What is a key advantage of using Monte Carlo VAR?

The key advantage of using Monte Carlo Value at Risk (VAR) is that it does not require specific distributional assumptions about asset returns. This flexibility allows Monte Carlo simulations to model the behavior of portfolios under a wide range of scenarios and potential outcomes. Unlike some VAR methods, which may depend on normal distribution or other specific distributions, Monte Carlo VAR can incorporate various possible distributions of returns, including those that account for skewness and kurtosis.

This characteristic is especially valuable in dealing with complex portfolios that contain a mix of different asset classes and derivatives, as it enables a more accurate assessment of risk through simulation of numerous potential future states of the world based on user-defined parameters.

In contrast, the other options relate to limitations that do not apply to Monte Carlo VAR. The requirement for specific distribution assumptions can often restrict other methods but is not a concern for this approach. Similarly, being constrained only to simple portfolios or traditional assets doesn't capture the versatile application of Monte Carlo methods across diverse and complex financial instruments.