基于时间序列模型的股票价格波动特性分析  

Analysis of volatility of stick price based on GARCH model

作　　者：张捷[1] 

机构地区：[1]广州大学数学与信息科学学院,广东广州510006

出　　处：《湖南文理学院学报（自然科学版）》2017年第3期4-8,12,共6页Journal of Hunan University of Arts and Science(Science and Technology)

摘　　要：股票市场的波动率问题一直是现代投资学研究的关键问题,是国家监管机构最关注的风险指标。选取股票交易系统中2015—2016年股票东阿阿胶(000423)日收盘价数据,分别从序列水平特征和波动特性2个角度,运用ARIMA模型和GARCH模型,进行股票的短期预测和波动性拟合。结果显示:ARIMA模型对深交所股票东阿阿胶日收盘价的短期预测值与实际值相对误差小,GARCH模型较好地拟合了股票价格,并估计出了风险区间,能为短期投资者和股票决策者提供参考。The research of the stock market’s return volatility, the most concerned measure of the National Regulatory Authorities, is one key issue in the field of modern investment all the while. The reported closing price of DEEJ（000423） cases are collected from 2015 to 2016 in stock trading system. From angles of sequence value and volatility, using ARIMA model and GARCH model respectively, a short-term prediction of the time series is used to simulate the volatility feature of the price. The result shows that the predictions of ARIMA model almost approach the truth. Through the establishment of the GARCH model, reflecting the confidence bounds around risk of the price, which can provide helpful references for the decision-maker or people who care about the change of short-term financial yield.

关 键 词：异方差时间序列分析 ARIMA模型 GARCH模型 波动性风险 

分 类 号：O213[理学—概率论与数理统计]