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Learning to Forecast the Exchange Rate: Two Competing Approaches

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Author Info
Paul De Grauwe (KULeuven)
Agnieszka Markiewicz (KULeuven)

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Abstract

In this paper, we investigate the behavior of the exchange rate within the framework of an asset pricing model. We assume boundedly rational agents who use simple rules to forecast the future exchange rate. They test these rules continuously using two learning mechanisms. The first one, the fitness method, assumes that agents evaluate forecasts by computing their past profitability. In the second mechanism, agents learn to improve these rules using statistical methods. First, we find that both learning mechanisms reveal the fundamental value of the exchange rate in the steady state. Second, both mechanisms mimic regularities observed in the foreign exchange markets, namely exchange rate disconnect and excess volatility. Fitness learning rule generates the disconnection at different frequencies, while the statistical method has this ability only at the high frequencies. Statistical learning can produce excess volatility of magnitude closer to reality than fitness learning but can also lead to explosive solutions

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 367.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:367

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Related research
Keywords: Exchange Rate Economics; Adaptive Learning; Behavioral Finance;

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Find related papers by JEL classification:
F31 - International Economics - - International Finance - - - Foreign Exchange
F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  7. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, vol. 108(1), pages 137-56, February. [Downloadable!] (restricted)
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  16. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics 0510022, EconWPA. [Downloadable!]
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  17. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Vivien Lewis & Agnieszka Markiewicz, 2009. "Model misspecification, learning and the exchange rate disconnect puzzle," Research series 200907-01, National Bank of Belgium. [Downloadable!]
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  2. 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. [Downloadable!]
  3. Mikael Bask, 2009. "Announcement effects on exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(1), pages 64-84. [Downloadable!]
  4. Zwart, G.J. de & Markwat, T.D. & Swinkels, L. & Dijk, D.J.C. van, 2007. "The Economic Value of Fundamental and Technical Information in Emerging Currency Markets," Research Paper ERS-2007-096-F&A Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
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