Should a portfolio construction process use VaR, CVaR, or variance as its risk measure?

Question

AcadiFi · Accepted Answer

The best measure depends on the portfolio and the investor's loss preferences. Variance uses all return observations and works well when upside and downside volatility are treated symmetrically. VaR focuses on a cutoff loss and is easy to communicate, but it ignores how bad losses become beyond the cutoff. CVaR captures average tail severity, making it more useful when deep losses matter.

Suppose Redwood Long-Short Equity manages an option-free equity portfolio with stable liquidity. Variance may be a reasonable core risk measure because return dispersion contains useful information. If the portfolio includes downside-sensitive mandates or tail-loss constraints, CVaR may better align with investor utility. VaR may remain useful for reporting a threshold but weaker as an optimization objective.

FRM questions often test whether candidates match the measure to the use case. There is no universal champion. Variance can be efficient and stable. VaR can be intuitive but incomplete. CVaR can be coherent and tail-aware but may require careful estimation. The right answer should mention the portfolio's payoff shape, the investor's tolerance for tail losses, and the operational purpose of the risk measure. On the exam, also state the horizon, confidence level, data source, modeling assumption, and validation step, because those choices usually explain why two reasonable VaR answers differ materially. Practice more in our FRM question bank.

Should a portfolio construction process use VaR, CVaR, or variance as its risk measure?

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