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上证A股收益率分布特征的挖掘分析 被引量:1

Mining Analysis on Stock Return Distribution Characteristic of Shanghai A Shares
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摘要 基于上证A股的每日、周、月行情数据建立数据库系统,采用统计方法进行数据挖掘研究,挖掘研究不同时间范围、时间刻度和股票行业对股票收益率分布的影响.从单只股票截面,对股票收益率密度分布进行正态性检验,分析其分布特征与股票流通市值、股票行业类别以及所研究的时间刻度(日、周、月)的关系.从单位时间截面,对股票集合的收益率均值和波动率的相关统计特征进行分析,研究结果表明,股票集合的收益率均值的方差远大于单只股票截面的收益率均值的方差,这是因为股票之间的相关性远大于时间之间的相关性;另外,股票集合的波动率还具有长期记忆性的特征. Based on the daily, weekly, and monthly market data of Shanghai A shares, this study uses statistical methods to carry on the data mining research, in order to learn the influence of different horizon, time scale, and stock industry on the distribution of stock returns. From single stock section, it performs the test of normality for the density distribution of price yield and analyzes the relationship between its distribution characteristics, and the circulation market value, the industry category of the stock and the time scale(day, week, and month) respectively. From the unit time section, the study analyzes the relevant statistical characteristics of the mean and volatility of the yield of the stock portfolio. The results show that the variance of the mean of the yield of the stock portfolio is much larger than that of the single stock section because the correlation between the stocks is much larger than the correlation between the time. In addition, the volatility of the stock set also has long-term memory characteristics.
作者 刘宇欣 范宏
出处 《计算机系统应用》 2018年第2期163-168,共6页 Computer Systems & Applications
基金 国家自然科学基金(71371046)
关键词 上证A股 股票收益率 相关性 波动率 长期记忆性 Shanghai A shares stock return correlation volatility long memory
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