What does Monte Carlo VAR generate?

Monte Carlo Value at Risk (VaR) generates random outcomes according to assumed probability distributions. This method utilizes simulations to produce a range of potential future portfolio values based on the statistical properties of asset returns, such as their mean and standard deviation. By sampling from these probability distributions, it can simulate the possible returns of a portfolio over a specified time horizon and provide an estimate of the risk of loss.

This approach is particularly valuable because it allows for the incorporation of complex features in return distributions, such as non-linear characteristics and fat tails, which are often present in financial markets. By analyzing a large number of simulated outcomes, analysts can assess the impact of various risk factors and develop a comprehensive view of potential losses at different confidence levels.

Other options do not accurately capture what Monte Carlo VaR offers: expected returns based on historical prices focus on past performance without the forward-looking simulations that Monte Carlo methods provide. Fixed outcomes from past performance ignore the inherent variability of future returns. Conservative estimates of risk exposure may not reflect the full range of potential outcomes that Monte Carlo simulations can reveal, as it emphasizes a more cautious approach rather than the probabilistic nature of the simulations.