The Anderson-Darling test provides enhanced sensitivity to the tails of distributions, making it ideal for understanding if a VaR model accurately captures tail risks and aligns with extreme quantile expectations. This focus on tails ensures the model can effectively predict and manage risks associated with extreme market events. By addressing tail-specific behaviors, the Anderson-Darling test complements broader uniformity tests, providing a more comprehensive validation of the model’s predictive capabilities.

A is incorrect. Cramér-von Mises tests balance sensitivity but are not as focused on tails as the Anderson-Darling.
C is incorrect. KS test is less ideal for tail-specific evaluations.
D is incorrect. Variance-Ratio tests address volatility rather than direct distribution uniformity or tail-dependence.

Things to Remember:

• Anderson-Darling is particularly useful for models needing accurate tail prediction.
• Enhances validation in models designed for severe economic scenarios.
• Focus on extreme quantiles helps align models with both risk management and regulatory needs.