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Predictive Regressions: A Present-value Approach

  • Jules H. van Binsbergen
  • Ralph S.J. Koijen

We propose a latent variables approach within a present-value model to estimate the expected returns and expected dividend growth rates of the aggregate stock market. This approach aggregates information contained in the history of price-dividend ratios and dividend growth rates to predict future returns and dividend growth rates. We find that returns and dividend growth rates are predictable with R-squared values ranging from 8.2% to 8.9% for returns and 13.9% to 31.6% for dividend growth rates. Both expected returns and expected dividend growth rates have a persistent component, but expected returns are more persistent than expected dividend growth rates.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16263.

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Date of creation: Aug 2010
Date of revision:
Publication status: published as van Binsbergen, Jules H. and Ralph S.J. Koijen, Predictive Regressions: A Present-Value Approach, Journal of Finance, August 2010, 65(4), 1439-1471.
Handle: RePEc:nbr:nberwo:16263
Note: AP HC
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  1. Lubos Pastor & Meenakshi Sinha & Bhaskaran Swaminathan, 2006. "Estimating the Intertemporal Risk-Return Tradeoff Using the Implied Cost of Capital," NBER Working Papers 11941, National Bureau of Economic Research, Inc.
  2. Martin Lettau & Stijn Van Nieuwerburgh, 2008. "Reconciling the Return Predictability Evidence," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1607-1652, July.
  3. Philippe Jorion & William N. Goetzmann, 1998. "A Longer Look at Dividend Yields," Yale School of Management Working Papers ysm41, Yale School of Management.
  4. Geert Bekaert & Steven R. Grenadier, 1999. "Stock and Bond Pricing in an Affine Economy," NBER Working Papers 7346, National Bureau of Economic Research, Inc.
  5. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
  6. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
  7. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
  8. Amit Goval & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," NBER Working Papers 10483, National Bureau of Economic Research, Inc.
  9. Andrew Ang & Jun Liu, 2004. "How to Discount Cashflows with Time-Varying Expected Returns," Journal of Finance, American Finance Association, vol. 59(6), pages 2745-2783, December.
  10. Lubos Pástor & Robert F. Stambaugh, 2009. "Predictive Systems: Living with Imperfect Predictors," Journal of Finance, American Finance Association, vol. 64(4), pages 1583-1628, 08.
  11. Xavier Gabaix, 2007. "Linearity-Generating Processes: A Modelling Tool Yielding Closed Forms for Asset Prices," NBER Working Papers 13430, National Bureau of Economic Research, Inc.
  12. Wayne E. Ferson & Sergei Sarkissian & Timothy Simin, 2002. "Spurious Regressions in Financial Economics?," NBER Working Papers 9143, National Bureau of Economic Research, Inc.
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