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| 基于波动和收益分解的股市风险收益关系检验——以2003—2012年上证指数高频数据为例 |
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张 虎，周 迪
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中南财经政法大学 统计与数学学院，武汉 430074
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| 摘要: |
| 基于非参数高频数据的跳跃检验以及方差分解方法，将股指收益和波动都分解为正负方向的连续、跳跃成分，并对2003—2012年上证指数的风险与收益关系进行检验，分析结果表明：上证综指跳跃发生天数占总天数的11.99%，平均跳跃强度为1.1次，正负跳跃存在非对称性，负向（向下）跳跃对跳跃方差的贡献比正向（向上）跳跃大；已实现方差在不同时间范围对收益都没有解释效力，分解的各风险因子只在中期（一周）对收益有较好的预测作用；不同成分的风险收益权衡关系是不一致的，各上行风险都得到负的风险溢酬，而各下跌风险都得到正的风险溢酬；我国股市中存在显著的杠杆效应，收益对波动非对称性的效应主要来自连续收益的贡献，而非跳跃收益。 |
| 关键词: 日内跳跃检验 波动分解 收益分解 风险收益权衡 波动非对称性 杠杆效应 风险溢酬 高频数据 |
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| Test of the Relation between Risk and Return of China’s Stock Market Based on Volatility and Earnings Decomposition—Taking High Frequent Data of Shanghai Composite Index during 2003—2012 as an Example |
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ZHANG Hu，ZHOU Di
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School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430074,China
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| Abstract: |
| Based on the jumping test and variance decomposition method of non-parametric frequency data, the stock index returns and volatility are both decomposed into successive and jumping ingredients with positive and negative directions, and the relation between the risk and the return of Shanghai index during 2003—2012 was tested. The analysis results show that the jumping days of Shanghai Composite Index take 11.99% of the total number of days between 2003—2012, that the average jumping intensity is 1.1 times, that there is asymmetrical feature between positive and negative jumps, that the contribution of downward jumps to jump variance is bigger than that of forward jumps, that the realized variance can not explain the return in different times ranges, that each decomposed risk factor can play better forecast role in earnings in the medium term （in one week）, that the tradeoff relation between the risk and the return in different compositions is different, that each of upside risks has negative risk premium while each of the downside risks has positive risk premium. There is significant leverage effect in China’s stock market, and the asymmetrical effect of the return on volatility mainly results from the contribution of consecutive return but not from jumping return. |
| Key words: intraday jumping test volatility decomposition return decomposition risk-return tradeoff volatility asymmetry leverage effect risk premium high frequent data |
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