1", "entity": {"type": "formula", "id": "garch-1-1"}, "tokens_approx": 127, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:ewma-volatility", "title": "Exponentially-Weighted Moving Average Variance", "text": "# Exponentially-Weighted Moving Average Variance (Formula)\n\n**Summary:** RiskMetrics-style variance with exponential decay.\n\n**LaTeX:** `\\sigma_t^2 = \\lambda \\sigma_{t-1}^2 + (1-\\lambda) r_{t-1}^2`\n\n**Plain text:** `sigma^2_t = lambda*sigma^2_{t-1} + (1-lambda)*r^2_{t-1}`\n\n**Variables:**\n  - λ: Decay parameter — Typical 0.94 for daily (RiskMetrics)\n\n**Intuition:** Recent shocks weighted more than older ones — smoothing without long memory.", "source": "https://hedgefund.wiki/api/formulas.json#ewma-volatility", "entity": {"type": "formula", "id": "ewma-volatility"}, "tokens_approx": 110, "tags": ["formula", "quantitative-methods"]}
{"id": "formula:almgren-chriss", "title": "Almgren-Chriss Optimal Execution", "text": "# Almgren-Chriss Optimal Execution (Formula)\n\n**Summary:** Closed-form trading schedule that minimizes expected cost plus risk × variance of cost.\n\n**LaTeX:** `x_t = X \\cdot \\frac{\\sinh(\\kappa(T - t))}{\\sinh(\\kappa T)}, \\quad \\kappa = \\sqrt{\\frac{\\lambda \\sigma^2}{\\eta}}`\n\n**Plain text:** `x_t = X * sinh(kappa*(T-t)) / sinh(kappa*T)`\n\n**Variables:**\n  - X: Total shares to trade — \n  - T: Time horizon — \n  - η: Permanent impact coefficient — \n  - σ: Volatility — \n  - λ: Risk aversion — \n\n**Intuition:** Trade faster when risk-averse (high λ) or when impact is low (small η). Trade slower when patient.", "source": "https://hedgefund.wiki/api/formulas.json#almgren-chriss", "entity": {"type": "formula", "id": "almgren-chriss"}, "tokens_approx": 151, "tags": ["formula", "trading-execution"]}
{"id": "formula:kyle-lambda", "title": "Kyle's Lambda", "text": "# Kyle's Lambda (Formula)\n\n**Summary:** Linear price impact coefficient from Kyle's (1985) microstructure model.\n\n**LaTeX:** `\\Delta P = \\lambda \\cdot Q`\n\n**Plain text:** `delta_P = lambda * Q`\n\n**Variables:**\n  - Q: Net order flow — \n  - λ: Price impact (illiquidity) coefficient — \n\n**Intuition:** Higher λ = thinner market. The slope at which a market maker shifts price for incremental flow.", "source": "https://hedgefund.wiki/api/formulas.json#kyle-lambda", "entity": {"type": "formula", "id": "kyle-lambda"}, "tokens_approx": 98, "tags": ["formula", "market-microstructure"]}
{"id": "formula:amihud-illiquidity", "title": "Amihud Illiquidity Measure", "text": "# Amihud Illiquidity Measure (Formula)\n\n**Summary:** Average absolute return per unit dollar volume.\n\n**LaTeX:** `\\text{ILLIQ}_i = \\frac{1}{D_i}\\sum_{t=1}^{D_i} \\frac{|R_{i,t}|}{V_{i,t}}`\n\n**Plain text:** `ILLIQ_i = mean(|R_t| / Volume_t)`\n\n**Variables:**\n  - R_t: Daily return — \n  - V_t: Daily dollar volume — \n\n**Intuition:** How much price moves per dollar traded. High illiquidity → high impact.", "source": "https://hedgefund.wiki/api/formulas.json#amihud-illiquidity", "entity": {"type": "formula", "id": "amihud-illiquidity"}, "tokens_approx": 100, "tags": ["formula", "market-microstructure"]}
{"id": "formula:fundamental-law-active-management", "title": "Grinold's Fundamental Law of Active Management", "text": "# Grinold's Fundamental Law of Active Management (Formula)\n\n**Summary:** Information ratio decomposes into information coefficient times the square root of breadth.\n\n**LaTeX:** `IR \\approx IC \\cdot \\sqrt{N}`\n\n**Plain text:** `IR ~ IC * sqrt(N)`\n\n**Variables:**\n  - IC: Information coefficient — Correlation between forecast and realized return\n  - N: Breadth — Number of independent bets per year\n\n**Intuition:** Skill (IC) × diversification (breadth) = risk-adjusted active return. The math reason quants seek breadth.", "source": "https://hedgefund.wiki/api/formulas.json#fundamental-law-active-management", "entity": {"type": "formula", "id": "fundamental-law-active-management"}, "tokens_approx": 129, "tags": ["formula", "portfolio-construction"]}
{"id": "formula:efficient-frontier", "title": "Markowitz Efficient Frontier (Tangency)", "text": "# Markowitz Efficient Frontier (Tangency) (Formula)\n\n**Summary:** Tangency portfolio weights with risky assets and a risk-free asset.\n\n**LaTeX:** `w \\propto \\Sigma^{-1} (\\mu - r \\mathbf{1})`\n\n**Plain text:** `w ~ Sigma^-1 * (mu - r * 1)`\n\n**Variables:**\n  - Σ: Covariance matrix — \n  - μ: Expected returns vector — \n  - r: Risk-free rate — \n\n**Intuition:** Optimal weights tilt toward higher Sharpe assets, downweight correlated ones. Notoriously sensitive to μ estimation error.", "source": "https://hedgefund.wiki/api/formulas.json#efficient-frontier", "entity": {"type": "formula", "id": "efficient-frontier"}, "tokens_approx": 119, "tags": ["formula", "portfolio-construction"]}
{"id": "formula:irr-newton", "title": "Internal Rate of Return (IRR)", "text": "# Internal Rate of Return (IRR) (Formula)\n\n**Summary:** Discount rate that zeros NPV of a cash flow stream.\n\n**LaTeX:** `0 = \\sum_{t=0}^{N} \\frac{CF_t}{(1+IRR)^t}`\n\n**Plain text:** `0 = sum(CF_t / (1+IRR)^t)`\n\n**Variables:**\n  - CF_t: Cash flow at period t — \n\n**Intuition:** Annualized rate that makes the investment NPV-neutral.\n\n**Edge cases:** IRR may have multiple roots when cash flows change sign more than once.; Assumes interim cash flows reinvest at IRR — Modified IRR (MIRR) corrects this.", "source": "https://hedgefund.wiki/api/formulas.json#irr-newton", "entity": {"type": "formula", "id": "irr-newton"}, "tokens_approx": 125, "tags": ["formula", "alternative-investments"]}
{"id": "structure:delaware-lp", "title": "Delaware Limited Partnership", "text": "# Delaware Limited Partnership (Structure)\n\n**Summary:** The default US onshore hedge fund vehicle.\n\n**Purpose:** House US-taxable investors as limited partners; the GP entity (typically a Delaware LLC) holds management and incentive economics.\n\n**Mechanics:** GP-LP relationship governed by an LPA. LPs receive K-1s reporting their share of fund income (passed through). State-of-formation: Delaware (Court of Chancery jurisprudence). Often paired with an offshore feeder in a master-feeder structure.\n\n**Tax:** Pass-through (Subchapter K). LPs taxed on share of income each year regardless of distributions.\n\n**Eligibility:** Accredited investors under Reg D 506(b)/(c); typically also Qualified Purchasers if the fund relies on 3(c)(7).\n\n**Jurisdictions:** Delaware (US)\n\n**Pros:** Pass-through taxation; Mature legal precedent; LP liability limited\n\n**Cons:** UBTI for tax-exempt LPs unless invested via blocker; K-1 timing/complexity", "source": "https://hedgefund.wiki/api/fund-structures.json#delaware-lp", "entity": {"type": "structure", "id": "delaware-lp"}, "tokens_approx": 234, "tags": ["structure"]}
{"id": "structure:cayman-fund", "title": "Cayman Islands Exempted Company", "text": "# Cayman Islands Exempted Company (Structure)\n\n**Summary:** The default offshore hedge fund vehicle for non-US and US tax-exempt investors.\n\n**Purpose:** Tax-neutral aggregation of non-US and US tax-exempt capital. The Cayman entity is treated as a corporation for US tax — providing a 'blocker' against UBTI for tax-exempt LPs.\n\n**Mechanics:** Exempted Company under Cayman Companies Act. Registered with CIMA (Cayman Islands Monetary Authority) under Mutual Funds Act. AEOI/CRS/FATCA reporting required. Typical board: 2 independent Cayman directors + 1 sponsor director.\n\n**Tax:** Cayman: 0% income tax, 0% capital gains. US tax-exempt LPs: corporate blocker shields UBTI. Non-US LPs: not subject to US tax on capital gains (subject to FIRPTA).\n\n**Eligibility:** Same Reg D / 3(c)(1) or 3(c)(7) gates as onshore feeder for US investors; non-US accept under local exemptions.\n\n**Jurisdictions:** Cayman Islands\n\n**Pros:** Tax neutrality; UBTI blocker for tax-exempts; Familiar to global LPs; Mature service-provider ecosystem\n\n**Cons:** AEOI/FATCA reporting overhead; EU AIFMD marketing requires NPPR or reverse-solicitation; OECD BEPS substance pressure", "source": "https://hedgefund.wiki/api/fund-structures.json#cayman-fund", "entity": {"type": "structure", "id": "cayman-fund"}, "tokens_approx": 289, "tags": ["structure"]}
{"id": "structure:master-feeder-structure", "title": "Master-Feeder Structure", "text": "# Master-Feeder Structure (Structure)\n\n**Summary:** Two or more feeder funds in different jurisdictions pool assets in a single master fund where trading occurs.\n\n**Purpose:** Tax-neutral aggregation of US-taxable, US tax-exempt, and non-US capital while maintaining a single trading book.\n\n**Mechanics:** (1) Onshore feeder (Delaware LP) for US-taxable. (2) Offshore feeder (Cayman Ltd) for US tax-exempt and non-US. (3) Master (Cayman Ltd) where assets and trading reside. Each feeder owns master shares pro-rata to its capital. Performance allocations and management fees flow from the feeders to the GP/manager.\n\n**Tax:** K-1 to onshore LPs, blocker treatment for tax-exempts via offshore feeder, no US tax for non-US (subject to FIRPTA).\n\n**Eligibility:** Set at feeder level; typically Reg D / QP standards.\n\n**Jurisdictions:** Cayman Islands (master + offshore feeder), Delaware (onshore feeder)\n\n**Pros:** Single trading book; Tax neutrality across LP classes; Operational efficiency\n\n**Cons:** More entities = more fees and admin; Pro-rata cross-class issues if master suspends", "source": "https://hedgefund.wiki/api/fund-structures.json#master-feeder-structure", "entity": {"type": "structure", "id": "master-feeder-structure"}, "tokens_approx": 271, "tags": ["structure"]}
{"id": "structure:luxembourg-raif", "title": "Luxembourg RAIF", "text": "# Luxembourg RAIF (Structure)\n\n**Summary:** Reserved Alternative Investment Fund — flexible Luxembourg vehicle for AIFs requiring an authorized AIFM.\n\n**Purpose:** Marketing-passportable EU vehicle for hedge fund-style strategies under AIFMD without direct CSSF authorization of the fund itself.\n\n**Mechanics:** Set up in 1-3 weeks (no CSSF approval required), but requires an authorized AIFM. Can be structured as SCSp (limited partnership), SA, Sàrl, or umbrella with sub-funds. Often used for credit, PE, and infra; growing presence in liquid alts.\n\n**Tax:** 0.01% subscription tax (SICAV-RAIF) or full corporate tax (other forms). Treaty access varies by sub-fund/legal form.\n\n**Jurisdictions:** Luxembourg\n\n**Pros:** Fast setup; Passport across EU under AIFMD; Familiar to European institutional LPs\n\n**Cons:** Requires authorized AIFM; Not retail-marketable (RAIF is for professional investors)", "source": "https://hedgefund.wiki/api/fund-structures.json#luxembourg-raif", "entity": {"type": "structure", "id": "luxembourg-raif"}, "tokens_approx": 225, "tags": ["structure"]}
{"id": "structure:ireland-icav", "title": "Irish ICAV", "text": "# Irish ICAV (Structure)\n\n**Summary:** Irish Collective Asset-management Vehicle — corporate fund vehicle, popular for UCITS and AIFMD funds.\n\n**Purpose:** EU-passportable fund structure with Irish tax-treaty access (especially favorable for US equity exposure via 0% withholding).\n\n**Mechanics:** Authorized by the Central Bank of Ireland. Can elect check-the-box for US tax purposes — partnership treatment shields tax-exempt LPs from UBTI without corporate blocker friction.\n\n**Tax:** Irish: no fund-level tax for non-Irish residents. US: check-the-box partnership election available.\n\n**Jurisdictions:** Ireland\n\n**Pros:** US tax-treaty (0% on US dividends for US-tax purposes if QFII status); Check-the-box flexibility; Strong UCITS ecosystem\n\n**Cons:** Higher setup and ongoing costs than RAIF; Central Bank approval required", "source": "https://hedgefund.wiki/api/fund-structures.json#ireland-icav", "entity": {"type": "structure", "id": "ireland-icav"}, "tokens_approx": 207, "tags": ["structure"]}
