Capturing value-at-risk in futures markets: a revised filtered historical simulation approach

Chang-Cheng Changchien, Chu-Hsiung Lin and Wei-Shun Kao

Abstract

ABSTRACT

This study modifies the filtered historical simulation developed by Barone-Adesi et al, using a general power weighted moving average estimator simulation to forecast value-at-risk (VaR). Our proposed approach is relatively simple and computationally straightforward compared with those of McNeil and Frey and Barone-Adesi et al. Using backtesting of historical daily return series of five futures prices, we show that our proposed method, in terms of unconditional coverage test, would provide an improvement in the precision of VaR forecasts in times of subprime mortgage crisis.