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On Predicting Stock Returns with Nearly Integrated Explanatory Variables

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Author Info
Walter Torous (UCLA)
Rossen Valkanov (UCLA)
Shu Yan (The University of Arizona)

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Abstract

Statistical inference in predictive regressions depends critically on the stochastic properties of the posited explanatory variable, in particular, its order of integration. Confidence intervals computed for the largest autoregressive root of many explanatory variables commonly used in predictive regressions, including the dividend yield, the book-to-market ratio, the short-term rate of interest, and the term and default spreads, confirm uncertainty surrounding these variables' order of integration. We investigate the effects of this uncertainty on inferences drawn in predictive regressions. Once this uncertainty is accounted for, contrary to previous evidence, we find reliable evidence of predictability at shorter rather than at longer horizons.

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Publisher Info
Article provided by University of Chicago Press in its journal Journal of Business.

Volume (Year): 77 (2004)
Issue (Month): 4 (October)
Pages: 937-966
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Handle: RePEc:ucp:jnlbus:v:77:y:2004:i:4:p:937-966

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  1. Erik Hjalmarsson, 2006. "New methods for inference in long-run predictive regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  2. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," NBER Working Papers 11468, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  3. Miguel A. Ferreira & Pedro Santa-Clara, 2008. "Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole," NBER Working Papers 14571, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  4. John H. Cochrane, 2006. "The Dog That Did Not Bark: A Defense of Return Predictability," NBER Working Papers 12026, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  5. Benjamin Chiquoine & Erik Hjalmarsson, 2008. "Jackknifing stock return predictions," International Finance Discussion Papers 932, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  6. GIOT, Pierre & PETITJEAN, Mikael, 2006. "The information content of the Bond-Equity Yield Ratio: better than a random walk?," CORE Discussion Papers 2006089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
    Other versions:
  7. David Rey, 2005. "Market Timing And Model Uncertainty: An Exploratory Study For The Swiss Stock Market," Financial Markets and Portfolio Management, Springer, vol. 19(3), pages 239-260, October. [Downloadable!] (restricted)
  8. In Choi & Timothy K. Chue, 2006. "Subsampling-Based Tests of Stock-Return Predictability," Hi-Stat Discussion Paper Series d06-178, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
  9. Borja Larrain & Motohiro Yogo, 2007. "Does Firm Value Move Too Much to be Justified by Subsequent Changes in Cash Flow?," NBER Working Papers 12847, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  10. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR). [Downloadable!]
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