{"id": "structure:section-3c1-fund", "title": "Section 3(c)(1) Fund", "text": "# Section 3(c)(1) Fund (Structure)\n\n**Summary:** US private fund relying on Investment Company Act exemption for funds with ≤100 beneficial owners.\n\n**Purpose:** Avoid registration as an investment company under the ICA.\n\n**Mechanics:** Limit beneficial owners to 100 (with knowledgeable-employee carve-outs and certain look-throughs). Rely on Reg D 506 for the offering exemption. Investors must be accredited.\n\n**Eligibility:** Accredited investors only (Reg D requirement); 100-investor cap.\n\n**Pros:** Lower investor-eligibility bar than 3(c)(7); Suitable for emerging managers\n\n**Cons:** Hard cap at 100 LPs; Difficult to scale assets without converting to 3(c)(7)", "source": "https://hedgefund.wiki/api/fund-structures.json#section-3c1-fund", "entity": {"type": "structure", "id": "section-3c1-fund"}, "tokens_approx": 167, "tags": ["structure"]}
{"id": "structure:section-3c7-fund", "title": "Section 3(c)(7) Fund", "text": "# Section 3(c)(7) Fund (Structure)\n\n**Summary:** US private fund relying on ICA exemption for funds whose investors are all Qualified Purchasers — no investor-count cap.\n\n**Purpose:** Scale beyond the 100-investor cap of 3(c)(1) by restricting to QPs.\n\n**Mechanics:** All beneficial owners must be QPs ($5m investments individuals, $25m entities). 'Section 12(g)' record-holder limit (2,000 holders / 500 non-accredited) caps practical scale before 1934 Act registration is triggered.\n\n**Eligibility:** Qualified Purchasers only.\n\n**Pros:** No 100-investor cap; Standard for institutional-scale funds\n\n**Cons:** Higher eligibility bar excludes many accredited individuals", "source": "https://hedgefund.wiki/api/fund-structures.json#section-3c7-fund", "entity": {"type": "structure", "id": "section-3c7-fund"}, "tokens_approx": 167, "tags": ["structure"]}
{"id": "structure:side-pocket-structure", "title": "Side Pocket", "text": "# Side Pocket (Structure)\n\n**Summary:** Segregated accounting compartment for illiquid or hard-to-value positions within a hedge fund.\n\n**Purpose:** Prevent stale-mark dilution between subscribers and redeemers when an asset becomes illiquid or impaired.\n\n**Mechanics:** On designation, the asset is moved to the side pocket. Existing investors hold pro-rata Series-B shares; new subscribers do not participate; redemptions of side-pocket shares occur only on realization. Performance fees on side-pocket P&L crystallize at realization.\n\n**Jurisdictions:** Cayman, Delaware\n\n**Pros:** Fair to all classes when illiquidity emerges; Preserves manager flexibility\n\n**Cons:** Investor sentiment damage when used; SEC scrutiny of designation criteria post-2008", "source": "https://hedgefund.wiki/api/fund-structures.json#side-pocket-structure", "entity": {"type": "structure", "id": "side-pocket-structure"}, "tokens_approx": 188, "tags": ["structure"]}
{"id": "structure:gate-mechanism", "title": "Gate", "text": "# Gate (Structure)\n\n**Summary:** Redemption restriction limiting the percentage of fund AUM (or per-investor stake) redeemable in a single window.\n\n**Purpose:** Prevent fire-sale liquidations that would crystallize losses for remaining LPs.\n\n**Mechanics:** Investor-level gate: caps each LP at e.g. 25% of stake per quarter. Fund-level gate: caps total redemptions at e.g. 10% of AUM per quarter, pro-rated. Excess requests roll to the next redemption date.\n\n**Pros:** Protects continuing LPs; Buys time in a liquidity crunch\n\n**Cons:** Reputational damage; Often leads to wholesale redemptions when lifted", "source": "https://hedgefund.wiki/api/fund-structures.json#gate-mechanism", "entity": {"type": "structure", "id": "gate-mechanism"}, "tokens_approx": 151, "tags": ["structure"]}
{"id": "structure:managed-account", "title": "Managed Account / SMA", "text": "# Managed Account / SMA (Structure)\n\n**Summary:** A separately managed account where the LP holds assets in their own name with the manager trading via limited POA.\n\n**Purpose:** Customization, transparency, and bankruptcy-remote custody for institutional LPs.\n\n**Mechanics:** LP opens accounts at LP-selected prime broker and custodian. Manager receives investment management agreement (IMA) with limited POA to trade. LP holds full position transparency, customizes guidelines, retains custody, and pays a negotiated (often lower) fee schedule.\n\n**Pros:** Custody control (no commingling); Position transparency; Customizable guidelines (ESG, exclusions, leverage); Often lower fees\n\n**Cons:** Higher operational burden for LP; Manager dilution of attention vs commingled fund; Capacity gating by managers", "source": "https://hedgefund.wiki/api/fund-structures.json#managed-account", "entity": {"type": "structure", "id": "managed-account"}, "tokens_approx": 201, "tags": ["structure"]}
{"id": "structure:ucits-structure", "title": "UCITS", "text": "# UCITS (Structure)\n\n**Summary:** EU regulated fund structure with daily liquidity, restricted leverage, and pan-EEA marketing passport.\n\n**Purpose:** Retail-marketable EU fund vehicle. Hedge fund strategies adapted into 'newcits' run as UCITS.\n\n**Mechanics:** Constraints: daily liquidity to investors, max 200% gross VaR-based leverage (or 100% commitment-method), 5/10/40 concentration rules, restricted instrument types (no direct commodities, limited derivatives use). UCITS V (2014) framework.\n\n**Pros:** Pan-EEA passport; Retail-marketable; Investor familiarity in Europe\n\n**Cons:** Liquidity and leverage constraints incompatible with many HF strategies; Higher operating cost (depositary)", "source": "https://hedgefund.wiki/api/fund-structures.json#ucits-structure", "entity": {"type": "structure", "id": "ucits-structure"}, "tokens_approx": 174, "tags": ["structure"]}
{"id": "structure:founders-share-class", "title": "Founders / Founder Share Class", "text": "# Founders / Founder Share Class (Structure)\n\n**Summary:** A discounted share class for early or large investors who anchor a new fund's launch.\n\n**Purpose:** Incentivize early capital commitment and lock in long-duration backers.\n\n**Mechanics:** Typical terms: 1% management / 10% performance (vs 1.5%/20% for standard); often 2-year hard lock-up; capacity to invest up to a threshold (e.g., $25m or 15% of fund); rolls into standard class when AUM crosses a level.\n\n**Pros:** LP gets economics; GP gets stable anchor capital\n\n**Cons:** Permanent vs phase-out structure can become a drag at scale", "source": "https://hedgefund.wiki/api/fund-structures.json#founders-share-class", "entity": {"type": "structure", "id": "founders-share-class"}, "tokens_approx": 149, "tags": ["structure"]}
{"id": "structure:seed-deal", "title": "Seed Deal", "text": "# Seed Deal (Structure)\n\n**Summary:** An anchor LP provides initial capital plus revenue share or equity in the management company in exchange for capacity and economics.\n\n**Purpose:** Solve the chicken-and-egg of new-fund launches: PMs need capital, capital wants to see capital.\n\n**Mechanics:** Typical seed: $50-200m anchor commitment, 2-3 year lock, in exchange for 10-25% of fee revenue (sometimes capped, sometimes perpetual) or equity in the GP. Major seeders: Investcorp-Tages, Borealis, Reservoir, Stable Asset Management, Proteus, Blackstone Strategic Alliance.\n\n**Pros:** GP launches at credible scale; Seeder gets economics + capacity\n\n**Cons:** Permanent revenue dilution; Strings attached on operations and brand", "source": "https://hedgefund.wiki/api/fund-structures.json#seed-deal", "entity": {"type": "structure", "id": "seed-deal"}, "tokens_approx": 181, "tags": ["structure"]}
{"id": "structure:pass-through-expenses", "title": "Pass-Through Expense Structure", "text": "# Pass-Through Expense Structure (Structure)\n\n**Summary:** Multi-strat platform fee model where actual expenses (PM comp, technology, financing, infrastructure) are charged to the fund instead of a fixed management fee.\n\n**Purpose:** Fund the platform's enormous infrastructure (PMs, tech, data, financing) without an artificial management fee cap.\n\n**Mechanics:** Investors are charged actual platform expenses, typically running 5-8% of AUM gross. Performance fees layer on top of expenses. LPs receive itemized expense reports. Disclosure has tightened post-2022 SEC rules on private fund advisor fees.\n\n**Pros:** Aligned: expenses are actual costs; Allows competitive PM compensation; Has produced sustained Sharpe 2-4 returns\n\n**Cons:** All-in cost often 5-8% gross — much higher than 2/20; Less transparency historically (now improving); SEC private fund advisor rules increasing reporting burden", "source": "https://hedgefund.wiki/api/fund-structures.json#pass-through-expenses", "entity": {"type": "structure", "id": "pass-through-expenses"}, "tokens_approx": 225, "tags": ["structure"]}
{"id": "regulation:investment-advisers-act", "title": "Investment Advisers Act of 1940", "text": "# Investment Advisers Act of 1940 (Regulation — US)\n_Investment Advisers Act of 1940_\n\n**Regulator:** SEC\n · **Enacted:** 1940\n\n**Summary:** The foundational US statute governing investment advisers, requiring registration, fiduciary duty, and a regulated compliance program.\n\n**Scope:** Applies to any person who, for compensation, advises others on investments in securities. Hedge fund managers fall under it.\n\n**Key provisions:**\n  • Section 206 — antifraud, fiduciary duty\n  • Rule 206(4)-7 — written compliance program\n  • Rule 206(4)-8 — antifraud rule for advisers to pooled investment vehicles\n  • Section 204 — books and records (Rule 204-2)\n  • Custody Rule 206(4)-2 — surprise audit, qualified custodian\n\n**Filings:** Form ADV (Annual + amendments: Registration and brochure); Form CRS (Annual + on material change: Retail relationship summary)\n\n**Official:** https://www.sec.gov/about/laws/iaa40.pdf", "source": "https://hedgefund.wiki/api/regulations.json#investment-advisers-act", "entity": {"type": "regulation", "id": "investment-advisers-act"}, "tokens_approx": 228, "tags": ["regulation", "us"]}
{"id": "regulation:investment-company-act", "title": "Investment Company Act of 1940", "text": "# Investment Company Act of 1940 (Regulation — US)\n\n**Regulator:** SEC\n · **Enacted:** 1940\n\n**Summary:** Governs investment companies (mutual funds, closed-end funds). Hedge funds rely on Section 3(c)(1) or 3(c)(7) exclusions.\n\n**Scope:** Anyone holding themselves out as an investment company OR primarily engaged in investing in securities.\n\n**Key provisions:**\n  • Section 3(c)(1) — exclusion for funds with ≤100 beneficial owners (or 250 under emerging growth amendment)\n  • Section 3(c)(7) — exclusion for funds whose investors are all Qualified Purchasers\n  • Rule 12d1 — fund-of-funds investment limits\n\n**Official:** https://www.sec.gov/about/laws/ica40.pdf", "source": "https://hedgefund.wiki/api/regulations.json#investment-company-act", "entity": {"type": "regulation", "id": "investment-company-act"}, "tokens_approx": 166, "tags": ["regulation", "us"]}
