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【JFE】一个趋势因子:利用投资期限信息能够获利吗?

[发布日期]:2016-12-09  [浏览次数]:

Journal of Financial Economics, Volume 122, Issue 2, November 2016, Pages 352-375, ISSN 0304-405X

作者:Yufeng Han (Belk College of Business, University of North Carolina), Guofu Zhou (Olin School of Business, Washington University; China Academy of Financial Research; China Economics and Management Academy), Yingzi Zhu (School of Economics and Management, Tsinghua University)

摘要:本文通过一般均衡模型,利用不同投资期限中的移动平均股价信息,提供了一个趋势因子,该因子可以同时捕捉短期、中长期和长期三种期限下的股价趋势。该趋势因子基本上超过了众所周知的短期反转因子、动量因子和长期反转因子(这三个因子分别基于三种股价趋势),其夏普比率是这三个因子的两倍。在最近的金融危机中,趋势因子的月收益率为0.75%,而市场为-2.03%,短期反转因子为-0.82%,动量因子为-3.88%,长期反转因子为0.03%。在进行了另外的构造方式和控制了其他变量后,趋势因子的表现仍然稳健。从资产定价的角度来看,趋势因子在解释股票的横截面收益率上也表现良好。

关键词:趋势,移动平均,信息不对称,可预测性,动量,因子模型

A trend factor: Any economic gains from using information over investment horizons?

Yufeng Han (Belk College of Business, University of North Carolina), Guofu Zhou (Olin School of Business, Washington University; China Academy of Financial Research; China Economics and Management Academy), Yingzi Zhu (School of Economics and Management, Tsinghua University)

ABSTRACT

In this paper, we provide a trend factor that captures simultaneously all three stock price trends: the short-, intermediate-, and long-term, by exploiting information in moving average prices of various time lengths whose predictive power is justified by a proposed general equilibrium model. It outperforms substantially the well-known short-term reversal, momentum, and long-term reversal factors, which are based on the three price trends separately, by more than doubling their Sharpe ratios. During the recent financial crisis, the trend factor earns 0.75% per month, while the market loses ? 2.03 % per month, the short-term reversal factor loses ? 0.82 % , the momentum factor loses ? 3.88 % , and the long-term reversal factor barely gains 0.03%. The performance of the trend factor is robust to alternative formations and to a variety of control variables. From an asset pricing perspective, it also performs well in explaining cross-section stock returns.

Keywords: Trends; Moving averages; Asymmetric information; Predictability; Momentum; Factor models

原文链接:http://www.sciencedirect.com/science/article/pii/S0304405X16301271

翻译:吴雨玲



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