Explanation:
In backtesting, using a 99% confidence level typically results in very few expected exceptions (e.g., 2.5 exceptions over 250 trading days). This small sample size significantly reduces the statistical power of the test, making it difficult to confidently accept or reject the model. At a 95% confidence level, the expected number of exceptions increases (e.g., 12.5 exceptions over 250 days), providing a much more robust and reliable basis for determining the accuracy of the model and for deciding whether to accept or reject it.
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Q.53 While carrying out backtesting of a leading bank's VaR model, you have made the following findings: the bank is currently calculating the 1-day VaR at a confidence level of 99%. However, based on your findings you suggest changing the confidence level from 99% to 95%. Which of the following statements would justify your stance?
A
While conducting backtesting with a 95% confidence interval, the probability of committing a Type 1 error is small as compared to the probability of Type 1 error when backtesting with 95% and 99% VaR models.
B
The accuracy of the VaR model and the basis of accepting/rejecting the model have a greater reliability at a 95% confidence level VaR as compared to at a 99% confidence level.
C
While conducting backtesting with a 95% confidence interval, the probability of rejecting the VaR models at a 95% confidence level is equal to that at a 99% confidence level.
D
There are fewer chances of a 95% VaR model being rejected based on backtesting as compared to a 99% VaR model.
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