{"id": "regulation:form-adv", "title": "Form ADV", "text": "# Form ADV (Regulation — US)\n\n**Regulator:** SEC\n\n**Summary:** Investment adviser registration form, with public Part 1 (data) and Part 2 (client brochure).\n\n**Key provisions:**\n  • Part 1A — adviser business data, AUM, employees, custody, disciplinary history (publicly available via IAPD)\n  • Part 2A — narrative client brochure\n  • Part 2B — brochure supplements on supervised persons\n  • Part 3 / Form CRS — retail relationship summary\n\n**Filings:** Form ADV (Annual within 90 days of FY end + amendments on material change: Registration / disclosure)\n\n**Official:** https://www.sec.gov/divisions/investment/iaregulation/iadisclosure.shtml", "source": "https://hedgefund.wiki/api/regulations.json#form-adv", "entity": {"type": "regulation", "id": "form-adv"}, "tokens_approx": 160, "tags": ["regulation", "us"]}
{"id": "regulation:form-pf", "title": "Form PF", "text": "# Form PF (Regulation — US)\n\n**Regulator:** SEC / CFTC\n · **Enacted:** 2011\n\n**Summary:** Confidential filing by private fund advisers reporting fund-level risk, leverage, and exposure data; used for systemic-risk monitoring by SEC and FSOC.\n\n**Key provisions:**\n  • Section 1 — basic adviser data, all filers\n  • Section 2 — large hedge fund advisers (> $1.5bn): quarterly reporting\n  • Section 3 — large liquidity fund advisers: monthly\n  • Section 4 — large private equity advisers\n  • 2024 amendments: 72-hour event reporting on stress (≥20% drawdown, large redemptions, prime broker termination, counterparty default)\n\n**Filings:** Form PF (Quarterly (large hedge fund), Annual (others), 72hr event-driven: Systemic risk monitoring)\n\n**Official:** https://www.sec.gov/about/forms/formpf.pdf", "source": "https://hedgefund.wiki/api/regulations.json#form-pf", "entity": {"type": "regulation", "id": "form-pf"}, "tokens_approx": 198, "tags": ["regulation", "us"]}
{"id": "regulation:regulation-d", "title": "Regulation D", "text": "# Regulation D (Regulation — US)\n\n**Regulator:** SEC\n\n**Summary:** Securities Act exemptions allowing private placement of securities to accredited investors without full SEC registration.\n\n**Key provisions:**\n  • Rule 504 — offerings up to $10m, limited investor restrictions\n  • Rule 506(b) — unlimited offering, no general solicitation, accredited investors + up to 35 sophisticated non-accredited\n  • Rule 506(c) — unlimited offering, general solicitation permitted, all purchasers must be verified accredited\n\n**Filings:** Form D (Within 15 days of first sale: Notice filing)\n\n**Official:** https://www.sec.gov/fast-answers/answers-regdhtm.html", "source": "https://hedgefund.wiki/api/regulations.json#regulation-d", "entity": {"type": "regulation", "id": "regulation-d"}, "tokens_approx": 162, "tags": ["regulation", "us"]}
{"id": "regulation:section-3c1", "title": "ICA Section 3(c)(1)", "text": "# ICA Section 3(c)(1) (Regulation — US)\n\n**Regulator:** SEC\n\n**Summary:** Investment Company Act exclusion for funds with no more than 100 beneficial owners.\n\n**Key provisions:**\n  • 100-investor cap (250 under JOBS Act 'venture capital' carve-out)\n  • Knowledgeable employee carve-outs (Rule 3c-5)\n  • Look-through rules for fund-of-funds investors (10% test)", "source": "https://hedgefund.wiki/api/regulations.json#section-3c1", "entity": {"type": "regulation", "id": "section-3c1"}, "tokens_approx": 90, "tags": ["regulation", "us"]}
{"id": "regulation:section-3c7", "title": "ICA Section 3(c)(7)", "text": "# ICA Section 3(c)(7) (Regulation — US)\n\n**Regulator:** SEC\n\n**Summary:** Investment Company Act exclusion for funds whose investors are all Qualified Purchasers.\n\n**Key provisions:**\n  • All beneficial owners must be QPs ($5m investments individuals, $25m entities)\n  • No investor count cap, but 1934 Act Section 12(g) registration triggered at 2,000 holders / 500 non-accredited", "source": "https://hedgefund.wiki/api/regulations.json#section-3c7", "entity": {"type": "regulation", "id": "section-3c7"}, "tokens_approx": 95, "tags": ["regulation", "us"]}
{"id": "regulation:dodd-frank", "title": "Dodd-Frank Act", "text": "# Dodd-Frank Act (Regulation — US)\n_Dodd-Frank Wall Street Reform and Consumer Protection Act_\n\n**Regulator:** SEC, CFTC, FRB, FDIC, OCC, FSOC\n · **Enacted:** 2010\n\n**Summary:** Post-GFC reform that mandated hedge fund SEC registration, introduced Form PF, created the Volcker Rule, and overhauled OTC derivatives.\n\n**Key provisions:**\n  • Title IV — eliminated 'private adviser' exemption; mandated SEC registration > $150m AUM\n  • Title VII — central clearing, exchange trading, and trade reporting for OTC derivatives\n  • Volcker Rule (Section 619) — limits bank prop trading and HF/PE sponsorship\n  • Title VIII — designation of systemically important FMUs\n  • Title X — created CFPB\n\n**Official:** https://www.govinfo.gov/content/pkg/PLAW-111publ203/pdf/PLAW-111publ203.pdf", "source": "https://hedgefund.wiki/api/regulations.json#dodd-frank", "entity": {"type": "regulation", "id": "dodd-frank"}, "tokens_approx": 194, "tags": ["regulation", "us"]}
{"id": "regulation:aifmd", "title": "AIFMD", "text": "# AIFMD (Regulation — EU)\n_Alternative Investment Fund Managers Directive (2011/61/EU)_\n\n**Regulator:** ESMA + national competent authorities (e.g., CSSF, CBI, BaFin, AMF, FCA-pre-Brexit)\n · **Enacted:** 2011\n\n**Summary:** EU regime governing managers of non-UCITS funds — depositary, capital, leverage, remuneration, transparency, and reporting.\n\n**Key provisions:**\n  • Authorization required for AIFMs with > €100m leveraged or > €500m unleveraged AUM\n  • Independent depositary required\n  • Annex IV reporting (semi-annual or quarterly by AUM)\n  • Marketing passport for EU AIFs / EU AIFMs\n  • AIFMD II (2024) — loan-originating funds, delegation, liquidity management tools\n\n**Official:** https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32011L0061", "source": "https://hedgefund.wiki/api/regulations.json#aifmd", "entity": {"type": "regulation", "id": "aifmd"}, "tokens_approx": 190, "tags": ["regulation", "eu"]}
{"id": "regulation:ucits", "title": "UCITS V", "text": "# UCITS V (Regulation — EU)\n_Undertakings for Collective Investment in Transferable Securities Directive V (2014/91/EU)_\n\n**Regulator:** ESMA + national competent authorities\n · **Enacted:** 2014\n\n**Summary:** EU retail-marketable fund framework — daily liquidity, restricted leverage, eligible asset rules. Underlies 'liquid alts' / 'newcits'.\n\n**Key provisions:**\n  • Daily redemption\n  • Max 200% gross VaR or 100% commitment-method leverage\n  • 5/10/40 concentration rule\n  • Eligible asset list (Article 50) — no direct commodities, restricted derivatives use\n  • Independent depositary\n\n**Official:** https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32014L0091", "source": "https://hedgefund.wiki/api/regulations.json#ucits", "entity": {"type": "regulation", "id": "ucits"}, "tokens_approx": 168, "tags": ["regulation", "eu"]}
{"id": "regulation:mifid-ii", "title": "MiFID II", "text": "# MiFID II (Regulation — EU)\n_Markets in Financial Instruments Directive II (2014/65/EU) and MiFIR_\n\n**Regulator:** ESMA + national competent authorities\n · **Enacted:** 2014\n\n**Summary:** EU framework for trading venues, transparency, best execution, transaction reporting, and (controversially) research unbundling.\n\n**Key provisions:**\n  • Best execution (Article 27) and execution-quality reporting (RTS 27/28, 2024 partial repeal)\n  • Transaction reporting (RTS 22) — granular post-trade reporting\n  • Pre/post-trade transparency on equity and non-equity\n  • Systematic Internaliser regime\n  • Research unbundling (2024 EU Listing Act allows opt-in rebundling)\n  • Position limits and reporting on commodity derivatives\n\n**Official:** https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32014L0065", "source": "https://hedgefund.wiki/api/regulations.json#mifid-ii", "entity": {"type": "regulation", "id": "mifid-ii"}, "tokens_approx": 202, "tags": ["regulation", "eu"]}
{"id": "regulation:emir", "title": "EMIR", "text": "# EMIR (Regulation — EU)\n_European Market Infrastructure Regulation (648/2012)_\n\n**Regulator:** ESMA + national competent authorities\n · **Enacted:** 2012\n\n**Summary:** EU regulation for OTC derivatives — central clearing, risk mitigation for non-cleared trades, trade reporting.\n\n**Key provisions:**\n  • Central clearing obligation for standardized OTC derivatives\n  • Margin requirements for non-centrally cleared derivatives (UMR phases 1-6, 2016-2022)\n  • Trade reporting to TRs\n  • EMIR Refit (2019) — reduced reporting burden on small counterparties\n  • EMIR 3.0 (2024) — active account requirement at EU CCPs", "source": "https://hedgefund.wiki/api/regulations.json#emir", "entity": {"type": "regulation", "id": "emir"}, "tokens_approx": 153, "tags": ["regulation", "eu"]}
{"id": "regulation:regulation-13d", "title": "Regulation 13D", "text": "# Regulation 13D (Regulation — US)\n\n**Regulator:** SEC\n · **Enacted:** 1968\n\n**Summary:** Beneficial ownership reporting for > 5% positions in publicly traded equity, with disclosure of intent.\n\n**Key provisions:**\n  • Schedule 13D — > 5% with active intent, must file within 5 business days (revised down from 10 in 2024)\n  • Schedule 13G — > 5% passive, less disclosure\n  • Section 13(f) — quarterly position reporting by managers > $100m discretionary AUM\n  • Section 13(h) — large trader reporting\n\n**Official:** https://www.sec.gov/divisions/corpfin/guidance/cfslb14e.htm", "source": "https://hedgefund.wiki/api/regulations.json#regulation-13d", "entity": {"type": "regulation", "id": "regulation-13d"}, "tokens_approx": 144, "tags": ["regulation", "us"]}
{"id": "regulation:reg-sho", "title": "Regulation SHO", "text": "# Regulation SHO (Regulation — US)\n\n**Regulator:** SEC\n · **Enacted:** 2005\n\n**Summary:** US regulation governing short selling — locate requirements, close-out obligations, threshold security restrictions.\n\n**Key provisions:**\n  • Rule 200 — order marking (long, short, short exempt)\n  • Rule 201 — alternative uptick rule (price test, triggered on 10% intraday decline)\n  • Rule 203 — locate and close-out requirements\n  • Rule 204 — close-out obligations (T+2 for short sales, T+1 since May 2024)", "source": "https://hedgefund.wiki/api/regulations.json#reg-sho", "entity": {"type": "regulation", "id": "reg-sho"}, "tokens_approx": 124, "tags": ["regulation", "us"]}
{"id": "regulation:fatca", "title": "FATCA", "text": "# FATCA (Regulation — US)\n_Foreign Account Tax Compliance Act_\n\n**Regulator:** IRS\n · **Enacted:** 2010\n\n**Summary:** US law requiring foreign financial institutions to report on US account holders or face 30% withholding.\n\n**Key provisions:**\n  • FFI agreement\n  • Form W-8BEN-E\n  • 30% withholding on US-source FDAP for non-compliant FFIs\n  • Intergovernmental Agreements (IGAs) — Model 1 and Model 2", "source": "https://hedgefund.wiki/api/regulations.json#fatca", "entity": {"type": "regulation", "id": "fatca"}, "tokens_approx": 100, "tags": ["regulation", "us"]}
{"id": "regulation:crs", "title": "CRS", "text": "# CRS (Regulation — global)\n_Common Reporting Standard_\n\n**Regulator:** OECD + national tax authorities\n · **Enacted:** 2014\n\n**Summary:** OECD-developed multilateral framework for automatic exchange of financial account information.\n\n**Key provisions:**\n  • Self-certification of tax residency\n  • Annual reporting of accounts to home jurisdictions\n  • 100+ participating jurisdictions", "source": "https://hedgefund.wiki/api/regulations.json#crs", "entity": {"type": "regulation", "id": "crs"}, "tokens_approx": 96, "tags": ["regulation", "global"]}
