Does Learning Help Explain Momentum?

摘要：

Using a simple reduced-form model that focuses on beta uncertainty, this paper investigates empirically whether rational learning can help explain momentum. My findings suggest that at the qualitative level, learning can rationalize a number of puzzling results on momentum. However, to achieve the success of quantitatively matching the magnitude of the momentum payo., it requires that the ranking-period events that produce winners or losers induce high uncertainty about the systematic risk estimates for these stocks. A key challenge for the learning explanation is that the required beta uncertainty appears too high.

作者: Kevin Q. Wang

作者单位: Joseph L.Rotman School of Management University of Toronto 105 St George Street Toronto,Ontario M5S 3E6,Canada

会议类型: 国际会议

会议名称: 2008年中国金融国际年会

会议地点: 大连

会议语种:英文

页码: 1-37

在线出版日期: 2008-07-02（万方平台首次上网日期，不代表论文的发表时间）