In-sample vs. out-of-sample tests of stock return predictability in the context of data mining |
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| Institution: | 1. Department of Economics, Saint Louis University, 3674 Lindell Boulevard, Saint Louis, MO 63108-3397, United States;2. Department of Economics, University of Nebraska at Omaha, RH-512K, Omaha, NE 68182-0286, United States;1. University of Notre Dame, USA;2. Department of Economics and Finance, University of Guelph, Guelph, Ontario, Canada N1G 2W1;1. Institute of Mathematics & Statistics, University of St. Gallen, Switzerland;2. School of Economics & Political Science, University of St. Gallen, Switzerland;1. Department of Economics, Strathclyde Business School, University of Strathclyde, Glasgow, G4 0QU, United Kingdom;2. Edinburgh Business School, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom;3. Faculty of Humanities and Social Sciences, Okayama University, Okayama-ken, Japan and Keio Economic Observatory, Keio University, Tokyo, Japan |
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| Abstract: | We undertake an extensive analysis of in-sample and out-of-sample tests of stock return predictability in an effort to better understand the nature of the empirical evidence on return predictability. We find that a number of financial variables appearing in the literature display both in-sample and out-of-sample predictive ability with respect to stock returns in annual data covering most of the twentieth century. In contrast to the extant literature, we demonstrate that there is little discrepancy between in-sample and out-of-sample test results once we employ out-of-sample tests with good power. While conventional wisdom holds that out-of-sample tests help guard against data mining, Inoue and Kilian Inoue, A., Kilian, L., 2004. In-sample or out-of-sample tests of predictability: which one should we use? Econometric Reviews 23, 371–402.] recently argue that in-sample and out-of-sample tests are equally susceptible to data mining biases. Using a bootstrap procedure that explicitly accounts for data mining, we still find that certain financial variables display significant in-sample and out-of-sample predictive ability with respect to stock returns. |
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