{"id": "regulation:cftc-cta-registration", "title": "CFTC CTA Registration", "text": "# CFTC CTA Registration (Regulation — US)\n\n**Regulator:** CFTC / NFA\n\n**Summary:** Registration regime for Commodity Trading Advisors and Commodity Pool Operators.\n\n**Key provisions:**\n  • CTA registration for advisors trading futures, swaps, and other commodity interests\n  • CPO registration for operators of commodity pools (often dual-registered with SEC)\n  • Rule 4.7 exemption for advisors to QEPs (qualified eligible persons)\n  • NFA membership and compliance obligations", "source": "https://hedgefund.wiki/api/regulations.json#cftc-cta-registration", "entity": {"type": "regulation", "id": "cftc-cta-registration"}, "tokens_approx": 119, "tags": ["regulation", "us"]}
{"id": "regulation:hsr-act", "title": "Hart-Scott-Rodino Act", "text": "# Hart-Scott-Rodino Act (Regulation — US)\n_Hart-Scott-Rodino Antitrust Improvements Act of 1976_\n\n**Regulator:** FTC + DOJ Antitrust Division\n · **Enacted:** 1976\n\n**Summary:** Pre-merger notification regime for transactions exceeding size thresholds (size-of-transaction $119.5m for 2024 indexed annually).\n\n**Key provisions:**\n  • Notification + 30-day waiting period (15 days for cash tender offers and bankruptcy)\n  • Second Request authority for in-depth review\n  • Expedited review of investment-only positions (< 10%, no participation)\n  • 2024 HSR rule overhaul — significantly expanded disclosure", "source": "https://hedgefund.wiki/api/regulations.json#hsr-act", "entity": {"type": "regulation", "id": "hsr-act"}, "tokens_approx": 151, "tags": ["regulation", "us"]}
{"id": "event:aw-jones-founds-first-hedge-fund", "title": "A.W. Jones founds the first 'hedged fund'", "text": "# A.W. Jones founds the first 'hedged fund' (1949-01-01)\n\n**Summary:** Sociologist-turned-investor Alfred Winslow Jones launches A.W. Jones & Co with $100,000, structuring it as a long/short equity partnership with leverage and a 20% incentive allocation. The blueprint for an entire industry.\n\n**Actors:** Alfred Winslow Jones\n\n**Mechanism:** Long undervalued stocks, short overvalued ones, use leverage. Charge 20% of gains; no management fee.\n\n**Lessons:**\n  • Hedging market exposure was the original innovation; the leverage and fee structure became the genre's signature.", "source": "https://hedgefund.wiki/api/timeline.json#aw-jones-founds-first-hedge-fund", "entity": {"type": "event", "id": "aw-jones-founds-first-hedge-fund"}, "tokens_approx": 144, "tags": ["origin", "structure", "event"]}
{"id": "event:soros-breaks-boe", "title": "Soros 'breaks the Bank of England'", "text": "# Soros 'breaks the Bank of England' (1992-09-16)\n\n**Summary:** Black Wednesday. George Soros's Quantum Fund shorts ~$10bn of GBP against the deutschmark; the BoE is forced to withdraw GBP from the ERM. Quantum reportedly made $1bn+ on the trade.\n\n**Actors:** George Soros, Stanley Druckenmiller, Quantum Fund\n\n**Mechanism:** Identified that GBP was overvalued in the ERM; the BoE could not credibly defend the peg given UK economic weakness and German rates. Built the position quietly, then publicly disclosed for crowding effect.\n\n**Magnitude:** $1.0bn+ Quantum profit; ~$3.4bn UK reserves spent\n\n**Lessons:**\n  • A central bank can lose to the market when the peg is fundamentally untenable.\n  • Reflexive feedback loops accelerate currency unwinds.", "source": "https://hedgefund.wiki/api/timeline.json#soros-breaks-boe", "entity": {"type": "event", "id": "soros-breaks-boe"}, "tokens_approx": 188, "tags": ["macro", "fx", "currency-crisis", "event"]}
{"id": "event:ltcm-collapse", "title": "LTCM collapse", "text": "# LTCM collapse (1998-09-23)\n\n**Summary:** Long-Term Capital Management — the John Meriwether-led fund staffed by Salomon's RV desk, Robert Merton, and Myron Scholes — loses ~$4.6bn in months as Russia defaults, swap spreads blow out, and forced deleveraging cascades through every relative-value position. The Fed orchestrates a $3.6bn 14-bank rescue.\n\n**Actors:** John Meriwether, Robert Merton, Myron Scholes, consortium of 14 Wall Street banks\n\n**Mechanism:** Massive convergence trades (swap spreads, on/off-the-run Treasuries, Italian rates, equity vol) at 25× leverage. When Russia defaulted, all RV positions widened simultaneously and forced unwinds destroyed the book.\n\n**Magnitude:** $4.6bn loss; $1.25tn notional positions\n\n**Lessons:**\n  • Correlation goes to 1 in a crisis.\n  • Liquidity-providing strategies become liquidity-demanding strategies in stress.\n  • VaR badly underestimates tail risk in fat-tailed strategies.\n  • Single-PB exposure is fatal.", "source": "https://hedgefund.wiki/api/timeline.json#ltcm-collapse", "entity": {"type": "event", "id": "ltcm-collapse"}, "tokens_approx": 242, "tags": ["systemic", "rv", "leverage", "case-study", "event"]}
{"id": "event:tiger-management-closes", "title": "Tiger Management closes", "text": "# Tiger Management closes (2000-03-30)\n\n**Summary:** Julian Robertson closes Tiger Management after $7.7bn in redemptions and underperformance during the dot-com bubble — Tiger's value discipline was punished by tech mania. Robertson seeded ~30 'Tiger Cubs' from his alumni.\n\n**Actors:** Julian Robertson\n\n**Mechanism:** Long undervalued (paper, airlines, tobacco) / short overvalued (tech). The value-tech spread blew out for 18 months before the bubble burst — Tiger ran out of patience and capital first.\n\n**Lessons:**\n  • You can be right and broke at the same time.\n  • Manager quality outlives any single fund — Tiger Cubs (Lone Pine, Maverick, Blue Ridge, Viking, Tiger Global) reproduced the model successfully.", "source": "https://hedgefund.wiki/api/timeline.json#tiger-management-closes", "entity": {"type": "event", "id": "tiger-management-closes"}, "tokens_approx": 179, "tags": ["closure", "value", "tech-bubble", "event"]}
{"id": "event:amaranth-2006", "title": "Amaranth Advisors collapse", "text": "# Amaranth Advisors collapse (2006-09-18)\n\n**Summary:** Brian Hunter's natural gas trade — long winter / short shoulder — moves against him; Amaranth loses $6.6bn in a week (out of $9.2bn AUM), the largest single-fund loss to that date.\n\n**Actors:** Brian Hunter, Nick Maounis\n\n**Mechanism:** Concentrated long winter / short shoulder spread positions in NYMEX natty gas. Position size dwarfed the open interest in those contracts; when prices moved, Amaranth could not exit without crashing the curve.\n\n**Magnitude:** $6.6bn loss\n\n**Lessons:**\n  • Position size relative to market depth is a hard constraint.\n  • Concentrated commodity bets can blow up faster than equities ever could.", "source": "https://hedgefund.wiki/api/timeline.json#amaranth-2006", "entity": {"type": "event", "id": "amaranth-2006"}, "tokens_approx": 171, "tags": ["commodities", "concentration", "blowup", "event"]}
{"id": "event:august-2007-quant-quake", "title": "August 2007 Quant Quake", "text": "# August 2007 Quant Quake (2007-08-08)\n\n**Summary:** Aug 6-10, 2007. Cross-firm deleveraging in equity statistical-arbitrage portfolios produces -10 sigma single-day moves in factor returns. Goldman's GEO and several others draw down 20-30% in days; many recover by month-end.\n\n**Actors:** Goldman Sachs Global Equity Opportunities, Renaissance, AQR, DE Shaw, Highbridge\n\n**Mechanism:** A fund caught in subprime had to liquidate; that liquidation pressured stat-arb factors; factor moves triggered VaR limits at other stat-arb funds; their selling propagated. The first cross-firm 'crowding cascade'.\n\n**Lessons:**\n  • Strategies that are uncorrelated to markets can be highly correlated to each other.\n  • VaR-based risk limits are procyclical: they amplify deleveraging.\n  • Khandani-Lo (2007) seminal paper on the event.", "source": "https://hedgefund.wiki/api/timeline.json#august-2007-quant-quake", "entity": {"type": "event", "id": "august-2007-quant-quake"}, "tokens_approx": 206, "tags": ["quant", "crowding", "deleveraging", "event"]}
{"id": "event:lehman-collapse", "title": "Lehman Brothers bankruptcy", "text": "# Lehman Brothers bankruptcy (2008-09-15)\n\n**Summary:** Lehman files Ch.11 on Sep 15, 2008. Lehman Brothers International (Europe) — the prime broker for hundreds of hedge funds — falls into UK administration. Funds with assets at LBIE find them frozen for years under UK 'Rule 7' insolvency.\n\n**Actors:** Lehman Brothers, PwC (UK administrator), hundreds of hedge funds\n\n**Mechanism:** LBIE used unrestricted client asset rehypothecation under UK rules. When LBIE failed, rehypothecated assets were treated as part of the estate, not segregated client property. ~$70bn+ of hedge fund assets frozen.\n\n**Magnitude:** $70bn+ frozen at LBIE\n\n**Lessons:**\n  • Single-PB risk is unacceptable.\n  • Custody and rehypothecation rules vary materially by jurisdiction.\n  • Multi-PB structure became universal post-2008.", "source": "https://hedgefund.wiki/api/timeline.json#lehman-collapse", "entity": {"type": "event", "id": "lehman-collapse"}, "tokens_approx": 202, "tags": ["systemic", "counterparty", "case-study", "event"]}
{"id": "event:madoff-fraud-revealed", "title": "Madoff Ponzi revealed", "text": "# Madoff Ponzi revealed (2008-12-11)\n\n**Summary:** Bernard L. Madoff Investment Securities, ostensibly a $65bn 'split-strike conversion' fund, is exposed as a Ponzi scheme spanning at least 17 years. ~$17.5bn principal lost; $50bn paper losses.\n\n**Actors:** Bernie Madoff\n\n**Mechanism:** No actual trading; fabricated returns of ~10% with near-zero volatility for years. Self-administered (no independent admin); audited by a 3-person firm. Markopolos warnings ignored by SEC for years.\n\n**Magnitude:** $65bn paper / $17.5bn principal\n\n**Lessons:**\n  • Independent fund administrator is non-negotiable.\n  • Audit by a Big-4 (or recognized) firm is a baseline.\n  • Returns too smooth to be real probably aren't.\n  • Operational due diligence matters as much as investment due diligence.", "source": "https://hedgefund.wiki/api/timeline.json#madoff-fraud-revealed", "entity": {"type": "event", "id": "madoff-fraud-revealed"}, "tokens_approx": 196, "tags": ["fraud", "operational-dd", "event"]}
{"id": "event:flash-crash-2010", "title": "Flash Crash", "text": "# Flash Crash (2010-05-06)\n\n**Summary:** S&P 500 drops ~9% in 36 minutes and recovers most of it. Triggered by a single large E-mini sell program (Waddell & Reed) interacting with HFT liquidity withdrawal.\n\n**Actors:** Waddell & Reed, HFT market makers, Navinder Sarao (later prosecuted for spoofing role)\n\n**Mechanism:** VWAP-targeted sell algo aggressed liquidity faster than HFTs replenished; some HFTs withdrew (stub quotes); cascading hot-potato selling.\n\n**Lessons:**\n  • Algorithmic execution and HFT liquidity create new failure modes.\n  • Limit-up/limit-down (LULD) circuit breakers introduced post-flash crash.", "source": "https://hedgefund.wiki/api/timeline.json#flash-crash-2010", "entity": {"type": "event", "id": "flash-crash-2010"}, "tokens_approx": 155, "tags": ["microstructure", "execution", "event"]}
{"id": "event:knight-2012", "title": "Knight Capital algorithm meltdown", "text": "# Knight Capital algorithm meltdown (2012-08-01)\n\n**Summary:** A botched software deployment at Knight Capital Group causes a runaway algo to send millions of orders in 45 minutes, generating $440m in losses and effectively ending Knight as a standalone firm.\n\n**Actors:** Knight Capital Group\n\n**Mechanism:** Old test code (PowerPeg) inadvertently activated in production by a partial deployment. No effective kill switch.\n\n**Magnitude:** $440m loss\n\n**Lessons:**\n  • Operational risk in algorithmic trading can wipe out a firm in minutes.\n  • Pre-trade risk controls and kill switches are mandatory (SEC Rule 15c3-5).", "source": "https://hedgefund.wiki/api/timeline.json#knight-2012", "entity": {"type": "event", "id": "knight-2012"}, "tokens_approx": 154, "tags": ["operational", "execution", "event"]}
