Publication Type

Working Paper

Publication Date

2-2005

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.

Keywords

Market Efficiency, Financial Anomalies

Discipline

Finance and Financial Management | Portfolio and Security Analysis

Research Areas

Finance; Econometrics

First Page

1

Last Page

54

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://ssrn.com/abstract=659941

Comments

Published in Journal of Financial Markets, February 2012, Volume 15, Issue 1, Pages 47-80. http://doi.org/10.1016/j.finmar.2011.08.003

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