VALUE-AT-RISK WITH TIME VARYING VOLATILITY AND ITS APPLICATION BASED ON EGARCH MODEL

Abstract

This study examines the influence of the current global financial crisis on the market risk exposure of investments in the Indian stock market. Market risk is quantified using the value-at-risk method (VaR). This risk management metric, which financial organizations commonly use, determines the most significant loss that may occur over a specified trading time with a specified level of confidence. Due to the well-documented time-varying volatility of financial time series, standard techniques of calculating VaR frequently underestimate the magnitude of portfolio losses, particularly during periods of high volatility. We use anEGARCH formulation to enhance the volatility forecasts and hence the VaR estimations. VaR is then calculated many times during the out-of-sample period. The results indicate that this method of calculating VaR is more accurate at capturing the real impact of market risk across a range of volatility situations.

Keywords

Value-at-Risk, EGARCH forecasting, back testing, Kupiec test

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