{"id": "event:sac-insider-trading-2013", "title": "SAC Capital insider trading settlement", "text": "# SAC Capital insider trading settlement (2013-11-04)\n\n**Summary:** SAC Capital Advisors agrees to plead guilty to insider trading and pay $1.8bn in fines. The firm converts to family office (Point72) in 2014. Founder Steve Cohen later returns to managing outside capital in 2018.\n\n**Actors:** Steve Cohen, DOJ (Preet Bharara), SEC\n\n**Mechanism:** Multiple SAC PMs (Mathew Martoma, Michael Steinberg) convicted of trading on MNPI obtained from expert networks and corporate insiders.\n\n**Magnitude:** $1.8bn fines\n\n**Lessons:**\n  • Pod platform model concentrates compliance risk at the platform level.\n  • Expert network protocols significantly tightened post-SAC.\n  • Newman/Salman/Blaszczak shaped tipper-tippee liability standards.", "source": "https://hedgefund.wiki/api/timeline.json#sac-insider-trading-2013", "entity": {"type": "event", "id": "sac-insider-trading-2013"}, "tokens_approx": 183, "tags": ["compliance", "insider-trading", "legal", "event"]}
{"id": "event:swiss-franc-shock", "title": "Swiss National Bank removes EUR/CHF floor", "text": "# Swiss National Bank removes EUR/CHF floor (2015-01-15)\n\n**Summary:** SNB unexpectedly drops the 1.20 EUR/CHF floor it had defended since 2011. CHF jumps 30% in minutes. Multiple FX brokers (Alpari UK, FXCM) suffer near-fatal losses; Everest Capital's Global fund liquidates.\n\n**Actors:** Swiss National Bank, FX brokers, Everest Capital\n\n**Magnitude:** Multiple FX broker failures; $830m Everest Capital Global wind-down\n\n**Lessons:**\n  • Central bank guidance is not a guarantee.\n  • Liquidity in 'managed' currencies can vanish instantly when policy shifts.", "source": "https://hedgefund.wiki/api/timeline.json#swiss-franc-shock", "entity": {"type": "event", "id": "swiss-franc-shock"}, "tokens_approx": 140, "tags": ["macro", "fx", "policy", "event"]}
{"id": "event:china-flash-crash-2015", "title": "China devaluation flash crash", "text": "# China devaluation flash crash (2015-08-24)\n\n**Summary:** The PBOC's Aug 11 devaluation triggers a 24-day global selloff culminating in 'Black Monday' Aug 24: -8.5% Shanghai Composite, -5.4% intraday on the SPX with extreme open dislocations on US ETFs.\n\n**Actors:** PBOC\n\n**Mechanism:** Surprise devaluation triggered EM and risk-asset selloff. ETF arbitrageurs widened spreads to 30-40% intraday on the open as APs paused.\n\n**Lessons:**\n  • EM macro shocks transmit to DM equities via cross-asset risk parity and CTA selling.\n  • ETF microstructure breaks at open under stress.", "source": "https://hedgefund.wiki/api/timeline.json#china-flash-crash-2015", "entity": {"type": "event", "id": "china-flash-crash-2015"}, "tokens_approx": 145, "tags": ["macro", "em", "etf", "event"]}
{"id": "event:brexit-referendum", "title": "Brexit referendum", "text": "# Brexit referendum (2016-06-23)\n\n**Summary:** UK votes 52-48 to leave the EU. GBP crashes 8% overnight. Macro funds positioned long GBP/short Euro stocks (the consensus 'Remain' bet) take large losses.\n\n**Actors:** UK electorate, global macro funds\n\n**Lessons:**\n  • Political-event probability pricing by markets had been wrong for 18 months.\n  • Tail-risk hedging via OTM puts proved its value for the few who maintained it.", "source": "https://hedgefund.wiki/api/timeline.json#brexit-referendum", "entity": {"type": "event", "id": "brexit-referendum"}, "tokens_approx": 106, "tags": ["macro", "political", "event"]}
{"id": "event:volmageddon-2018", "title": "Volmageddon (XIV blowup)", "text": "# Volmageddon (XIV blowup) (2018-02-05)\n\n**Summary:** VIX spikes from ~17 to 38 intraday; XIV (Credit Suisse short-VIX ETN) loses 96% in a day, triggering acceleration. ~$3bn of short-vol ETPs unwound; Credit Suisse retires XIV.\n\n**Actors:** Credit Suisse, ProShares, XIV holders\n\n**Mechanism:** Short-vol ETPs were end-of-day rebalancing — a vol spike forces buying VIX futures, which lifts the futures further, which forces more buying. Procyclical feedback.\n\n**Magnitude:** $3bn+ short-vol ETP unwinds\n\n**Lessons:**\n  • Procyclical leveraged ETPs in vol products are uniquely fragile.\n  • Short-vol carry strategies need explicit drawdown rules.", "source": "https://hedgefund.wiki/api/timeline.json#volmageddon-2018", "entity": {"type": "event", "id": "volmageddon-2018"}, "tokens_approx": 162, "tags": ["vol", "etp", "procyclical", "event"]}
{"id": "event:march-2020-dash-for-cash", "title": "March 2020 'Dash for Cash'", "text": "# March 2020 'Dash for Cash' (2020-03-12)\n\n**Summary:** COVID lockdown announcements trigger universal cross-asset selling. Treasuries — supposedly the safe haven — sell off as relative-value funds unwind basis trades. The Fed launches unlimited QE on Mar 23 to restore Treasury liquidity.\n\n**Actors:** Federal Reserve, Treasury rates RV funds (Citadel, Millennium, ExodusPoint), global investors\n\n**Mechanism:** Margin calls forced unwinds of leveraged Treasury basis trades; demand for cash collateral overwhelmed Treasury market liquidity; Fed had to backstop functioning of the most liquid market on earth.\n\n**Magnitude:** $2.3tn+ Fed asset purchases\n\n**Lessons:**\n  • Even Treasuries can become illiquid in a true crisis.\n  • Leveraged basis trades create systemic vulnerabilities flagged ever since.\n  • SEC pursuing UST cash and repo central clearing in part because of this episode.", "source": "https://hedgefund.wiki/api/timeline.json#march-2020-dash-for-cash", "entity": {"type": "event", "id": "march-2020-dash-for-cash"}, "tokens_approx": 222, "tags": ["systemic", "rates", "liquidity", "event"]}
{"id": "event:wirecard-collapse", "title": "Wirecard collapse — short squeeze validated", "text": "# Wirecard collapse — short squeeze validated (2020-06-18)\n\n**Summary:** German payments processor Wirecard admits €1.9bn cash 'missing'. Short sellers (Fahmi Quadir, Muddy Waters, FT's Dan McCrum) vindicated after years of accusations. BaFin had banned shorts and investigated journalists rather than the company.\n\n**Actors:** Wirecard, Fahmi Quadir (Safkhet), Muddy Waters, FT\n\n**Lessons:**\n  • Activist short sellers can identify fraud regulators miss.\n  • Banning short selling protects bad actors, not investors.\n  • BaFin restructured post-Wirecard.", "source": "https://hedgefund.wiki/api/timeline.json#wirecard-collapse", "entity": {"type": "event", "id": "wirecard-collapse"}, "tokens_approx": 138, "tags": ["short-selling", "fraud", "germany", "event"]}
{"id": "event:gamestop-squeeze", "title": "GameStop short squeeze", "text": "# GameStop short squeeze (2021-01-28)\n\n**Summary:** Retail-driven squeeze on GME (and AMC, BBBY, others) sends GME from $20 to $483. Melvin Capital loses ~$7bn (53% of fund) and ultimately closes in 2022. Citadel and Point72 inject $2.75bn into Melvin to stabilize; Robinhood restricts buying triggering Congressional hearings.\n\n**Actors:** WSB / r/wallstreetbets, Melvin Capital, Citadel, Robinhood, Point72\n\n**Mechanism:** Coordinated retail buying + heavy GME short interest (~140% of float) triggered short covering and gamma squeeze (dealer hedging of OTM call buying).\n\n**Lessons:**\n  • Crowded shorts in low-float names are a recurring vulnerability.\n  • Retail aggregation via social platforms is a new and persistent market force.\n  • Position-level transparency (13F lag) is a vulnerability for short positioning.", "source": "https://hedgefund.wiki/api/timeline.json#gamestop-squeeze", "entity": {"type": "event", "id": "gamestop-squeeze"}, "tokens_approx": 205, "tags": ["short-squeeze", "retail", "social", "event"]}
{"id": "event:archegos-2021", "title": "Archegos Capital Management collapse", "text": "# Archegos Capital Management collapse (2021-03-26)\n\n**Summary:** Bill Hwang's family office Archegos defaults on margin calls. Forced unwinds of total return swap positions in ViacomCBS, Discovery, GSX, and others cause ~$30bn in dealer block trades. Credit Suisse loses $5.5bn, Nomura $2.9bn, Morgan Stanley $1bn.\n\n**Actors:** Bill Hwang, Credit Suisse, Nomura, Goldman, Morgan Stanley, UBS\n\n**Mechanism:** Highly concentrated long positions held via TRS at multiple PBs (each unaware of total exposure). Effective leverage ~5x. Position drawdowns triggered margin calls; Hwang refused to meet; PBs unwound.\n\n**Magnitude:** $10bn+ dealer losses; ~$160bn notional unwound\n\n**Lessons:**\n  • Total return swaps escape 13D disclosure — the SEC has since proposed Rule 10B-1 to require beneficial ownership disclosure of large swaps.\n  • Family offices are not exempt from systemic risk.\n  • Credit Suisse's prime brokerage failed risk management — contributed to CS's eventual demise.\n  • Hwang was convicted on multiple counts in 2024.", "source": "https://hedgefund.wiki/api/timeline.json#archegos-2021", "entity": {"type": "event", "id": "archegos-2021"}, "tokens_approx": 258, "tags": ["counterparty", "swap", "family-office", "event"]}
{"id": "event:russia-invades-ukraine", "title": "Russia invades Ukraine — commodity supershock", "text": "# Russia invades Ukraine — commodity supershock (2022-02-24)\n\n**Summary:** Russian invasion of Ukraine triggers commodity supershock. Brent +35%, EU gas +400%, wheat +40%. LME nickel short squeeze (Mar 7-8) forces LME to cancel trades. CTAs and macro funds capture historic gains.\n\n**Actors:** Russia, Ukraine, LME, Tsingshan (nickel short), JPMorgan (Tsingshan PB)\n\n**Magnitude:** Multi-billion CTA gains; LME's reputational damage from canceling nickel trades\n\n**Lessons:**\n  • Commodity tail risk had been underpriced through 15 years of QE-suppressed vol.\n  • Trend-following CTAs delivered crisis alpha (+27% SG Trend Index 2022).\n  • Exchange intervention to cancel trades creates legal precedent and damages confidence.", "source": "https://hedgefund.wiki/api/timeline.json#russia-invades-ukraine", "entity": {"type": "event", "id": "russia-invades-ukraine"}, "tokens_approx": 181, "tags": ["macro", "commodities", "geopolitical", "event"]}
{"id": "event:2022-yield-curve-inversion", "title": "Deepest US yield curve inversion in 40 years", "text": "# Deepest US yield curve inversion in 40 years (2022-07-05)\n\n**Summary:** 2s10s inverts and reaches -108bp by mid-2023 — deepest since 1981. Recession does not arrive on cue. Macro funds positioned for recession underperform; soft landing playbook wins out 2023-2024.\n\n**Actors:** Federal Reserve, global macro funds\n\n**Lessons:**\n  • Inversion has a ~12-24 month lead time but not an automatic recession trigger.\n  • Fiscal dominance and post-pandemic balance sheet dynamics broke historical patterns.", "source": "https://hedgefund.wiki/api/timeline.json#2022-yield-curve-inversion", "entity": {"type": "event", "id": "2022-yield-curve-inversion"}, "tokens_approx": 125, "tags": ["macro", "rates", "recession-indicator", "event"]}
