{ "$schema": "https://hedgefund.wiki/api/schema.json#/definitions/Term", "endpoint": "https://hedgefund.wiki/api/risk-management.json", "version": "2026.05.0", "description": "Risk management concepts, methodologies, and frameworks used by institutional hedge funds.", "concepts": [ { "id": "var-family", "name": "Value at Risk Family", "subconcepts": [ { "id": "parametric-var", "name": "Parametric (Variance-Covariance) VaR", "method": "Assume returns are jointly normal with known covariance Σ; VaR_α = z_α × √(w' Σ w) × NAV.", "pros": ["Closed-form", "Fast for large portfolios", "Clean Greeks decomposition"], "cons": ["Massively underestimates fat tails", "Assumes constant correlations", "Misses optionality"], "use_when": "Linear, well-behaved portfolios with quick recompute needs." }, { "id": "historical-var", "name": "Historical Simulation VaR", "method": "Apply historical return distribution to current positions; read percentile of P&L distribution.", "pros": ["No distributional assumption", "Captures observed fat tails and correlations"], "cons": ["Sensitive to lookback length", "Cannot extrapolate beyond observed history", "Slow for full revaluation"], "use_when": "Standard institutional choice; most banks under FRTB use this." }, { "id": "monte-carlo-var", "name": "Monte Carlo VaR", "method": "Simulate from a fitted joint distribution (often copula-based with t-marginals); revalue portfolio per scenario.", "pros": ["Handles non-linearity (options)", "Customizable distributions", "Captures tail dependence via copulas"], "cons": ["Compute-intensive", "Distribution choice and parameterization are model risk"], "use_when": "Option-heavy or path-dependent portfolios." } ] }, { "id": "expected-shortfall", "name": "Expected Shortfall (Conditional VaR)", "summary": "Average loss in the worst α% of outcomes — coherent, tail-sensitive, replacing VaR under Basel FRTB.", "regulatory_use": "Basel III FRTB market risk capital uses ES at 97.5% level (equivalent to ~99% normal VaR).", "see_also": [{ "type": "term", "id": "expected-shortfall" }, { "type": "formula", "id": "expected-shortfall" }] }, { "id": "stress-testing", "name": "Stress Testing", "summary": "Re-pricing the portfolio under hypothetical or historical shock scenarios.", "scenario_types": [ { "id": "historical-replay", "scenarios": [ "Black Monday Oct 19, 1987 (S&P -22.6% in a day)", "Asian Crisis Aug-Oct 1997", "Russia/LTCM Aug-Sep 1998", "Tech Crash Apr 2000 - Oct 2002", "Aug 2007 Quant Quake (cross-strategy stat-arb deleveraging)", "Lehman Sep 15, 2008 - Mar 2009", "Flash Crash May 6, 2010", "Aug 24, 2015 China devaluation flash crash", "Brexit Jun 23-24, 2016", "Volmageddon Feb 5, 2018 (XIV blowup)", "Q4 2018 selloff (rates + credit + equities together)", "March 2020 COVID dash-for-cash", "Jan 2021 GameStop short squeeze", "Mar 2022 nickel short squeeze (LME canceled trades)", "Sep 2022 UK gilts/LDI crisis", "Mar 2023 SVB / regional bank crisis", "Aug 5, 2024 Yen carry unwind" ] }, { "id": "hypothetical", "scenarios": [ "Rates +200bp parallel shift", "Equity -25%", "USD/JPY +15% (yen weakening)", "Oil -50%", "Credit spreads +200bp", "Vol +20 vol points (SPX IV)", "Repo blowout (+100bp on funding spreads)" ] }, { "id": "reverse", "summary": "Find the smallest shock that breaches a threshold (e.g., -20% NAV)." } ], "regulatory_requirements": [ "Form PF: large hedge fund advisers report stress test results quarterly.", "AIFMD Annex IV: regular stress reporting to home regulator.", "Basel FRTB SA: prescribed stress scenarios for bank prop / inventory." ], "see_also": [{ "type": "term", "id": "stress-test" }, { "type": "regulation", "id": "form-pf" }] }, { "id": "drawdown-control", "name": "Drawdown Control", "summary": "Active reduction of leverage or risk as drawdowns deepen, to protect capital and preserve optionality to