FRM Part II · FRM Exam Part II · Advances in Artificial Intelligence: Implications for Capital Markets Activities
A desk head reviews an AI-driven market-making strategy whose profits come mainly from many small gains, with rare large losses when volatility jumps. Back-tested daily 99% VaR is low. Which conclusion is most consistent with sound risk practice for such AI trading models?
Risk should be assessed with stress tests and scenario analysis beyond VaR. Steady small gains with rare large losses resemble short-volatility exposure, so a low back-tested VaR can understate tail risk and model uncertainty, and it should not justify relaxing limits.
- ALow VaR confirms the strategy is low risk, so limits can be relaxed
- BTail risk and model uncertainty should be assessed with stress tests and scenario analysis beyond VaR, since the strategy resembles short-volatility exposureCorrect
- CVaR is unreliable only for human traders, not for AI models
- DRare large losses are irrelevant if the average daily profit is positive
Explanation
A profile of steady small gains and rare large losses signals negative skew and hidden tail exposure that a 99% VaR on a calm sample may understate. Stress testing and scenario analysis complement VaR and address model uncertainty. Relaxing limits or ignoring tails would be unsound.
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