{"id": "event:uk-gilts-ldi-crisis", "title": "UK gilt / LDI crisis", "text": "# UK gilt / LDI crisis (2022-09-28)\n\n**Summary:** Truss-Kwarteng mini-budget triggers gilt selloff that nearly destroys UK pension LDI strategies. BoE intervenes with bond buying to break the doom loop. Margin calls on LDI swaps forced gilt sales which deepened the selloff.\n\n**Actors:** UK Truss government, BoE, UK DB pension schemes, LDI managers (BlackRock, Insight, LGIM, Schroders)\n\n**Magnitude:** £1trn+ LDI assets at risk; BoE £65bn purchase facility\n\n**Lessons:**\n  • Levered duration overlays in pensions create systemic transmission paths.\n  • Procyclical margining can destabilize the asset central bankers thought safest.\n  • Liability-driven investing requires liquidity planning that LDI managers had inadequately stress-tested.", "source": "https://hedgefund.wiki/api/timeline.json#uk-gilts-ldi-crisis", "entity": {"type": "event", "id": "uk-gilts-ldi-crisis"}, "tokens_approx": 185, "tags": ["systemic", "rates", "uk", "pension", "event"]}
{"id": "event:ftx-collapse-2022", "title": "FTX collapse", "text": "# FTX collapse (2022-11-11)\n\n**Summary:** Crypto exchange FTX files Chapter 11. ~$8bn customer fund shortfall; Sam Bankman-Fried convicted on 7 counts in 2023, sentenced to 25 years. Multiple crypto hedge funds (Three Arrows, Voyager, Genesis Trading) directly or indirectly destroyed.\n\n**Actors:** Sam Bankman-Fried, Alameda Research, FTX customers\n\n**Mechanism:** Alameda misappropriation of FTX customer funds; CoinDesk reporting on Alameda balance sheet triggered Binance withdrawal threat → bank run → insolvency.\n\n**Magnitude:** $8bn customer shortfall\n\n**Lessons:**\n  • Exchange counterparty risk in crypto is a first-order concern; segregated custody is non-negotiable.\n  • Self-custody and proof-of-reserves became baseline asks post-FTX.\n  • Adjacent failures: Three Arrows ($10bn), Voyager, Celsius, BlockFi, Genesis.", "source": "https://hedgefund.wiki/api/timeline.json#ftx-collapse-2022", "entity": {"type": "event", "id": "ftx-collapse-2022"}, "tokens_approx": 207, "tags": ["crypto", "fraud", "counterparty", "event"]}
{"id": "event:three-arrows-2022", "title": "Three Arrows Capital liquidation", "text": "# Three Arrows Capital liquidation (2022-06-29)\n\n**Summary:** Singapore-based 3AC enters liquidation after ~$10bn in losses tied to Luna/UST collapse, GBTC discount, and high leverage. Su Zhu and Kyle Davies disappear; subsequent contempt orders ensue.\n\n**Actors:** Three Arrows Capital, Su Zhu, Kyle Davies, Voyager, Genesis, BlockFi\n\n**Magnitude:** $10bn+\n\n**Lessons:**\n  • Crypto credit was uncollateralized and undisclosed — counterparties assumed others had checked.\n  • Reputational lending without verifiable financials was a feature of late-cycle crypto credit.", "source": "https://hedgefund.wiki/api/timeline.json#three-arrows-2022", "entity": {"type": "event", "id": "three-arrows-2022"}, "tokens_approx": 142, "tags": ["crypto", "credit", "counterparty", "event"]}
{"id": "event:svb-collapse-2023", "title": "Silicon Valley Bank failure", "text": "# Silicon Valley Bank failure (2023-03-10)\n\n**Summary:** SVB closed by California regulators after a $42bn deposit run in 24 hours. Held to maturity Treasuries had ~$15bn in unrealized losses. Depositors made whole via systemic risk exception. Signature, First Republic follow.\n\n**Actors:** SVB, FDIC, Federal Reserve, Treasury\n\n**Mechanism:** Duration mismatch (long duration HTM) + concentrated tech depositor base + viral social-media-driven run.\n\n**Magnitude:** $209bn SVB assets; ~$25bn FDIC fund cost across 2023 bank failures\n\n**Lessons:**\n  • AOCI on AFS securities was not in regulatory capital — masked losses.\n  • Interest rate risk had been underweighted in bank stress testing.\n  • Concentrated depositor bases and digital banking enable run velocities never seen before.\n  • Hedge funds shorting regional banks materially benefited; some notable wins.", "source": "https://hedgefund.wiki/api/timeline.json#svb-collapse-2023", "entity": {"type": "event", "id": "svb-collapse-2023"}, "tokens_approx": 216, "tags": ["banking", "rates", "concentration", "event"]}
{"id": "event:credit-suisse-acquired", "title": "UBS forced to acquire Credit Suisse", "text": "# UBS forced to acquire Credit Suisse (2023-03-19)\n\n**Summary:** Following Archegos, Greensill, and a deposit run, Credit Suisse is acquired by UBS in a Swiss government-orchestrated deal. AT1 bondholders wiped out (writedown ahead of equity), creating a notable AT1 market dislocation that hedge fund credit funds traded around.\n\n**Actors:** Credit Suisse, UBS, Swiss FINMA, SNB, Swiss government\n\n**Magnitude:** $17bn AT1 wipeout; CHF 9bn UBS purchase price\n\n**Lessons:**\n  • AT1 instruments behaved per their contracts — but global AT1 issuance briefly froze.\n  • Bank failures can cascade across continents in days.\n  • Prime brokerage market further consolidated; Goldman, Morgan Stanley, and JPM gained share.", "source": "https://hedgefund.wiki/api/timeline.json#credit-suisse-acquired", "entity": {"type": "event", "id": "credit-suisse-acquired"}, "tokens_approx": 178, "tags": ["banking", "credit", "at1", "event"]}
{"id": "event:yen-carry-unwind-2024", "title": "August 2024 Yen carry unwind", "text": "# August 2024 Yen carry unwind (2024-08-05)\n\n**Summary:** BoJ rate hike + weak US payrolls triggers violent yen carry unwind. Nikkei -12.4% (worst day since 1987). VIX spikes from 16 to 65 intraday. Multi-strat pods take outsize losses on cross-asset deleveraging.\n\n**Actors:** Bank of Japan, yen carry traders, multi-strat platforms\n\n**Lessons:**\n  • Cross-asset crowding creates global transmission of single-country rate decisions.\n  • Pod platform positions converged enough that several pods drew down 5-8% in a day.", "source": "https://hedgefund.wiki/api/timeline.json#yen-carry-unwind-2024", "entity": {"type": "event", "id": "yen-carry-unwind-2024"}, "tokens_approx": 130, "tags": ["macro", "fx", "carry", "deleveraging", "event"]}
{"id": "event:sec-private-fund-rules-vacated", "title": "Fifth Circuit vacates SEC Private Fund Adviser Rules", "text": "# Fifth Circuit vacates SEC Private Fund Adviser Rules (2024-06-05)\n\n**Summary:** US Fifth Circuit Court of Appeals vacates the SEC's August 2023 Private Fund Adviser Rules in entirety, ruling the SEC exceeded statutory authority. The decision unwinds quarterly statements, side-letter MFN restrictions, and fee/expense disclosure mandates that the industry had been preparing for.\n\n**Actors:** SEC, MFA, AIMA, NVCA, MFA, plaintiffs, 5th Circuit\n\n**Lessons:**\n  • SEC regulatory expansion via the Advisers Act faces meaningful judicial limits post-Loper Bright.\n  • Industry resources spent on compliance preparation were partly stranded.", "source": "https://hedgefund.wiki/api/timeline.json#sec-private-fund-rules-vacated", "entity": {"type": "event", "id": "sec-private-fund-rules-vacated"}, "tokens_approx": 159, "tags": ["regulation", "legal", "event"]}
{"id": "event:us-treasury-clearing-mandate", "title": "SEC US Treasury Clearing Mandate effective dates", "text": "# SEC US Treasury Clearing Mandate effective dates (2025-12-31)\n\n**Summary:** Mandate phases in: cash UST clearing by Dec 31, 2025; UST repo clearing by Jun 30, 2026 (subsequently extended). Materially changes the economics of the Treasury basis trade by adding clearing margin on the repo leg.\n\n**Actors:** SEC, FICC (DTCC), hedge funds running UST basis\n\n**Lessons:**\n  • Regulatory changes can compress strategy capacity by 20-40%.\n  • The basis trade may bifurcate between bank-balance-sheet and hedge-fund-balance-sheet players.", "source": "https://hedgefund.wiki/api/timeline.json#us-treasury-clearing-mandate", "entity": {"type": "event", "id": "us-treasury-clearing-mandate"}, "tokens_approx": 133, "tags": ["regulation", "rates", "structural", "event"]}
{"id": "event:renaissance-medallion-track", "title": "Renaissance Medallion turns 35 with 39% net annualized", "text": "# Renaissance Medallion turns 35 with 39% net annualized (2024-12-31)\n\n**Summary:** Renaissance's Medallion Fund (closed to outside investors since 1993) reportedly compounds at ~39% net annualized over 35 years — the longest sustained outperformance in hedge fund history. Outside-investor funds (RIDA, RIEF, RIDGE) have lagged dramatically.\n\n**Actors:** Renaissance Technologies, Jim Simons (1938-2024)\n\n**Lessons:**\n  • Capacity is the binding constraint on the highest-Sharpe strategies.\n  • Edge identified, sized correctly, and never shared has produced the only true compounding machine in the industry.", "source": "https://hedgefund.wiki/api/timeline.json#renaissance-medallion-track", "entity": {"type": "event", "id": "renaissance-medallion-track"}, "tokens_approx": 152, "tags": ["track-record", "quant", "capacity", "event"]}
{"id": "event:tiger-asia-2012", "title": "Tiger Asia insider trading guilty plea", "text": "# Tiger Asia insider trading guilty plea (2012-12-12)\n\n**Summary:** Bill Hwang's Tiger Asia pleads guilty to insider trading in Chinese bank stocks; pays $44m. Closes the fund and converts to family office Archegos — setting up the 2021 collapse.\n\n**Actors:** Bill Hwang, Tiger Asia, DOJ\n\n**Lessons:**\n  • The SAC enforcement era saw multiple Tiger-lineage funds caught up in MNPI cases.\n  • Conversion to family office was a regulatory escape hatch — Archegos showed why that escape had downsides.", "source": "https://hedgefund.wiki/api/timeline.json#tiger-asia-2012", "entity": {"type": "event", "id": "tiger-asia-2012"}, "tokens_approx": 124, "tags": ["compliance", "insider-trading", "asia", "event"]}
{"id": "event:weil-gotshal-clearwire-2013", "title": "Clearwire merger arb retrade", "text": "# Clearwire merger arb retrade (2013-06-25)\n\n**Summary:** Sprint's bid for Clearwire faces a competing Dish offer. Sprint raises bid from $2.97 → $5.00. Merger arbs caught short-Sprint / long-Clearwire suffer the worst topping bid in years.\n\n**Actors:** Sprint, Dish Network, Clearwire, merger arb funds\n\n**Lessons:**\n  • Hostile interloper risk is asymmetric — bumps cost shorts, breaks cost longs.", "source": "https://hedgefund.wiki/api/timeline.json#weil-gotshal-clearwire-2013", "entity": {"type": "event", "id": "weil-gotshal-clearwire-2013"}, "tokens_approx": 99, "tags": ["merger-arb", "case-study", "event"]}
{"id": "category:accounting-valuation", "title": "Accounting & Valuation", "text": "# Accounting & Valuation (Category)\n\nHow fund assets, liabilities, and performance are measured. NAV calculation, fair value hierarchy, side-pocket accounting, and Level 1/2/3 marks.\n\n**Key terms:** nav, high-water-mark, level-3-asset, fair-value, side-pocket, crystallisation, accrual-fee", "source": "https://hedgefund.wiki/api/categories.json#accounting-valuation", "entity": {"type": "category", "id": "accounting-valuation"}, "tokens_approx": 72, "tags": ["taxonomy"]}
{"id": "category:alternative-investments", "title": "Alternative Investments", "text": "# Alternative Investments (Category)\n\nAsset classes outside long-only equity and bonds: private equity, real assets, infrastructure, art, litigation finance, and other illiquid plays.\n\n**Key terms:** private-equity, j-curve, co-investment, illiquidity-premium", "source": "https://hedgefund.wiki/api/categories.json#alternative-investments", "entity": {"type": "category", "id": "alternative-investments"}, "tokens_approx": 64, "tags": ["taxonomy"]}
{"id": "category:behavioral-finance", "title": "Behavioral Finance", "text": "# Behavioral Finance (Category)\n\nCognitive and emotional biases that drive market inefficiencies and create both opportunities and traps for hedge funds.\n\n**Key terms:** herding, anchoring, loss-aversion, overconfidence-bias, narrative-fallacy", "source": "https://hedgefund.wiki/api/categories.json#behavioral-finance", "entity": {"type": "category", "id": "behavioral-finance"}, "tokens_approx": 60, "tags": ["taxonomy"]}
