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Predicting By Learning: An Adaptive Rationale

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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)

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.

Suggested Citation

  • Kaihua Deng, 2015. "Predicting By Learning: An Adaptive Rationale," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-14, December.
  • Handle: RePEc:wsi:afexxx:v:10:y:2015:i:02:n:s2010495215500177
    DOI: 10.1142/S2010495215500177
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    References listed on IDEAS

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