The Consistency of Size Effect: Time Periods, Regression Methods, and Database Selection

摘要：

We try to reconcile the findings of prior size effect studies by re-examining the issue with different time periods, regression methods, and database selection. We test whether the size effect varies in relation to the time period, whether extreme observations cause the size effect, by experimenting with different regression methods, and whether the survivorship bias in the COMPUSTAT database induces the size effect. It is found that the size effect is highly significant for data from the earlier time period, but its significance is noticeably reduced for the later time period. Extreme returns cannot fully account for the size effect, because the effect remains strong in the earlier time period even when the extreme observations are trimmed. Finally, we do not find any evidence indicating that the survivorship bias in the COMPUSTAT database is responsible for the size effect.

关键词： CAPM Size Effect Survivorship Bias Least Trimmed Squares Method

作者: Robin K. Chou Mei Yueh Huang Jun Biao Lin Jen Tsung Hsu

作者单位: Department of Finance, National Central University, R.O.C. Department of Industrial Management, Lunghwa University of Science and Technology, R.O.C. Department of Money and Banking, National Kaohsiung First University of Science and Technology,R.O.C Department of Finance, Ching Yun University

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）