What are the three methods to calculate Value at Risk (VaR)?

Value at Risk (VaR) is a widely used risk measure that helps financial institutions assess the potential loss in value of an asset or portfolio over a specified time frame at a given confidence level. The three primary methods to calculate VaR each have distinct approaches and applications:

1. Historical Simulation: This method involves taking actual past return data to simulate the potential future losses. By analyzing historical price changes over a specified period, it generates a distribution of returns that can then be used to determine the VaR at the desired confidence level. This method is particularly powerful because it uses real market data to reflect potential outcomes.

2. Parametric Method (Variance-Covariance Method): This approach assumes that returns are normally distributed. It uses the mean and standard deviation of the portfolio's returns to calculate the VaR through statistical formulas. This method is straightforward and allows for quick calculations, but it may not adequately capture the risk in cases where returns exhibit non-normal characteristics, such as skewness or kurtosis.

3. Monte Carlo Simulation: This method generates a large number of random price paths for the portfolio based on input parameters such as expected return and volatility. By simulating a wide range of potential outcomes, it builds a distribution of