Value at Risk – Historical Simulation

Historical simulation is a non-parametric approach of estimating VaR, i.e. the returns are not subjected to any functional distribution. VaR is estimated directly from the data without deriving parameters or making assumptions about the entire distribution of the data. This methodology is based on the premise that the pattern of historical returns is indicative of…Read moreRead more

Value at Risk – Methods – Variance Covariance

This method assumes that the daily returns follow a normal distribution. From the distribution of daily returns we estimate the standard deviation (σ). The daily VaR is simply a function of the standard deviation and the desired confidence level. For example, at the 99% confidence level the VaR is equal to 2.33 × σ. To…Read moreRead more

Value at Risk – VaR

VaR is a market risk measurement approach that uses the statistical analysis of historical market trends and volatilities to estimate the likelihood that a given portfolio’s losses will exceed a certain amount. It measures the largest loss likely to be suffered on a portfolio position over a holding period (usually 1 to 10 days) with…Read moreRead more