The Historical Simulation Method with Time-varying Volatility for Value-at-Risk Estimation

Abstract

This study proposes a two-stage approach combining the Power EWMA estimator with the historical simulation when estimating Value-at-Risk. Our method can avoid estimating parameters to forecast the variance when using GARCH model and retains the easy usages characteristic of the historical simulation approach. In addition, we also use the kurtosis coefficients to estimate the distribution form for capturing the time-varying volatility. In the light of results of the failure rates and Kupiec test, the empirical result shows that the proposed method can onsiderably enhance the estimation accuracy of Value-at-Risk. Key words: Value at Risk, Historical Simulation, GARCH Model, EWMA