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在我国股票市场发展日趋成熟的今天,股票价格的波动率作为度量股市风险的最重要的一个工具,一直备受经济金融各界的广泛关注。而其中,股票价格的波动集聚性是股票市场波动规律中最明显的特征之一。该文针对我国沪市股市所有综合指数、行业指数及部分个股,以上证指数日收盘价为样本,基于2002年1月4日至2012年3月23日的收盘价数据利用广义自回归条件异方差模型(GARCH)对上证指数的波动进行拟合,结果表明,广义自回归条件异方差模型(GARCH)对我国股市波动具有较好的拟合效果。
As China’s stock market matures, the volatility of stock prices, as one of the most important tools for measuring the risk of the stock market, has been widely concerned by all sectors of the economy and finance. Among them, the volatility of stock prices is one of the most obvious features of the stock market volatility. In this paper, all the composite indices, industry indices and some individual stocks of Shanghai Stock Market are sampled. Based on the daily closing prices of Shanghai Stock Index, based on the closing price data from January 4, 2002 to March 23, 2012, Variance model (GARCH) to fit the volatility of the Shanghai Composite Index, the results show that the generalized autoregressive conditional heteroscedasticity model (GARCH) on China’s stock market volatility has a good fitting effect.