| GARCH模型在中国股票波动预测中的应用 |
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| 引用本文： | 康建林,朱开永,周圣武,韩苗.GARCH模型在中国股票波动预测中的应用[J].赣南师范学院学报,2005,26(3):29-32. |
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| 作者姓名： | 康建林 朱开永 周圣武 韩苗 |
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| 作者单位： | 中国矿业大学,理学院应用数学系,江苏,徐州,221008 |
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| 摘 要： | 大量的实证研究表明诸如股票价格等经济类时间序列具有方差随时间变化即异方差的特点.目前被认为最集中地反映了方差变化特点而被广泛地应用在金融时间序列上的模型为广义自回归条件异方差(GARCH)模型.应用GARCH模型对我国股票波动率进行应用预测分析,结果表明模型对波动率进行了很好的预测.这对股票投资者尤其短期交易者具有指导意义.
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| 关 键 词： | GARCH 波动率 预测 |
| 文章编号： | 1004-8332(2005)03-0029-04 |
| 修稿时间： | 2004年10月17 |
Applying GARCH Model to Forecast Chinese Stock Volatility |
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| KANG Jian-lin,ZHU Kai-yong,ZHOU Sheng-wu,HAN Miao.Applying GARCH Model to Forecast Chinese Stock Volatility[J].Journal of Gannan Teachers' College(Social Science(2)),2005,26(3):29-32. |
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| Authors: | KANG Jian-lin ZHU Kai-yong ZHOU Sheng-wu HAN Miao |
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| Abstract: | A lot of research indicates that economic time series, such as stock price etc, have variance up to time change i.e. heteroskedastic. At present, the model that is thinked to reflect variance change characteristics broadly is generalized autoregressive conditional heteroskedastic(GARCH),which has been widely used in financial time series. The paper applies GARCH model to forecast stock volatility in Chinese stock markets. The conclusion reveals that the model predicts well. It has directive significance to the stock investors especially short-term traders. |
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| Keywords: | GARCH volatility forecast |
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