What is the main disadvantage of using analytical VAR?

The main disadvantage of using analytical Value at Risk (VAR) is its reliance on the assumption of normality, which can lead to misleading results. This approach presumes that returns are normally distributed, which may not accurately reflect the characteristics of financial returns, particularly during periods of market stress or increased volatility. Financial data often exhibit heavy tails and skewness, meaning that extreme events are more common than the normal distribution would suggest. This can result in underestimating the potential for losses, which is a critical consideration in risk management.

In contrast, while some options might also present challenges—such as complexity in computations or sensitivity to extreme values—analytical VAR's reliance on normal distributions stands out as a fundamental limitation that can significantly affect risk assessment and decision-making in financial contexts. By overestimating the likelihood of small losses while underestimating the probability of large losses, this drawback can have profound implications for capital allocation and risk management strategies.