First Quadrant examines how tail risk changes across market cycles rather than remaining constant. Using volatility regimes defined by a composite VIX, the paper argues that extreme losses cluster during high uncertainty periods, challenging risk models that rely on long term averages and normal distributions.
How “Tail Risk” Changes Over the Market Cycle
First Quadrant
Edgar Peters, Bruno Miranda
Research
8 Pages
Key Takeaways
Tail Risk Clusters: The probability of a monthly decline worse than -13% was 1.36% in high uncertainty periods versus 0% in low uncertainty periods.
Volatility Regimes Matter: MSCI excess returns averaged -3.33% during high volatility regimes compared with 10.10% during low volatility regimes from 1990 to 2013.
Conditional Metrics Improve: High uncertainty produced conditional kurtosis of 5.17 and conditional skewness of -1.73, revealing risks conventional statistics significantly understated.
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