CVaR-EGARCH-GED Model and Its Application in Chinese Financial Field

机译：CVaR-EGARCH-GED模型及其在中国金融领域的应用

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Conditional value at risk (CVaR) is a kind of method to measure the financial asset risk and it improved value at risk (VaR); EGARCH model is used to simulate the volatility (heteroskedasticity) which can measure the financial asset risk dynamically; For the leptokurtic and heavy tail of the return series, this paper use Generalized error distribution (GED) to fit the return distribution; The model which compute CVaR value by EGARCH-GED model that we call it CVaR-EGARCH-GED model. Then we make empirical analysis for the Shanghai and Shenzhen Stock market index. The results showed that: CVaR-EGARCH-GED model can fit and forecast Chinese two stock markets' index well. It should to be an effective tool for risk management in Chinese stock markets especially in Shenzhen stock market.

机译：条件风险价值（CVaR）是一种衡量金融资产风险的方法，它提高了风险价值（VaR）; EGARCH模型用于模拟可动态测量金融资产风险的波动率（异方差）;对于返回序列的轻骑兵和沉重的尾巴，本文使用广义误差分布（GED）来拟合返回分布。通过EGARCH-GED模型计算CVaR值的模型，我们称之为CVaR-EGARCH-GED模型。然后，我们对上海和深圳股市指数进行了实证分析。结果表明：CVaR-EGARCH-GED模型可以很好地拟合和预测中国两个股市的指数。它应该成为中国股票市场（尤其是深圳股票市场）风险管理的有效工具。

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《2008年国际应用统计学术研讨会（2008 International Institute of Applied Statistics Studies）论文集》|2008年|1-5|共5页
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LI Weidong; LI Shushan;
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中图分类 FO;
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Value at Risk (VaR); Conditional Value at Risk (CVaR); EGARCH Model; Generalized Error Distribution (GED);

机译：风险价值（VaR）;条件风险价值（CVaR）; EGARCH模型;广义误差分布（GED）;

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CVaR-EGARCH-GED Model and Its Application in Chinese Financial Field

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