Stress Testing and Scenario Analysis

advancedPublished: 2026-01-01

Stress Testing and Scenario Analysis

Stress testing evaluates portfolio performance under extreme but plausible market conditions, complementing VaR by examining scenarios that statistical models may underweight. Effective stress testing combines historical events, hypothetical shocks, and reverse stress tests to identify vulnerabilities.

Definition and Key Concepts

Types of Stress Tests

TypeDescriptionUse Case
HistoricalReplay actual market eventsKnown crisis impacts
HypotheticalConstruct plausible shocksForward-looking scenarios
SensitivitySingle-factor movesUnderstand risk drivers
ReverseFind scenarios causing failureIdentify vulnerabilities

Stress Test vs. VaR

AttributeVaRStress Test
Probability-basedYesNo (plausibility judgment)
Scenario-specificNo (aggregate)Yes (named scenarios)
Extreme eventsUnderweightedExplicitly examined
Regulatory useMarket risk capitalComprehensive capital

Scenario Library

Historical scenarios:

EventDateKey Shocks
Black MondayOct 1987Equity -22%, vol +400 bps
LTCM/RussiaAug 1998Credit spreads +200 bps
Tech CrashMar 2000NASDAQ -40%, growth →value
GFCOct 2008Equity -40%, vol +500 bps
VolmageddonFeb 2018VIX +400%, vol products liquidate
COVID CrashMar 2020Equity -35%, vol +600 bps

How It Works in Practice

Scenario Construction

Historical scenario replay:

  1. Select event period
  2. Extract actual market moves
  3. Apply to current portfolio
  4. Calculate P/L

Hypothetical scenario design:

StepActivity
1Define narrative (e.g., "Fed rate shock")
2Specify risk factor moves
3Ensure internal consistency
4Apply to portfolio
5Analyze results

Risk Factor Shocks

Standard shock magnitudes:

Risk FactorModerateSevereExtreme
Equity spot-15%-25%-40%
Equity vol+50%+100%+200%
Interest rates+100 bps+200 bps+400 bps
Credit spreads+100 bps+250 bps+500 bps
FX+/- 10%+/- 20%+/- 30%

Correlation Assumptions

Normal markets: Correlations as observed historically.

Stress markets: Correlations typically move toward +1 for risk assets.

PairNormal CorrelationStress Correlation
Stocks / Credit0.40.8
Stocks / Vol-0.6-0.9
EM / DM equities0.70.9
USD / Risk assets-0.3-0.7

Worked Example

Portfolio:

  • Long $100M equities (S&P 500)
  • Long 1,000 SPX puts (4,000 strike, 3-month)
  • Short 500 SPX calls (5,500 strike, 3-month)

Current Greeks:

  • Delta: +85,000 shares
  • Gamma: +50 deltas per $1
  • Vega: +$200,000

Scenario 1: 2008-Style Crisis

Shocks:

  • S&P 500: -40% (5,000 → 3,000)
  • Implied vol: +200% (20% → 60%)
  • Rates: -150 bps

P/L Calculation:

ComponentCalculationP/L
Equity position-40% × $100M-$40,000,000
Delta on options85,000 × (-2,000) × 50%-$85,000,000
Gamma benefit½ × 50 × (2,000)²+$100,000,000
Put payoff (intrinsic)1,000 × 100 × ($4,000-$3,000)+$100,000,000
Vega gain$200,000 × 40%+$8,000,000
Call liability500 × 100 × $0$0
Net P/L+$83,000,000

The protective puts and long vega more than offset equity losses.

Scenario 2: Rate Spike + Equity Selloff

Shocks:

  • S&P 500: -20%
  • Implied vol: +50% (20% → 30%)
  • Rates: +200 bps

P/L Calculation:

ComponentCalculationP/L
Equity position-20% × $100M-$20,000,000
Delta on options85,000 × (-1,000) × 60%-$51,000,000
Gamma benefit½ × 50 × (1,000)²+$25,000,000
Vega gain$200,000 × 10%+$2,000,000
Rho impactHigher rates reduce put value-$500,000
Net P/L-$44,500,000

Moderate crash hurts more than extreme crash due to less gamma convexity.

Scenario 3: Melt-Up

Shocks:

  • S&P 500: +20%
  • Implied vol: -30% (20% → 14%)
  • Rates: +50 bps

P/L Calculation:

ComponentP/L
Equity gains+$20,000,000
Put decay-$3,000,000
Call liability-$8,500,000 (calls go ITM)
Vega loss-$1,200,000
Net P/L+$7,300,000

Upside capped by short calls.

VaR Comparison

ScenarioStress P/LImplied by 99% VaR
2008-style crash+$83M~(-$15M)
Rate spike + selloff-$45M~(-$15M)
Melt-up+$7M~(-$15M)

Stress tests reveal both upside potential and losses beyond VaR.

Risks, Limitations, and Tradeoffs

Scenario Design Challenges

ChallengeDescription
Correlation shiftsHard to predict how correlations change
Non-linearityOptions payoffs non-linear in risk factors
Path dependencySome products depend on how crisis unfolds
Model breakdownModels may fail in extreme stress

Historical Scenario Limitations

LimitationExample
Survivorship biasDon't test for events that haven't happened
Regime change2008 may not repeat exactly
Different starting pointCurrent vol/valuations differ from historical

Common Pitfalls

PitfallDescriptionPrevention
Too few scenariosMiss important risksComprehensive library
Inconsistent shocksFX up, exports down?Ensure economic consistency
Static portfolioIgnores hedging responseConsider dynamic scenarios
Ignore liquidityCan't exit positions in stressInclude liquidity stress

Reverse Stress Testing

Process:

  1. Define failure threshold (e.g., -50% capital)
  2. Work backward to find scenarios causing failure
  3. Assess plausibility of those scenarios
  4. Develop contingency plans

Example: Failure threshold: Portfolio loss > $50 million

Scenarios causing failure:

  • Equity -25% with vol flat (puts don't help enough)
  • Vol crush -50% without equity move
  • Counterparty default on winning positions

Regulatory Requirements

JurisdictionRequirement
US (Fed)CCAR, DFAST stress testing
EU (EBA)EU-wide stress tests
BaselInternal stress testing for capital
SECRegistered fund stress testing

Checklist and Next Steps

Scenario library checklist:

  • Include 5+ historical scenarios
  • Create 3+ hypothetical scenarios
  • Define sector-specific scenarios
  • Include recovery scenarios
  • Document scenario rationale

Execution checklist:

  • Calculate P/L for each scenario
  • Compare to risk limits
  • Identify largest loss scenarios
  • Attribute losses to risk factors
  • Present to risk committee

Follow-up checklist:

  • Review scenarios quarterly
  • Update for new risk factors
  • Conduct reverse stress tests
  • Develop action plans for severe scenarios
  • Document and archive results

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