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A Test of Technical Analysis: Matching Time Displaced Generalized Patterns


  • Jimmy Hilliard,

  • Adam Schwartz,

  • James Squire

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    • Jimmy E. Hilliard is Professor of Finance and the Harbert Eminent Scholar at Auburn University in Auburn University, AL. Adam Schwartz is the Lawrence Term Professor of Business Administration at the Williams School of Commerce, Economics and Politics at Washington and Lee University in Lexington, VA. James C. Squire is Professor of Electrical Engineering at Virginia Military Institute in Lexington, VA.

  • The authors would like to thank Bill Christie (Editor) and an anonymous referee for helpful comments and suggestions. The paper has also benefited from the comments received at presentations at the Auburn University Seminar series and the 2011 meeting of the Eastern Finance Association. Professor Hilliard acknowledges the support of Kathryn and Raymond Harbert and Professor Schwartz acknowledges the support of the Lenfest grant program. We are responsible for any errors.


We use a least squares metric to match the return pattern of a target stock with that of an out-of-sample-twin. The twin with the smallest metric is found by a comprehensive period-by-period search of stocks in the Center for Research in Security Prices data set extending back to 1926. If technical analysis has value, targets of twins producing the highest returns in the twin postperiod should also have the highest performance in the target postperiod. Using a randomly selected sample of 66,000 return patterns, we find higher means for targets corresponding to the highest returning twin quintile. We also use regressions to risk adjust target returns and find that twin returns in the postmatch period significantly predict risk-adjusted target returns.