{"id": "category:commodities-futures", "title": "Commodities & Futures", "text": "# Commodities & Futures (Category)\n\nPhysical and financial commodity markets, futures curves, basis, roll yield, and the mechanics of CTA trading.\n\n**Key terms:** contango, backwardation, roll-yield, basis, term-structure", "source": "https://hedgefund.wiki/api/categories.json#commodities-futures", "entity": {"type": "category", "id": "commodities-futures"}, "tokens_approx": 55, "tags": ["taxonomy"]}
{"id": "category:crypto-digital-assets", "title": "Crypto & Digital Assets", "text": "# Crypto & Digital Assets (Category)\n\nHedge fund engagement with crypto: spot, perps, basis trades, market-making, MEV, validator yield, and tokenized funds.\n\n**Key terms:** basis-trade, perpetual-futures, funding-rate, mev, tokenized-fund", "source": "https://hedgefund.wiki/api/categories.json#crypto-digital-assets", "entity": {"type": "category", "id": "crypto-digital-assets"}, "tokens_approx": 59, "tags": ["taxonomy"]}
{"id": "category:derivatives-options", "title": "Derivatives & Options", "text": "# Derivatives & Options (Category)\n\nForwards, futures, swaps, and the option Greeks. Pricing models, vol surface dynamics, and structured products.\n\n**Key terms:** delta, gamma, vega, theta, rho, implied-volatility, skew, black-scholes", "source": "https://hedgefund.wiki/api/categories.json#derivatives-options", "entity": {"type": "category", "id": "derivatives-options"}, "tokens_approx": 58, "tags": ["taxonomy"]}
{"id": "category:esg-sustainable", "title": "ESG & Sustainable Investing", "text": "# ESG & Sustainable Investing (Category)\n\nEnvironmental, social, and governance overlays in hedge fund mandates: SFDR Article 8/9, climate VaR, transition risk.\n\n**Key terms:** sfdr, climate-var, transition-risk, scope-3-emissions", "source": "https://hedgefund.wiki/api/categories.json#esg-sustainable", "entity": {"type": "category", "id": "esg-sustainable"}, "tokens_approx": 57, "tags": ["taxonomy"]}
{"id": "category:equities-analysis", "title": "Equities & Analysis", "text": "# Equities & Analysis (Category)\n\nSingle-name equity analysis: financial statements, valuation multiples, quality screens, primary research.\n\n**Key terms:** ev-ebitda, free-cash-flow-yield, roic, primary-research, channel-checks", "source": "https://hedgefund.wiki/api/categories.json#equities-analysis", "entity": {"type": "category", "id": "equities-analysis"}, "tokens_approx": 57, "tags": ["taxonomy"]}
{"id": "category:fixed-income-credit", "title": "Fixed Income & Credit", "text": "# Fixed Income & Credit (Category)\n\nGovernment, corporate, and structured credit markets. Yield curves, duration, OAS, default modeling, distressed debt.\n\n**Key terms:** duration, convexity, oas, credit-default-swap, distressed-debt", "source": "https://hedgefund.wiki/api/categories.json#fixed-income-credit", "entity": {"type": "category", "id": "fixed-income-credit"}, "tokens_approx": 58, "tags": ["taxonomy"]}
{"id": "category:fund-operations", "title": "Fund Operations & Structure", "text": "# Fund Operations & Structure (Category)\n\nLegal entity setup, investor docs, prime broker relationships, fund admin, and the full ops stack.\n\n**Key terms:** master-feeder, side-pocket, gate, lock-up, high-water-mark, prime-broker, administrator", "source": "https://hedgefund.wiki/api/categories.json#fund-operations", "entity": {"type": "category", "id": "fund-operations"}, "tokens_approx": 61, "tags": ["taxonomy"]}
{"id": "category:global-markets", "title": "Global Markets", "text": "# Global Markets (Category)\n\nCross-border markets, FX, EM debt and equity, sovereign analysis, and global rates.\n\n**Key terms:** carry-trade, covered-interest-parity, em-debt, sovereign-cds", "source": "https://hedgefund.wiki/api/categories.json#global-markets", "entity": {"type": "category", "id": "global-markets"}, "tokens_approx": 47, "tags": ["taxonomy"]}
{"id": "category:hedge-fund-strategies", "title": "Hedge Fund Strategies", "text": "# Hedge Fund Strategies (Category)\n\nThe strategy taxonomy: equity hedge, event-driven, global macro, relative value, managed futures, multi-strategy.\n\n**Key terms:** long-short-equity, merger-arbitrage, global-macro, convertible-arbitrage, multi-strategy-pod", "source": "https://hedgefund.wiki/api/categories.json#hedge-fund-strategies", "entity": {"type": "category", "id": "hedge-fund-strategies"}, "tokens_approx": 64, "tags": ["taxonomy"]}
{"id": "category:insurance-reinsurance", "title": "Insurance & Reinsurance", "text": "# Insurance & Reinsurance (Category)\n\nReinsurance sidecars, ILS, cat bonds, and the convergence of hedge fund capital with re/insurance balance sheets.\n\n**Key terms:** cat-bond, ils, sidecar, reinsurer-collateralized", "source": "https://hedgefund.wiki/api/categories.json#insurance-reinsurance", "entity": {"type": "category", "id": "insurance-reinsurance"}, "tokens_approx": 54, "tags": ["taxonomy"]}
{"id": "category:macroeconomics", "title": "Macroeconomics", "text": "# Macroeconomics (Category)\n\nThe macro backdrop: monetary policy, fiscal cycles, trade balances, and how regimes shift.\n\n**Key terms:** yield-curve-inversion, monetary-policy, neutral-rate, fiscal-dominance", "source": "https://hedgefund.wiki/api/categories.json#macroeconomics", "entity": {"type": "category", "id": "macroeconomics"}, "tokens_approx": 51, "tags": ["taxonomy"]}
{"id": "category:market-microstructure", "title": "Market Microstructure", "text": "# Market Microstructure (Category)\n\nHow orders meet at the exchange: order book dynamics, latency, adverse selection, market making, dark pools.\n\n**Key terms:** bid-ask-spread, adverse-selection, kyle-lambda, vpin, iceberg-order", "source": "https://hedgefund.wiki/api/categories.json#market-microstructure", "entity": {"type": "category", "id": "market-microstructure"}, "tokens_approx": 57, "tags": ["taxonomy"]}
{"id": "category:portfolio-construction", "title": "Portfolio Construction", "text": "# Portfolio Construction (Category)\n\nTranslating signals into positions: optimization, risk budgeting, factor exposures, and capital allocation.\n\n**Key terms:** mean-variance-optimization, risk-parity, kelly-criterion, factor-tilt", "source": "https://hedgefund.wiki/api/categories.json#portfolio-construction", "entity": {"type": "category", "id": "portfolio-construction"}, "tokens_approx": 57, "tags": ["taxonomy"]}
{"id": "category:quantitative-methods", "title": "Quantitative Methods", "text": "# Quantitative Methods (Category)\n\nStats, ML, time series, and the engineering of systematic alpha.\n\n**Key terms:** alpha, beta, sharpe-ratio, sortino-ratio, information-ratio, cointegration, kalman-filter", "source": "https://hedgefund.wiki/api/categories.json#quantitative-methods", "entity": {"type": "category", "id": "quantitative-methods"}, "tokens_approx": 51, "tags": ["taxonomy"]}
{"id": "category:regulatory-compliance", "title": "Regulatory & Compliance", "text": "# Regulatory & Compliance (Category)\n\nForm ADV, AIFMD, MiFID II, Dodd-Frank, side letters, MNPI, expert networks, and the compliance lifecycle.\n\n**Key terms:** form-adv, aifmd, mifid-ii, regulation-d, expert-network, mnpi", "source": "https://hedgefund.wiki/api/categories.json#regulatory-compliance", "entity": {"type": "category", "id": "regulatory-compliance"}, "tokens_approx": 55, "tags": ["taxonomy"]}
{"id": "category:risk-management", "title": "Risk Management", "text": "# Risk Management (Category)\n\nVaR families, expected shortfall, stress testing, scenario analysis, drawdown control, and counterparty risk.\n\n**Key terms:** value-at-risk, expected-shortfall, max-drawdown, stress-test, counterparty-risk", "source": "https://hedgefund.wiki/api/categories.json#risk-management", "entity": {"type": "category", "id": "risk-management"}, "tokens_approx": 58, "tags": ["taxonomy"]}
{"id": "category:trading-execution", "title": "Trading & Execution", "text": "# Trading & Execution (Category)\n\nImplementation shortfall, TCA, algo wheels, smart order routing, dark vs lit, and the execution alpha frontier.\n\n**Key terms:** implementation-shortfall, vwap, twap, algo-wheel, tca, dark-pool", "source": "https://hedgefund.wiki/api/categories.json#trading-execution", "entity": {"type": "category", "id": "trading-execution"}, "tokens_approx": 56, "tags": ["taxonomy"]}
{"id": "calculator:sharpe-ratio-calc", "title": "Sharpe Ratio", "text": "# Sharpe Ratio (Calculator)\n\n**Summary:** Annualized Sharpe from a return series.\n\n**Formula reference:** sharpe-ratio\n\n**Inputs:** returns(array<number>); rf_periodic(number); periods_per_year(integer)\n\n**Outputs:** sharpe(number); mean_excess(number); std(number)\n\n**Reference impl (javascript):**\n```\nfunction sharpeRatio(returns, rfPeriodic = 0, periodsPerYear = 252) {\n  const ex = returns.map(r => r - rfPeriodic);\n  const mean = ex.reduce((a, b) => a + b, 0) / ex.length;\n  const variance = ex.reduce((s, r) => s + (r - mean) ** 2, 0) / (ex.length - 1);\n  const std = Math.sqrt(variance);\n  const sharpe = (mean / std) * Math.sqrt(periodsPerYear);\n  return { sharpe, mean_excess: mean, std };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#sharpe-ratio-calc", "entity": {"type": "calculator", "id": "sharpe-ratio-calc"}, "tokens_approx": 176, "tags": ["calculator"]}
{"id": "calculator:sortino-ratio-calc", "title": "Sortino Ratio", "text": "# Sortino Ratio (Calculator)\n\n**Summary:** Sortino Ratio\n\n**Formula reference:** sortino-ratio\n\n**Inputs:** returns(array<number>); target(number); periods_per_year(integer)\n\n**Outputs:** sortino(number)\n\n**Reference impl (javascript):**\n```\nfunction sortinoRatio(returns, target = 0, periodsPerYear = 252) {\n  const ex = returns.map(r => r - target);\n  const mean = ex.reduce((a,b) => a + b, 0) / ex.length;\n  const downside = ex.filter(r => r < 0);\n  const dd = Math.sqrt(downside.reduce((s, r) => s + r * r, 0) / ex.length);\n  return { sortino: (mean / dd) * Math.sqrt(periodsPerYear) };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#sortino-ratio-calc", "entity": {"type": "calculator", "id": "sortino-ratio-calc"}, "tokens_approx": 149, "tags": ["calculator"]}
{"id": "calculator:max-drawdown-calc", "title": "Maximum Drawdown", "text": "# Maximum Drawdown (Calculator)\n\n**Summary:** Maximum Drawdown\n\n**Formula reference:** max-drawdown\n\n**Inputs:** nav_series(array<number>)\n\n**Outputs:** mdd(number); peak_index(integer); trough_index(integer); duration(integer)\n\n**Reference impl (javascript):**\n```\nfunction maxDrawdown(nav) {\n  let peak = nav[0], peakIdx = 0, mdd = 0, troughIdx = 0;\n  for (let i = 1; i < nav.length; i++) {\n    if (nav[i] > peak) { peak = nav[i]; peakIdx = i; }\n    const dd = (nav[i] - peak) / peak;\n    if (dd < mdd) { mdd = dd; troughIdx = i; }\n  }\n  return { mdd, peak_index: peakIdx, trough_index: troughIdx, duration: troughIdx - peakIdx };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#max-drawdown-calc", "entity": {"type": "calculator", "id": "max-drawdown-calc"}, "tokens_approx": 159, "tags": ["calculator"]}
{"id": "calculator:calmar-ratio-calc", "title": "Calmar Ratio", "text": "# Calmar Ratio (Calculator)\n\n**Summary:** Calmar Ratio\n\n**Formula reference:** calmar-ratio\n\n**Inputs:** annualized_return(number); max_drawdown(number)\n\n**Outputs:** calmar(number)\n\n**Reference impl (javascript):**\n```\nfunction calmar(annRet, mdd) { return { calmar: annRet / Math.abs(mdd) }; }\n```", "source": "https://hedgefund.wiki/api/calculators.json#calmar-ratio-calc", "entity": {"type": "calculator", "id": "calmar-ratio-calc"}, "tokens_approx": 74, "tags": ["calculator"]}