recover.", "techniques": [ { "name": "CPPI (Constant Proportion Portfolio Insurance)", "method": "Risk = m × (NAV − floor); reduce risk to zero at floor.", "pitfall": "Procyclical — sells into selloffs; can lock at the floor in trending bear markets." }, { "name": "Vol targeting", "method": "Scale exposure to target a constant ex-ante vol; reduces in vol spikes.", "pitfall": "Lags realized vol; can amplify deleveraging cascades." }, { "name": "Discretionary stop-out", "method": "Manager triggers de-risking on -X% from peak.", "pitfall": "Behavioral inconsistency; difficult under stress." }, { "name": "Pod risk leashes (multi-strat)", "method": "PM is cut by 50% at -3%, fired at -5/8%.", "pitfall": "Forces premature exits; selects for short-horizon strategies." } ] }, { "id": "counterparty-risk", "name": "Counterparty Risk", "summary": "Risk that a trading counterparty defaults before performing on outstanding obligations.", "mitigation": [ "ISDA Master + CSA with daily Variation Margin and Initial Margin (UMR phases 1-6, 2016-2022)", "Central clearing where mandated (Title VII; EMIR; UMR)", "Multi-PB structure (typically 2-4 prime brokers post-Lehman)", "Tri-party custody for excess collateral", "Daily counterparty exposure monitoring + concentration limits", "Settlement (PvP for FX via CLS; T+1 for US equities since May 2024)" ], "case_studies": [ { "type": "event", "id": "lehman-collapse", "label": "Lehman Sep 2008 — UK Rule 7 freeze" }, { "type": "event", "id": "mf-global-2011", "label": "MF Global Oct 2011 — segregated funds shortfall" }, { "type": "event", "id": "archegos-2021", "label": "Archegos Mar 2021 — total return swap exposure" } ], "see_also": [{ "type": "term", "id": "counterparty-risk" }, { "type": "term", "id": "isda" }] }, { "id": "liquidity-risk", "name": "Liquidity Risk", "summary": "Risk of being unable to exit at a fair price within needed timeframe; encompasses market liquidity and funding liquidity.", "metrics": [ "Days-to-liquidate (e.g., at 25% of ADV) for each position", "Liquidity buckets: 1 day, 1 week, 1 month, 3 months, 6+ months", "Asset-liability liquidity matching to redemption terms", "Bid-ask spread and effective spread time series", "Amihud illiquidity (|return| / dollar volume)", "Funding-liquidity coverage ratio (cash + margin headroom / 30-day stressed outflow)" ], "case_studies": [ { "type": "event", "id": "ltcm-collapse" }, { "type": "event", "id": "march-2020-dash-for-cash" }, { "type": "event", "id": "woodford-2019" } ], "see_also": [ { "type": "term", "id": "liquidity-risk" }, { "type": "term", "id": "amihud-illiquidity" }, { "type": "term", "id": "side-pocket" } ] }, { "id": "model-risk", "name": "Model Risk", "summary": "Risk of loss arising from decisions based on flawed or misapplied models.", "components": [ "Specification error (wrong functional form)", "Estimation error (parameters fit to a regime that has shifted)", "Implementation bugs (off-by-one, look-ahead, survivorship bias)", "Misuse (using a model outside its calibrated domain)" ], "controls": [ "Independent model validation (separate team)", "Champion-challenger ensembles", "Backtest with strict out-of-sample discipline", "Model inventory and tiering (SR 11-7 framework)" ] }, { "id": "operational-risk", "name": "Operational Risk", "summary": "Risk from failed processes, people, systems, or external events.", "subcategories": ["Trade settlement failures", "Fat-finger errors", "Cyber incidents (ransomware, account takeover)", "Vendor / SaaS outages (e.g., June 2024 CrowdStrike)", "Compliance breaches (insider trading, sanctions, AML)"], "metrics": ["NAV restatements", "Trade error count and $ impact", "Reg breach count", "Failed-trade rate"], "regulatory_focus": "SEC Rule 206(4)-7 (compliance program); NYDFS Part 500 cybersecurity; SEC 2024 cyber disclosure rules." } ] }