2009Unpublished venueRequires access

Empirical Analysis of the Market Risk of Chinese Open-Ended Funds Based on GARCH-VaR Models

Jian Wang, Xiaotao Wu, Mingli Zhong

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Abstract

Traditional study has some limitation on GARCH models to describe VAR in a market of great volatility, so the purpose of this paper is to look for an effective GARCH model for measuring VAR value of the market risk of open-ended funds. This paper adopted variance-covariance method and introduced the GARCH series models to calculate the conditional variance for VaR value. The authors used the GARCH models to conduct the empirical research under three different distributions. The result shows that GARCH models under Student T distribution perform best in evaluating VAR value and simulating the market risk in a fluctuate market. The authors suggest that the funds management companies in China should enhance the efficiency of risk control with the help of suitable GARCH models and distribution.

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What this paper is about

Traditional study has some limitation on GARCH models to describe VAR in a market of great volatility, so the purpose of this paper is to look for an effective GARCH model for measuring VAR value of the market risk of open-ended funds. This paper adopted variance-covariance method and introduced the GARCH series models to calculate the conditional variance for VaR value. The authors used the GARCH models to conduct the empirical research under three different distributions. The result shows that GARCH models under Student T distribution perform best in evaluating VAR value and simulating the market risk in a fluctuate market. The authors suggest that the funds management companies in China should enhance the efficiency of risk control with the help of suitable GARCH models and distribution.

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Available abstract

Traditional study has some limitation on GARCH models to describe VAR in a market of great volatility, so the purpose of this paper is to look for an effective GARCH model for measuring VAR value of the market risk of open-ended funds. This paper adopted variance-covariance method and introduced the GARCH series models to calculate the conditional variance for VaR value. The authors used the GARCH models to conduct the empirical research under three different distributions. The result shows that GARCH models under Student T distribution perform best in evaluating VAR value and simulating the market risk in a fluctuate market. The authors suggest that the funds management companies in China should enhance the efficiency of risk control with the help of suitable GARCH models and distribution.

Key concepts: Autoregressive conditional heteroskedasticity, Econometrics, Volatility (finance), Value at risk, Conditional variance, Market risk, Variance (accounting), Economics

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