Case Studies of Exotic Product Blowups
Case Studies of Exotic Product Blowups
Exotic derivatives have been involved in some of the largest trading losses in financial history. These failures typically stem from model errors, underestimated tail risks, inadequate hedging, or governance breakdowns. Studying these cases provides essential lessons for risk management.
Definition and Key Concepts
Common Failure Patterns
| Pattern | Description |
|---|---|
| Model failure | Pricing/hedging model inadequate for actual risks |
| Tail risk | Rare events cause outsized losses |
| Liquidity trap | Can't exit or hedge positions |
| Correlation breakdown | Diversification fails in crisis |
| Leverage | Small moves create large losses |
| Governance failure | Inadequate oversight, rogue trading |
Warning Signs
| Sign | Meaning |
|---|---|
| Complexity | Hard to explain = hard to hedge |
| Premium income | Selling tail risk |
| Correlation assumptions | Unstable in stress |
| Short volatility | Unlimited loss potential |
| Model dependence | No market prices for validation |
Case Study 1: XIV Volmageddon (February 2018)
Situation
Product: XIV (Velocity Shares Daily Inverse VIX Short-Term ETN) Strategy: Daily inverse of VIX futures (-1×) Issuer: Credit Suisse
How it worked:
- Each day, rebalance to deliver -100% of VIX futures return
- In calm markets: VIX futures decline (contango), XIV rises
- Required daily rebalancing into moves
What Went Wrong
February 5, 2018:
- VIX spiked from 17 to 37 (118% increase)
- VIX futures rose ~100% intraday
- XIV needed to buy VIX futures into the spike
Death spiral dynamics:
| Time | VIX Futures | XIV Action | Impact |
|---|---|---|---|
| 3pm | +50% | Buy futures | Pushes VIX higher |
| 3:30pm | +75% | Buy more | Accelerates spike |
| 4pm | +100% | Buy more | Self-reinforcing |
| Close | +115% | Forced buying | XIV down 93% |
Loss magnitude:
- XIV lost 93% in one day
- NAV fell from ~$2 billion to ~$150 million
- Product terminated
Lessons Learned
| Lesson | Application |
|---|---|
| Leveraged rebalancing risk | Daily rebalancing amplifies moves |
| Short vol is dangerous | Tail events cause catastrophic losses |
| Liquidity in size | Large positions can't exit in stress |
| Termination provisions | Read accelerated termination clauses |
| Correlation to market | Everyone hedging same direction |
Case Study 2: JPMorgan London Whale (2012)
Situation
Desk: Chief Investment Office (CIO) Strategy: Credit index hedging turned into proprietary trading Instruments: CDX indices, tranches, and exotic credit derivatives
Initial purpose: Hedge credit exposure across JPMorgan's balance sheet.
What Went Wrong
Position accumulation:
- Synthetic credit positions grew to >$100 billion notional
- Market share in certain CDX tranches exceeded 50%
- Position became the market
Pricing problems:
| Issue | Description |
|---|---|
| Mark-to-market | Valued at model, not market |
| Bid-ask | Wide spreads obscured true value |
| Liquidity | Couldn't exit without moving market |
| Basis risk | Hedges didn't offset as expected |
Unwind losses:
| Quarter | Loss |
|---|---|
| Q2 2012 | $4.4 billion |
| Q3 2012 | $1.5 billion |
| Total | ~$6 billion |
Lessons Learned
| Lesson | Application |
|---|---|
| Position limits | Size relative to market liquidity |
| Independent valuation | Don't let traders mark their own books |
| Hedge vs. prop | Clear distinction, different limits |
| Concentration risk | Dominant position = trapped |
| Model validation | Verify against market prices |
Case Study 3: Swiss Franc Barrier Options (January 2015)
Situation
Event: Swiss National Bank removed EUR/CHF 1.20 floor Date: January 15, 2015 Move: EUR/CHF dropped 30% instantly (1.20 → 0.85)
Affected products:
- Barrier options on EUR/CHF
- Target redemption forwards (TARFs)
- Knock-in/knock-out structures
What Went Wrong
Barrier option exposure: Many corporate hedgers and private banks sold knock-in puts or bought knock-out calls at/near 1.20 barrier.
