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Robust Tests of Market Efficiency using Statistical Arbitrage

Listed author(s):
  • Melvyn Teo

    (School of Economics and Social Sciences, Singapore Management University)

  • Yiu Kuen Tse


    (School of Economics and Social Sciences, Singapore Management University)

  • Mitch Warachka

    (School of Economics and Social Sciences, Singapore Management University)

This paper develops robust tests of market efficiency using statistical arbitrage which circumvent the joint-hypotheses dilemma confounding the traditional literature. Hogan, Jarrow, Teo and Warachka (2004) identify statistical arbitrage opportunities in momentum and value strategies. However, their results are sensitive to the assumption that expected incremental trading profits are constant. We demonstrate that this empirical discrepancy results from a lack of statistical power in their Bonferroni test procedure. To resolve the disparity, we propose a Min-t test statistic for trading strategies with time-varying expected profits. This procedure is then extended to examine autocorrelated and non-normal trading profit innovations. According to the Min-t statistic, conclusions regarding market efficiency are consistent across various trading profit assumptions. Furthermore, a robust methodology to determine a trading strategy’s convergence rate to arbitrage is provided. Overall, our results confirm the appropriateness of statistical arbitrage as a test of market efficiency.

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Paper provided by Singapore Management University, School of Economics in its series Working Papers with number 12-2004.

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Length: 38 pages
Date of creation: Apr 2004
Publication status: Published in SMU Economics and Statistics Working Paper Series
Handle: RePEc:siu:wpaper:12-2004
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