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Learning to forecast the exchange rate: Two competing approaches

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  • De Grauwe, Paul
  • Markiewicz, Agnieszka

Abstract

This paper compares two competing approaches to model foreign exchange market participants' behavior: statistical learning and fitness learning. These learning mechanisms are applied to a set of predictors: chartist and fundamentalist rules. We examine which of the learning approaches is best in terms of replicating the exchange rate dynamics within the framework of a standard asset pricing model. We find that both learning methods reveal the fundamental value of the exchange rate in the equilibrium but only fitness learning creates the disconnection phenomenon and only statistical learning replicates volatility clustering. None of the mechanisms is able to produce a unit root process but both of them generate non-normally distributed returns.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of International Money and Finance.

Volume (Year): 32 (2013)
Issue (Month): C ()
Pages: 42-76

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Handle: RePEc:eee:jimfin:v:32:y:2013:i:c:p:42-76

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Web page: http://www.elsevier.com/locate/inca/30443

Related research

Keywords: Exchange rates; Adaptive learning; Bounded rationality;

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References

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Citations

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Cited by:
  1. ter Ellen, Saskia & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2013. "Dynamic expectation formation in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 75-97.
  2. Lewis Vivien & Markiewicz Agnieszka, 2009. "Model Misspecification, Learning and the Exchange Rate Disconnect Puzzle," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-24, April.
  3. Teneng, Dean, 2013. "Outperforming the naïve Random Walk forecast of foreign exchange daily closing prices using Variance Gamma and normal inverse Gaussian Levy processes," MPRA Paper 47851, University Library of Munich, Germany.
  4. Hommes, C.H., 2007. "Bounded Rationality and Learning in Complex Markets," CeNDEF Working Papers 07-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  5. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.
  6. de Zwart, Gerben & Markwat, Thijs & Swinkels, Laurens & van Dijk, Dick, 2009. "The economic value of fundamental and technical information in emerging currency markets," Journal of International Money and Finance, Elsevier, vol. 28(4), pages 581-604, June.
  7. Carlos Eduardo Iwai Drumond & Gilberto Tadeu Lim, 2014. "Exchange Rate Dynamics With Heterogeneous Expectations," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41th Brazilian Economics Meeting] 108, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
  8. Kim, Young Se, 2009. "Exchange rates and fundamentals under adaptive learning," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 843-863, April.
  9. Mikael Bask, 2009. "Announcement effects on exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(1), pages 64-84.

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