统计研究 ›› 2000, Vol. 17 ›› Issue (1): 49-52.
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刘国旗
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LIU Guo-Qi
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Abstract: This paper studies the performance of the GARCH model and two of its non-linear modifications to forecast China’s weekly stock market volatility. The models are the Quadratic GARCH and the Glosten, Jagannathan and Runkle models which have proposed to describe the often observed negative skewness in stock market indices. We find that the QGARCH model is best when the estimation sample does not contain extreme observations such as the stock market crash and that the GJR model cannot be recommended for forecasting.
刘国旗. 非线性GARCH模型在中国股市波动预测中的应用研究[J]. 统计研究, 2000, 17(1): 49-52.
LIU Guo-Qi. Studying on Non-liner GARCH Models to Forecast China’s Stock Market Volatility[J]. , 2000, 17(1): 49-52.
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https://tjyj.stats.gov.cn/CN/Y2000/V17/I1/49
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