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Why is it so difficult to beat the random walk forecast of exchange rates?

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  • Kilian, Lutz
  • Taylor, Mark P.

Abstract

We propose a stylized exchange rate model based on diversity and weight ofopinion. Our model departs from standard assumptions in that we allow forheterogeneous agents. We show that such a model can explain both the observedvolatility and the persistence of real and nominal exchange rate movements and thusin some measure resolves Rogoffs (1996) purchasing power parity puzzle. Ourempirical analysis reconciles the well-known difficulties in beating the random walkforecast model with the statistical evidence of nonlinear mean reversion in deviationsfrom fundamentals. We find strong evidence of long-horizon predictability both intheory and in practice. We also explain why it is difficult to exploit this predictabilityin out-of-sample forecasts. Our results not only lend support to economists' beliefsthat the exchange rate is inherently predictable, but they also help us to understandthe reluctance of applied forecasters to abandon chartists methods in favor ofmodels based on economic fundamentals.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of International Economics.

Volume (Year): 60 (2003)
Issue (Month): 1 (May)
Pages: 85-107

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Handle: RePEc:eee:inecon:v:60:y:2003:i:1:p:85-107

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Web page: http://www.elsevier.com/locate/inca/505552

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  4. Jeffrey A. Frankel and Andrew K. Rose., 1995. "A Survey of Empirical Research on Nominal Exchange Rates," Center for International and Development Economics Research (CIDER) Working Papers C95-051, University of California at Berkeley.
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  7. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-45, August.
  8. Peel, David & Sarno, Lucio & Taylor, Mark P, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Towards a Solution to the Purchasing Power Parity Puzzles," CEPR Discussion Papers 2658, C.E.P.R. Discussion Papers.
  9. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
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  11. De Long, J. Bradford & Shleifer, Andrei & Summers, Lawrence H. & Waldmann, Robert J., 1990. "Noise Trader Risk in Financial Markets," Scholarly Articles 3725552, Harvard University Department of Economics.
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  13. Berben, R-P. & van Dijk, D.J.C., 1998. "Does the absence of cointegration explain the typical findings in long horizon regressions?," Econometric Institute Research Papers EI 9814, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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  21. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
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