Conditional VaR (Expected Shortfall)
What happens when things go wrong?
CVaR (or Expected Shortfall) answers what VaR misses: 'If we *do* breach the VaR limit, what is the average loss?' It measures the average loss in the tail of the distribution, providing a more conservative view of catastrophic risk.
Why CVaR is Superior
CVaR is 'sub-additive', meaning the risk of a portfolio is always less than or equal to the sum of the risks of its parts. VaR fails this property, making CVaR the preferred metric for optimization.
Key Takeaways
Measures the 'average' worst-case scenario.
Better for fat-tailed distributions.
More conservative than VaR.
Conditional VaR (Expected Shortfall)
What happens when things go wrong?
CVaR (or Expected Shortfall) answers what VaR misses: 'If we *do* breach the VaR limit, what is the average loss?' It measures the average loss in the tail of the distribution, providing a more conservative view of catastrophic risk.
Why CVaR is Superior
CVaR is 'sub-additive', meaning the risk of a portfolio is always less than or equal to the sum of the risks of its parts. VaR fails this property, making CVaR the preferred metric for optimization.
Key Takeaways
Measures the 'average' worst-case scenario.
Better for fat-tailed distributions.
More conservative than VaR.
Apply This Knowledge
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