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中国股票不同风险指标下的周度特质动量

文章 arXiv papers · 作者: Huai-Long Shi et al.
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总结

该研究使用原始收益、特质收益和不同的特质风险指标，比较中国市场的周度股票动量策略。样本涵盖 1997 年 1 月至 2017 年 12 月的个股 A 股数据。作者先评估动量和反转模式，再通过单变量投资组合分析，考察风险指标能否预测收益，并比较根据这些指标构建的动量组合。

论文报告了整体反转效应和特质动量效应。大多数特质风险指标与横截面收益负相关，而基于波动率和最大回撤的信号表现更强，对广义特质动量组合的解释力也更好。作者还指出，市场上涨、流动性较强和投资者情绪高涨时，这些策略的盈利能力更高。证据仅适用于中国 A 股市场和历史样本；现有摘要不能证明结果在其他市场或时期持续存在，也不能证明计入实施成本后仍然成立。

核心观点

  • 研究比较中国 A 股中基于原始收益和特质收益的周度动量。
  • 样本中同时出现反转行为和特质动量效应。
  • 特质波动率和最大回撤与更强的风险型动量表现相关。
  • 策略盈利能力与上涨市场、流动性和投资者情绪有关。
  • 研究发现基于中国股票历史样本，可能无法推广到其他市场。

标签

股票中国市场动量因子投资市场情绪
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# 1910.13115


# Horse race of weekly idiosyncratic momentum strategies with respect to various risk metrics: Evidence from the Chinese stock market









This paper focuses on the horse race of weekly idiosyncratic momentum (IMOM) with respect to various idiosyncratic risk metrics. Using the A-share individual stocks in the Chinese market from January 1997 to December 2017, we first evaluate the performance of the weekly momentum based on raw returns and idiosyncratic returns, respectively. After that the univariate portfolio analysis is conducted to investigate the return predictability with respect to various idiosyncratic risk metrics. Further, we perform a comparative study on the performance of the IMOM portfolios with respect to various risk metrics. At last, we explore the possible explanations to IMOM as well as risk based IMOM portfolios. We find that 1) there are prevailing contrarian effect and IMOM effect for the whole sample; 2) the negative relations exist between most of the idiosyncratic risk metrics and the cross-sectional stock returns, and better performance is linked to idiosyncratic volatility (IVol) and maximum drawdowns (IMDs); 3) additionally, the IVol-based and IMD-based IMOM portfolios exhibit better explanatory power to the IMOM portfolios with respect to other risk metrics; 4) finally, higher profitability of IMOM as well as IVol-based and IMD-based IMOM portfolios is found to be related to upside market states, high levels of liquidity and high levels of investor sentiment.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。