Testing the APT with the Maximum Sharpe Ratio of Extracted Factors

• 成果类型: Article
• 署名作者: Zhang, Chu
• 署名单位: Hong Kong University of Science & Technology
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.1090.1004
• 发表日期: 2009
• 页码: 1255-1266
• 关键词: asymptotic APT; beta pricing errors; Sharpe ratio; Connor-Korajczyk method; EIGENVALUE; eigenvector

摘要

This paper develops a test of the asymptotic arbitrage pricing theory (APT) via the maximum squared Sharpe ratio of the factors extracted from individual stocks using the Connor-Korajczyk method. The test treats the beta pricing relation as approximate without predetermining the systematic factors, unlike the existing tests that take the relationship as exact and systematic factors as given. This paper also examines the magnitude of pricing errors bounded partly by the maximum squared Sharpe ratio. For most 60-month subperiods of the sample, the hypothesis that the maximum squared Sharpe ratio for monthly returns is greater than 0.25 can be rejected. Simulation indicates that the average pricing error in monthly returns is less than 0.001. These results support the asymptotic APT.