Learn what conditional value at risk measures, how it extends VaR, and why tail-loss averages matter in serious risk management.
Conditional value at risk (CVaR) estimates the average loss in the worst part of the loss distribution after the value at risk threshold has already been breached.
It is often described as a deeper tail-risk measure than VaR because it focuses on the severity of bad outcomes, not just the cutoff point.
If a portfolio has a 95% VaR, the remaining 5% of cases are the worst outcomes beyond that threshold.
CVaR asks: what is the average loss inside that worst tail?
That makes it especially useful when risk managers care about how bad extreme losses can become once the portfolio moves beyond its ordinary range.
Suppose a portfolio has:
95% VaR: $2 million95% CVaR: $3.4 millionThat means losses worse than the VaR threshold are not just slightly worse on average. In the worst 5% of cases, the average loss is around $3.4 million.
A manager says, “VaR already tells us tail risk, so CVaR is unnecessary.”
Answer: VaR identifies the cutoff. CVaR helps show how severe losses can be beyond that cutoff.