Explanation:
Shortening the historical window from 10 years to 5 years in VaR calculations can help improve the accuracy of the predictions by making the data more relevant to current market conditions. Given the recent discrepancies between predicted and actual losses, this adjustment allows for a more accurate reflection of the current market volatility and risk characteristics, which can change significantly over shorter periods.
A is incorrect. While increasing the confidence level from 95% to 99% does reduce the probability of losses exceeding the VaR, it does not address the issue of the historical data no longer being representative of current market conditions, which is likely causing the discrepancies.
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Q.6207 In the context of market risk management, ABC Financial, a multinational investment bank, utilizes a Value at Risk (VaR) model to predict potential losses in an unusually volatile market. The bank uses historical simulation based on a 10-year market data set. However, they have been experiencing discrepancies between their VaR predictions and actual losses, which exceeded the VaR estimates on several occasions last quarter. Given the nature of the data and market conditions, which of the following would most likely improve the accuracy of ABC Financial's VaR predictions?
A
Increasing the confidence level from 95% to 99% in the VaR calculations.
B
Shortening the historical window from 10 years to 5 years.
C
Integrating stress testing scenarios based on hypothetical future market disruptions.
D
Applying a Gaussian copula model to better capture dependencies between asset classes.
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