Financial Risk Manager Part 2

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Explanation:

According to the Peaks-Over-Threshold (POT) approach in Extreme Value Theory (EVT), the Balkema-de Haan-Pickands theorem states that as the threshold value is raised, the distribution of exceedances over that high threshold converges to the Generalized Pareto Distribution (GPD).

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Question The CRO of a regional bank expresses concern in a meeting of the risk team that the bank’s internal risk models are not adequately assessing potential random extreme losses. A risk analyst asks if implementing a model based on extreme value theory (EVT) would address the CRO’s concern. Which of the following is correct when applying EVT and examining distributions of losses exceeding a threshold value?

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Last updated: July 5, 2026 at 07:28

As the threshold value is increased, the distribution of losses over a fixed threshold value converges to a generalized Pareto distribution.

If the tail parameter value of the generalized extreme-value (GEV) distribution goes to infinity, then the GEV essentially becomes a normal distribution.

To apply EVT, the underlying loss distribution must be either normal or lognormal.

The number of exceedances decreases as the threshold value decreases, which causes the reliability of the parameter estimates to increase.