Spurious Regressions in Financial Economics?


  • Wayne E. Ferson,

  • Sergei Sarkissian,

  • Timothy T. Simin

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    • Ferson is at the Carroll School of Management, Boston College and is a Research Associate, National Bureau of Economic Research; Sarkissian is on the Faculty of Management, McGill University; Simin is at the Smeal College of Business, Pennsylvania State University. We are grateful to Eugene Fama for suggesting the question that motivates this research and to John Cochrane, Frank Diebold, Richard C. Green, Gordon Hanka, Raymond Kan, Donald Keim, Jeffrey Pontiff, Bill Schwert, Rossen Valkanov, and an anonymous referee for helpful comments. Ferson acknowledges financial support from the Pigott-Paccar professorship at the University of Washington and the Collins Chair in Finance at Boston College. Sarkissian acknowledges financial support from FCAR and IFM2. This paper has benefited from workshops at McGill University, at the July 2000 NBER Asset Pricing Group, the 2000 Northern Finance Association Meetings, and the 2001 American Finance Association Meetings.


Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of Yule (1926) and Granger and Newbold (1974). Data mining for predictor variables interacts with spurious regression bias. The two effects reinforce each other, because more highly persistent series are more likely to be found significant in the search for predictor variables. Our simulations suggest that many of the regressions in the literature, based on individual predictor variables, may be spurious.