Explanation:
The team is concerned about clustering of exceptions, which suggests a focus on whether exceptions are occurring independently over time. A conditional coverage test addresses this by combining:
By testing both aspects, a conditional coverage test can identify if the model is failing to account for time-varying risks that cause clustering.
B is incorrect: While comparing the model to historical data helps validate its accuracy, it does not directly address the clustering of exceptions or time-varying risks.
C is incorrect: Stress testing evaluates the model's performance under hypothetical extreme conditions but does not analyze the temporal clustering of exceptions.
D is incorrect: Rolling window analysis helps identify model stability and performance trends but does not explicitly test for the independence of exceptions.
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Q.6442 The risk management team at Horizon Bank is validating their VaR model using backtesting techniques. They start with an unconditional coverage test to determine whether the model’s predicted exception rate matches the observed frequency of exceptions. However, they are also concerned about whether exceptions are clustering in certain time periods, indicating potential weaknesses in the model’s ability to account for time-varying risks. Which of the following would address the team’s concern about clustered exceptions?
A
Perform a conditional coverage test.
B
Compare the VaR model against historical market data.
C
Conduct a stress test to evaluate the model under extreme scenarios.
D
Use a rolling window analysis to assess model performance over time.
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