Measuring Fund Strategy and Performance in Changing Economic Conditions




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    • Ferson is from the University of Washington School of Business Administration, Department of Finance and Business Economics DJ-10, Seattle, Washington 98195, and Schadt is from the Edwin L. Cox School of Business, Southern Methodist University, Dallas, Texas 75275-0333. We thank numerous colleagues for comments and helpful discussions, including Connie Becker, David P. Brown, Stephen Brown, Jon Christopherson, John Cochrane, William Goetzmann, Mark Grinblatt, Campbell Harvey, Ravi Jagannathan, Debbie Lucas, Jianping Mei, Ed Rice, the editor René Stulz, Bill Sharpe, Andy Siegel, Karl Snow, and an anonymous referee. Vincent Warther deserves special recognition for providing some of the empirical analysis described herein, and David Modest and Peter Knez deserve thanks for supplying some of the data. This paper was presented in workshops at the Universities of Alberta, Arizona State, British Columbia, California at Los Angeles, Chicago, Notre Dame, Oklahoma, Washington, and at J. P. Morgan Investment Management, and at the following conferences: the 1993 European Finance Association, the 1994 National Bureau of Economic Research Summer Institute, the third annual Osaka Conference on Finance, the 1994 Southwestern Finance Association and the 1994 Western Finance Association. Ferson acknowledges financial support from the Pigott-Paccar professorship at the University of Washington.


The use of predetermined variables to represent public information and time-variation has produced new insights about asset pricing models, but the literature on mutual fund performance has not exploited these insights. This paper advocates conditional performance evaluation in which the relevant expectations are conditioned on public information variables. We modify several classical performance measures to this end and find that the predetermined variables are both statistically and economically significant. Conditioning on public information controls for biases in traditional market timing models and makes the average performance of the mutual funds in our sample look better.