When floor removed:
| Position | Impact |
|---|---|
| Short knock-in put | Knocked in, massive loss |
| Long knock-out call | Knocked out, worthless |
| Leveraged TARFs | Accumulated huge losses |
Example TARF loss:
- Notional: $10 million
- Accumulated leverage: 5×
- CHF move: 30%
- Loss: $10M × 5 × 30% = $15 million (150% of notional)
Industry losses:
- Retail FX brokers: Several bankruptcies
- Banks: Billions in losses
- Corporates: Large unexpected losses
Lessons Learned
| Lesson | Application |
|---|---|
| Gap risk | Central bank actions can skip barriers |
| Leverage amplification | Small moves, huge losses |
| Correlation = 1 in crisis | All CHF positions moved together |
| Stress testing | Test for gap scenarios |
| Counterparty credit | Clients couldn't pay losses |
Case Study 4: Correlation Products in 2008
Situation
Products: CDO-squared, synthetic CDOs, correlation trades Pre-crisis: High demand for structured credit yield enhancement
Mechanics:
- CDOs pooled credit risk
- CDO² (CDO-squared) pooled CDOs
- Tranching created "AAA" rated pieces
What Went Wrong
Correlation collapse:
- Housing downturn caused correlated defaults
- "AAA" tranches experienced losses
- Correlation that was assumed to be 0.2 became 0.8
CDO valuation collapse:
| Tranche | Pre-Crisis Price | Crisis Price | Loss |
|---|---|---|---|
| AAA | $100 | $50-80 | 20-50% |
| AA | $100 | $30-60 | 40-70% |
| A | $100 | $10-40 | 60-90% |
| BBB | $100 | $0-20 | 80-100% |
| Equity | $100 | $0 | 100% |
Total losses: Hundreds of billions across financial system.
Lessons Learned
| Lesson | Application |
|---|---|
| Correlation assumptions | Correlations spike in crises |
| Rating agency reliance | AAA doesn't mean no risk |
| Tail risk pricing | Models underpriced extremes |
| Complexity | Couldn't understand own positions |
| Liquidity evaporation | No bids for CDOs |
Summary: Common Themes
Risk Management Failures
| Theme | Occurrence |
|---|---|
| Underestimated tail risk | All cases |
| Inadequate stress testing | All cases |
| Model over-reliance | All cases |
| Position size relative to liquidity | Most cases |
| Correlation assumptions | Most cases |
| Governance gaps | Most cases |
VaR Limitations Illustrated
| Case | VaR Said | Reality |
|---|---|---|
| XIV | ~$50M max daily loss | $1.9B one-day loss |
| London Whale | Limits not breached | $6B total loss |
| CHF barrier | Normal FX risk | 30% gap move |
| CDOs | High-rated, low risk | Total loss of capital |
Warning Indicators
| Indicator | Warning Level |
|---|---|
| Short vol/selling premium | High risk |
| Position > 10% market volume | Liquidity trap risk |
| Model-dependent pricing | Validation needed |
| Correlation-dependent | Stress test for breakdown |
| Leverage > 5× | Amplified losses |
| Complexity > 2 exotics | Hard to hedge |
Checklist and Next Steps
Pre-trade risk assessment:
- Identify tail risk scenarios
- Stress test for gap moves
- Assess liquidity relative to position
- Verify model against market
- Calculate maximum possible loss
- Review with independent risk
Position monitoring:
- Track position vs. market share
- Monitor liquidity conditions
- Stress test regularly
- Review Greeks in scenarios
- Report to senior management
Governance checklist:
- Clear position limits
- Independent valuation
- Regular risk reporting
- Escalation procedures
- Documented exceptions
Related articles:
- For hedging, see Hedging Complex Payoffs in Practice
- For terminology, see Glossary: Exotic and Volatility Products