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Semi-parametric Estimation and the Predictability of Stock Market Returns: Some Lessons from Japan

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Sentana, Enrique
Wadhwani, Sushil

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Abstract

This paper attempts to explore whether lagged variables that help predict stock returns are merely proxying for mismeasured risk. Therefore, three different ways of measuring risk are employed (i.e., semiparametric, GARCH, and lagged squared returns). In an application to Japanese data, four key predictor variables are shown to have nontrivial additional forecasting power irrespective of how they measure risk. Interestingly, unlike the United States, the level of the lagged dividend yield is not positively correlated with returns in either Japan or South Korea. Copyright 1991 by The Review of Economic Studies Limited.

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Publisher Info
Article provided by Blackwell Publishing in its journal Review of Economic Studies.

Volume (Year): 58 (1991)
Issue (Month): 3 (May)
Pages: 547-63
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Handle: RePEc:bla:restud:v:58:y:1991:i:3:p:547-63

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  1. Jonathan Manton & Anton Muscatelli & Vikram Krishnamurthy & Stan Hurn, . "Modelling Stock Market Excess Returns by Markov Modulated Gaussian Noise," Working Papers 9806, Department of Economics, University of Glasgow. [Downloadable!]
  2. Marquering, W. & Verbeek, M., 2000. "The economic value of predicting stock index returns and volatility," Discussion Paper 78, Tilburg University, Center for Economic Research. [Downloadable!]
  3. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO. [Downloadable!]
  4. Benoit Perron, 2002. "Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off," CIRANO Working Papers 2002s-88, CIRANO. [Downloadable!]
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  5. Peter F. Christoffersen & Francis X. Diebold, 2003. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," NBER Working Papers 10009, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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