基于EWMA模型和GARCH模型对于股指波动率的预测在我国，伴随着近几年来我国股票市场的迅速发展，我国股票市场在金融体系中的地位愈来愈发重要，所以，认真分析风险的大小、努力做好风险防控的准备对于股票市场的稳定有不可缺少的作用。因而，金融资产波动率的大小是衡量金融风险的重要内容，预测股票波动率便可以在一定程度上预测股票未来波动，为投资者和研究员提供更加准确无误的投资和研究方向，进而做到一定程度地防范风险。如今投资者和研究员们对股票波动率研究类型上已经获得了许多成果，建立了许多模型，但是美中不足的是这些模型在预测的精确性方面还有不少欠缺，因此，本文以上证300为研究样本，建立了GARCH和EWMA模型相互验证来预测股票波动率。在最后还加入了ARCH模型作为辅助。 投资者们建立的波动率预测的数学模型越来越丰富和完善，也意味着波动率模型的理论内容越加完善，因而在现实生活中所发挥的作用也越来越大。本文也介绍了波动率的相关内容。当前已建立的波动率预测模型可以分为两大种类：其一是利用股票市场价格的历史数据来预测未来的波动率，即为历史信息方法；其二便是将股票市场上的期权价格代入公式运算后反推计算出的波动率，即为计算隐含波动率的方法。本文采用的GARCH和EWMA模型属于历史信息法，由于此模型构造较为简易数据方便得到而被广大投资者使用。最后的波动率预测结论也是较为科学的，因为将EWMA模型和GARCH模型的预测结果放在一起进行验证，得到趋势波动是基本相符的。 关键词：波动率预测；GARCH模型；EWMA模型; ABSTRACT In China, with the rapid development of China's stock market in recent years, the position of China's stock market in the financial system is becoming more and more important. Therefore, it is indispensable for the stability of the stock market to carefully analyze the size of risk and make efforts to prepare for risk prevention and control. Therefore, the volatility of financial assets is an important content to measure financial risks. Predicting the volatility of stocks can predict the future volatility of stocks to a certain extent, and provide investors and researchers with more accurate investment and research direction, so as to prevent risks to a certain extent. Nowadays, investors and researchers have made a lot of achievements on the types of research on stock volatility, and established many models. However, there are still many deficiencies in the accuracy of these models. Therefore, this paper takes the above 300 samples as the research sample, and establishes GARCH and EWMA models to verify each other to predict stock volatility. In the end, ARCH model is added as an assistant. The mathematical models of Volatility Prediction established by investors are more and more abundant and perfect, which also means that the theoretical content of volatility model is more and more perfect, so it plays an increasingly important role in real life. This paper also introduces the related content of volatility. At present, the established volatility prediction models can be divided into two categories: one is to use the historical data of the stock market price to predict the future volatility, that is, the historical information method; the other is to put the option price in the stock market into the formula to calculate the volatility, that is, to calculate the implied volatility. The GARCH and EWMA models used in this paper belong to the historical information method. Because this model is easy to construct and the data is easy to get, it is widely used by investors. The final Volatility Prediction conclusion is also more scientific, because the prediction results of EWMA model and GARCH model are put together for verification, and the trend fluctuation is basically consistent Keywords:volatility forecast; GARCH; EWMA；Risk prevention and control 目 录 摘 要 1 一、绪论 1 （一）研究背景 1 （二）研究意义 2 1.理论意义 2 2.现实意义 2 （三）研究现状 3 （四）本文创新和难点 3 1.创新点 3 2．研究的难点 3 二、理论介绍 3 （一）波动率 3 1．波动率定义介绍 3 2．股票波动率产生的原因及特征分析 4 3．股票价格波动周期性 4 4．股票波动率产生的原因分析 5 （二）加权模型 6 三、EWMA模型和GARCH模型介绍 6 （一）指数加权移动平均模型（EWMA模型） 6 （二） GARCH（P,Q）模型 7 四、上证50波动率实证研究 7 五、结论 9 （一）结论 9 （二）展望 9
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