我国股票市场高频波动预测研究——基于ARQ及HARQ模型的实证分析

发布时间：2018-05-19 18:30

  本文选题：金融资产 + 证券市场　； 参考：《西南交通大学学报(社会科学版)》2017年04期

【摘要】：利用日内高频交易数据对金融资产收益率的波动率进行建模分析是近年来理论界和实务界共同关注的热点问题。以2005年初到2016年底我国日间HS300指数5分钟高频数据为样本,实证分析以渐进理论为基础的ARQ及HARQ模型对我国股票市场高频波动的预测效果,并与跳跃、跳跃变差及正负向跳跃变差为基础的HAR-RV、HAR-JC、CHAR及SHAR等多种高频波动率预测模型进行比较,发现:ARQ及HARQ模型对我国股票市场具有更高的预测精度。
[Abstract]:The modeling and analysis of volatility of financial asset return by using intraday high-frequency trading data is a hot issue in theory and practice in recent years. Based on the 5-minute high-frequency data of China's daytime HS300 index from the beginning of 2005 to the end of 2016, this paper empirically analyzes the prediction effect of the ARQ and HARQ models based on the progressive theory on the high-frequency volatility of China's stock market, and jumps. Based on the jump variation and the positive and negative jump variation, several kinds of high-frequency volatility prediction models, such as HAR-RVN HAR-JCNCHAR and SHAR, are compared. It is found that the two models have higher prediction accuracy for China's stock market.
【作者单位】： 西南交通大学经济管理学院;
【分类号】：F224;F832.51
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本文编号：1911179