Publication Type
Working Paper
Version
publishedVersion
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
Citation
JARROW, Robert A.; TEO, Melvyn; TSE, Yiu Kuen; and WARACHKA, Mitch.
Statistical Arbitrage and Market Efficiency: Enhanced Theory, Robust Tests and Further Applications. (2005). 1-54.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/3168
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International 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