PREDICTING BY LEARNING: AN ADAPTIVE RATIONALE

Kaihua Deng
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Kaihua Deng: Department of Economics, University of Washington, Seattle, WA 98195-3330, USA2Hanqing Advanced Institute of Economics and Finance, Renmin University of China, Beijing 100872, P. R. China

Annals of Financial Economics (AFE), 2015, vol. 10, issue 02, 1-14

Abstract: The paper proposes a partial-adjustment mechanism for the learning process of economic agents and justify the use of past information in predicting stock returns from four different perspectives. By making a pair of mild assumptions about how rational investors learn about the fundamental values of returns and dividend yield over time, I show that for one-step-ahead forecast a stable and significant improvement in terms of short-horizon R2 can be achieved by recasting the classical single-equation predictive regression in a differenced form and incorporating information from the recent past. For longer horizons, the relationship reduces to the standard form.

Keywords: Dividend yield; long-horizon predictability; partial adjustment; short-horizon predictability (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1142/S2010495215500177

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