{"id": "calculator:var-parametric-calc", "title": "Parametric VaR", "text": "# Parametric VaR (Calculator)\n\n**Summary:** Parametric VaR\n\n**Formula reference:** parametric-var\n\n**Inputs:** portfolio_value(currency); sigma_periodic(number); horizon_periods(number); confidence(number)\n\n**Outputs:** var_usd(currency)\n\n**Reference impl (javascript):**\n```\nfunction inverseNormal(p) {\n  // Beasley-Springer-Moro approximation\n  const a = [-3.969683028665376e+01, 2.209460984245205e+02, -2.759285104469687e+02, 1.383577518672690e+02, -3.066479806614716e+01, 2.506628277459239e+00];\n  const b = [-5.447609879822406e+01, 1.615858368580409e+02, -1.556989798598866e+02, 6.680131188771972e+01, -1.328068155288572e+01];\n  const c = [-7.784894002430293e-03, -3.223964580411365e-01, -2.400758277161838e+00, -2.549732539343734e+00, 4.374664141464968e+00, 2.938163982698783e+00];\n  const d = [7.784695709041462e-03, 3.224671290700398e-01, 2.445134137142996e+00, 3.754408661907416e+00];\n  const pl = 0.02425, ph = 1 - pl;\n  let q, r;\n  if (p < pl) { q = Math.sqrt(-2*Math.log(p)); return (((((c[0]*q+c[1])*q+c[2])*q+c[3])*q+c[4])*q+c[5]) / ((((d[0]*q+d[1])*q+d[2])*q+d[3])*q+1); }\n  if (p <= ph) { q = p - 0.5; r = q*q; return (((((a[0]*r+a[1])*r+a[2])*r+a[3])*r+a[4])*r+a[5])*q / (((((b[0]*r+b[1])*r+b[2])*r+b[3])*r+b[4])*r+1); }\n  q = Math.sqrt(-2*Math.log(1-p));\n  return -(((((c[0]*q+c[1])*q+c[2])*q+c[3])*q+c[4])*q+c[5]) / ((((d[0]*q+d[1])*q+d[2])*q+d[3])*q+1);\n}\nfunction parametricVaR(value, sigma, horizon = 1, conf = 0.99) {\n  const z = inverseNormal(conf);\n  const v = value * sigma * Math.sqrt(horizon) * z;\n  return { var_usd: v };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#var-parametric-calc", "entity": {"type": "calculator", "id": "var-parametric-calc"}, "tokens_approx": 389, "tags": ["calculator"]}
{"id": "calculator:kelly-fraction-calc", "title": "Kelly Fraction", "text": "# Kelly Fraction (Calculator)\n\n**Summary:** Kelly Fraction\n\n**Formula reference:** kelly-criterion\n\n**Inputs:** expected_return(number); risk_free(number); variance(number); fraction(number)\n\n**Outputs:** leverage(number)\n\n**Reference impl (javascript):**\n```\nfunction kelly(mu, rf, variance, fraction = 1) { return { leverage: fraction * (mu - rf) / variance }; }\n```", "source": "https://hedgefund.wiki/api/calculators.json#kelly-fraction-calc", "entity": {"type": "calculator", "id": "kelly-fraction-calc"}, "tokens_approx": 92, "tags": ["calculator"]}
{"id": "calculator:performance-fee-calc", "title": "Performance Fee with HWM and Hurdle", "text": "# Performance Fee with HWM and Hurdle (Calculator)\n\n**Summary:** Computes performance fee given prior HWM, current NAV, hurdle, and rate.\n\n**Formula reference:** sharpe-ratio\n\n**Inputs:** starting_nav(number); ending_nav_pre_fee(number); high_water_mark(number); hurdle_rate(percent); performance_fee_rate(percent); hurdle_type(string)\n\n**Outputs:** performance_fee_per_share(number); ending_nav_post_fee(number); new_high_water_mark(number)\n\n**Reference impl (javascript):**\n```\nfunction performanceFee(start, endPre, hwm, hurdle = 0, rate = 0.2, type = 'hard') {\n  const hurdleNav = Math.max(hwm, start) * (1 + hurdle);\n  const above = endPre - hurdleNav;\n  if (above <= 0) return { performance_fee_per_share: 0, ending_nav_post_fee: endPre, new_high_water_mark: Math.max(endPre, hwm) };\n  let fee;\n  if (type === 'soft') {\n    const totalProfit = endPre - Math.max(hwm, start);\n    fee = rate * totalProfit;\n  } else {\n    fee = rate * above;\n  }\n  const post = endPre - fee;\n  return { performance_fee_per_share: fee, ending_nav_post_fee: post, new_high_water_mark: Math.max(post, hwm) };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#performance-fee-calc", "entity": {"type": "calculator", "id": "performance-fee-calc"}, "tokens_approx": 274, "tags": ["calculator"]}
{"id": "calculator:annualize-return-calc", "title": "Annualize Return", "text": "# Annualize Return (Calculator)\n\n**Summary:** Annualize Return\n\n**Formula reference:** sharpe-ratio\n\n**Inputs:** total_return(number); years(number)\n\n**Outputs:** annualized(number)\n\n**Reference impl (javascript):**\n```\nfunction annualize(totalReturn, years) { return { annualized: Math.pow(1 + totalReturn, 1 / years) - 1 }; }\n```", "source": "https://hedgefund.wiki/api/calculators.json#annualize-return-calc", "entity": {"type": "calculator", "id": "annualize-return-calc"}, "tokens_approx": 82, "tags": ["calculator"]}
{"id": "calculator:vol-annualize-calc", "title": "Annualize Volatility", "text": "# Annualize Volatility (Calculator)\n\n**Summary:** Annualize Volatility\n\n**Formula reference:** sharpe-ratio\n\n**Inputs:** periodic_vol(number); periods_per_year(integer)\n\n**Outputs:** annualized_vol(number)\n\n**Reference impl (javascript):**\n```\nfunction annVol(v, n) { return { annualized_vol: v * Math.sqrt(n) }; }\n```", "source": "https://hedgefund.wiki/api/calculators.json#vol-annualize-calc", "entity": {"type": "calculator", "id": "vol-annualize-calc"}, "tokens_approx": 79, "tags": ["calculator"]}
{"id": "calculator:black-scholes-call-calc", "title": "Black-Scholes Call Price + Greeks", "text": "# Black-Scholes Call Price + Greeks (Calculator)\n\n**Summary:** Black-Scholes Call Price + Greeks\n\n**Formula reference:** black-scholes\n\n**Inputs:** S(number); K(number); T(number); r(number); sigma(number); q(number)\n\n**Outputs:** call(number); delta(number); gamma(number); vega(number); theta(number); rho(number)\n\n**Reference impl (javascript):**\n```\nfunction normCdf(x){const a1=0.254829592,a2=-0.284496736,a3=1.421413741,a4=-1.453152027,a5=1.061405429,p=0.3275911;const sign=x<0?-1:1;x=Math.abs(x)/Math.SQRT2;const t=1/(1+p*x);const y=1-(((((a5*t+a4)*t)+a3)*t+a2)*t+a1)*t*Math.exp(-x*x);return 0.5*(1+sign*y);}\nfunction normPdf(x){return Math.exp(-x*x/2)/Math.sqrt(2*Math.PI);}\nfunction bsCall(S,K,T,r,sigma,q=0){\n  const d1=(Math.log(S/K)+(r-q+sigma*sigma/2)*T)/(sigma*Math.sqrt(T));\n  const d2=d1-sigma*Math.sqrt(T);\n  const Nd1=normCdf(d1),Nd2=normCdf(d2),nd1=normPdf(d1);\n  const call=S*Math.exp(-q*T)*Nd1-K*Math.exp(-r*T)*Nd2;\n  return {\n    call,\n    delta: Math.exp(-q*T)*Nd1,\n    gamma: Math.exp(-q*T)*nd1/(S*sigma*Math.sqrt(T)),\n    vega: S*Math.exp(-q*T)*nd1*Math.sqrt(T),\n    theta: -(S*Math.exp(-q*T)*nd1*sigma)/(2*Math.sqrt(T)) - r*K*Math.exp(-r*T)*Nd2 + q*S*Math.exp(-q*T)*Nd1,\n    rho: K*T*Math.exp(-r*T)*Nd2\n  };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#black-scholes-call-calc", "entity": {"type": "calculator", "id": "black-scholes-call-calc"}, "tokens_approx": 309, "tags": ["calculator"]}
{"id": "calculator:implied-vol-newton-calc", "title": "Implied Volatility (Newton-Raphson)", "text": "# Implied Volatility (Newton-Raphson) (Calculator)\n\n**Summary:** Implied Volatility (Newton-Raphson)\n\n**Formula reference:** black-scholes\n\n**Inputs:** market_price(number); S(number); K(number); T(number); r(number); q(number)\n\n**Outputs:** implied_vol(number)\n\n**Reference impl (javascript):**\n```\n// Requires bsCall from black-scholes-call-calc\nfunction impliedVol(price, S, K, T, r, q = 0) {\n  let sigma = 0.30;\n  for (let i = 0; i < 100; i++) {\n    const o = bsCall(S, K, T, r, sigma, q);\n    const diff = o.call - price;\n    if (Math.abs(diff) < 1e-8) return { implied_vol: sigma };\n    sigma -= diff / o.vega;\n    if (sigma <= 0) sigma = 0.001;\n  }\n  return { implied_vol: sigma };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#implied-vol-newton-calc", "entity": {"type": "calculator", "id": "implied-vol-newton-calc"}, "tokens_approx": 173, "tags": ["calculator"]}
{"id": "calculator:duration-modified-calc", "title": "Modified Duration", "text": "# Modified Duration (Calculator)\n\n**Summary:** Modified Duration\n\n**Formula reference:** duration-modified\n\n**Inputs:** cash_flows(array<number>); times(array<number>); ytm(number); compounding(integer)\n\n**Outputs:** macaulay(number); modified(number); price(number)\n\n**Reference impl (javascript):**\n```\nfunction durations(cfs, times, ytm, m = 2) {\n  let pv = 0, weighted = 0;\n  for (let i = 0; i < cfs.length; i++) {\n    const df = Math.pow(1 + ytm/m, -times[i]*m);\n    pv += cfs[i] * df;\n    weighted += times[i] * cfs[i] * df;\n  }\n  const mac = weighted / pv;\n  const mod = mac / (1 + ytm/m);\n  return { macaulay: mac, modified: mod, price: pv };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#duration-modified-calc", "entity": {"type": "calculator", "id": "duration-modified-calc"}, "tokens_approx": 164, "tags": ["calculator"]}
{"id": "calculator:cds-spread-calc", "title": "CDS Spread (Simplified)", "text": "# CDS Spread (Simplified) (Calculator)\n\n**Summary:** CDS Spread (Simplified)\n\n**Formula reference:** cds-pricing\n\n**Inputs:** default_probability(number); recovery_rate(number)\n\n**Outputs:** spread_bps(number)\n\n**Reference impl (javascript):**\n```\nfunction cdsSpread(p, R = 0.40) { return { spread_bps: p * (1 - R) * 10000 }; }\n```", "source": "https://hedgefund.wiki/api/calculators.json#cds-spread-calc", "entity": {"type": "calculator", "id": "cds-spread-calc"}, "tokens_approx": 82, "tags": ["calculator"]}
{"id": "calculator:merger-arb-annualized-spread-calc", "title": "Merger Arb Annualized Spread", "text": "# Merger Arb Annualized Spread (Calculator)\n\n**Summary:** Annualizes the deal spread given the days remaining to close.\n\n**Formula reference:** irr-newton\n\n**Inputs:** deal_price(number); current_price(number); days_to_close(number)\n\n**Outputs:** raw_spread_pct(number); annualized_spread_pct(number)\n\n**Reference impl (javascript):**\n```\nfunction mergerSpread(deal, current, days) {\n  const raw = deal / current - 1;\n  const ann = raw * (365 / Math.max(days, 1));\n  return { raw_spread_pct: raw, annualized_spread_pct: ann };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#merger-arb-annualized-spread-calc", "entity": {"type": "calculator", "id": "merger-arb-annualized-spread-calc"}, "tokens_approx": 133, "tags": ["calculator"]}
{"id": "calculator:perp-funding-rate-pnl-calc", "title": "Perpetual Futures Funding-Rate Carry P&L", "text": "# Perpetual Futures Funding-Rate Carry P&L (Calculator)\n\n**Summary:** Annualized P&L from a cash-and-carry trade in crypto perps.\n\n**Formula reference:** irr-newton\n\n**Inputs:** funding_rate_per_period(number); periods_per_day(integer)\n\n**Outputs:** annualized(number)\n\n**Reference impl (javascript):**\n```\nfunction perpFundingAnn(rate, perDay = 3) { return { annualized: rate * perDay * 365 }; }\n```", "source": "https://hedgefund.wiki/api/calculators.json#perp-funding-rate-pnl-calc", "entity": {"type": "calculator", "id": "perp-funding-rate-pnl-calc"}, "tokens_approx": 100, "tags": ["calculator"]}
{"id": "calculator:irr-calc", "title": "IRR (Newton)", "text": "# IRR (Newton) (Calculator)\n\n**Summary:** IRR (Newton)\n\n**Formula reference:** irr-newton\n\n**Inputs:** cash_flows(array<number>); guess(number)\n\n**Outputs:** irr(number)\n\n**Reference impl (javascript):**\n```\nfunction irr(cfs, guess = 0.10) {\n  let r = guess;\n  for (let i = 0; i < 100; i++) {\n    let f = 0, fp = 0;\n    for (let t = 0; t < cfs.length; t++) {\n      f += cfs[t] / Math.pow(1 + r, t);\n      fp -= t * cfs[t] / Math.pow(1 + r, t + 1);\n    }\n    const next = r - f / fp;\n    if (Math.abs(next - r) < 1e-9) return { irr: next };\n    r = next;\n  }\n  return { irr: r };\n}\n```", "source": "https://hedgefund.wiki/api/calculators.json#irr-calc", "entity": {"type": "calculator", "id": "irr-calc"}, "tokens_approx": 146, "tags": ["calculator"]}