|
|
|
|
||||
|
||||
Statistical Arbitrage and Market Efficiency: Enhanced Theory, Robust Tests and Further ApplicationsRobert A. JarrowCornell University - Samuel Curtis Johnson Graduate School of Management Melvyn TeoSingapore Management University - School of Business Yiu Kuen TseSingapore Management University - School of Economics & Social Sciences Mitch WarachkaClaremont Colleges - Robert Day School of Economics and Finance February 2005 Abstract: Statistical arbitrage enables tests of market efficiency which circumvent the joint-hypotheses dilemma. This paper makes several contributions to the statistical arbitrage framework. First, we enlarge the set of statistical arbitrage opportunities in Hogan, Jarrow, Teo, and Warachka (2004) to avoid penalizing incremental trading profits with positive deviations from their expected value. Second, we provide a statistical methodology to remedy the lack of consistency and statistical power in their Bonferroni approach. In addition, this procedure allows for autocorrelation and non-normality in trading profits. Third, we apply our tests to a wide range of trading strategies based on stock momentum, stock value, stock liquidity, and industry momentum. Over 50% of these strategies are found to violate market efficiency. We also identify dominant trading strategies which converge to arbitrage most rapidly.
Number of Pages in PDF File: 54 Keywords: Market Efficiency, Financial Anomalies JEL Classification: G12, G14 working papers seriesDate posted: February 3, 2005Suggested CitationContact Information
|
|
|||||||||||||||||||||||||||||||||
© 2013 Social Science Electronic Publishing, Inc. All Rights Reserved.
FAQ
Terms of Use
Privacy Policy
Copyright
This page was processed by apollo5 in 0.422 seconds
