Answer: Does not consider the severity of losses in the tail of the returns distribution.

## Explanation The key weakness of Value at Risk (VaR) is that **it does not consider the severity of losses in the tail of the returns distribution**. ### Why Option A is correct: - VaR measures the **maximum loss** at a given confidence level over a specified time horizon - However, it **does not provide information about losses beyond the VaR threshold** - This means VaR ignores the **magnitude and probability of extreme losses** in the tail of the distribution - For example, a VaR of $1 million at 95% confidence tells us we won't lose more than $1 million 95% of the time, but it doesn't tell us what could happen in the remaining 5% of cases ### Why other options are incorrect: - **Option B**: VaR is not particularly difficult to compute with modern computational methods - **Option C**: VaR is actually **not subadditive** - this is one of its mathematical weaknesses, but the question specifically asks for a "key weakness" and the tail risk issue is more fundamental - **Option D**: The amount of backtesting data depends on the specific implementation, not an inherent weakness of VaR itself This limitation led to the development of **Expected Shortfall (ES)** or **Conditional VaR (CVaR)**, which measures the average loss in the tail beyond the VaR threshold.

Author: LeetQuiz .