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FRM Part II · FRM Exam Part II · Parametric Approaches (II): Extreme Value

A risk analyst wants to apply extreme value theory to the joint behavior of losses on an equity portfolio and a credit portfolio during crises. Which feature of multivariate EVT is most relevant to this goal?

Multivariate EVT models the dependence of extreme outcomes across risk factors. Correlation estimated mostly from ordinary observations can understate how strongly losses cluster in crises, so tail dependence modeling gives a more realistic view of joint extreme losses and diversification.

  1. AIt models dependence among extremes, which can be stronger than the dependence suggested by a correlation estimated from the center of the distributionCorrect
  2. BIt assumes all risk factors are jointly normal in the tails, so the correlation matrix is sufficient
  3. CIt removes the need to choose a threshold for each marginal distribution
  4. DIt guarantees that diversification benefits increase in extreme events

Explanation

Multivariate EVT focuses on tail dependence, i.e., how likely extremes occur together. Linear correlation estimated from ordinary observations can understate co-movement in crises. Normal-tail assumptions are the opposite of what EVT does, and thresholds are still needed.

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