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Why so Glum? The Meese-Rogoff Methodology Meets the Stock Market

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  • Flood, Robert P
  • Rose, Andrew K

Abstract

This paper applies the Meese-Rogoff (1983a) methodology to the stock market. We compare the out-of-sample forecasting accuracy of various time-series and fundamentals-based models of aggregate stock prices. We stick as close as possible to the original Meese-Rogoff sample and methodology. Just as Meese and Rogoff found for the case of exchange rates, we find that a random walk model of stock prices performs as well as any estimated model at one to twelve month horizons, even though we base forecasts on actual future fundamentals of dividends and earnings. Using this metric and for this sample period, aggregate stock prices seem to be as difficult to model empirically as exchange rates.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 6714.

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Date of creation: Feb 2008
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Handle: RePEc:cpr:ceprdp:6714

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Keywords: aggregate; dividend; earning; exchange; forecast; fundamental; growth; model; rate;

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References

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  1. Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
  2. Charles Engel & Kenneth D. West, 2003. "Exchange rates and fundamentals," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  3. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
  4. Richard Meese & Kenneth Rogoff, 1983. "The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification?," NBER Chapters, in: Exchange Rates and International Macroeconomics, pages 67-112 National Bureau of Economic Research, Inc.
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Cited by:
  1. Valerie Cerra & Sweta Chaman Saxena, 2008. "The Monetary Model Strikes Back," IMF Working Papers 08/73, International Monetary Fund.

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