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Dynamic Forecasting Rules and the Complexity of Exchange Rate Dynamics

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  • Hans Dewachter
  • Romain Houssa
  • Marco Lyrio
  • Pablo Rovira Kaltwasser

Abstract

This paper investigates the exchange rate dynamics implied by a heterogeneous agent model proposed in De Grauwe and Grimaldi (2006). The two groups of agents, chartists and fundamentalists, use simple forecasting rules and the ex post relative profitability to decide whether to switch to the other group. We extend this model by introducing a simple evolutionary selection mechanism which allows agents not only to switch between groups but also to adapt the forecasting rule of each group over time. This selection process naturally leads agents to choose forecasting rules over time which results in the convergence of the exchange rate to its fundamental value. However, our learning rule is not robust to the introduction of shocks to the fundamental. In particular, once we allow for random variation in the fundamental, the model exhibits again all of the nonlinear features discussed in De Grauwe and Grimaldi (2006): the disconnect puzzle, volatility clustering and fat tails.

Suggested Citation

  • Hans Dewachter & Romain Houssa & Marco Lyrio & Pablo Rovira Kaltwasser, 2011. "Dynamic Forecasting Rules and the Complexity of Exchange Rate Dynamics," Business and Economics Working Papers 125, Unidade de Negocios e Economia, Insper.
  • Handle: RePEc:aap:wpaper:125
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    References listed on IDEAS

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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    3. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    4. Cars Hommes, 2010. "The heterogeneous expectations hypothesis: some evidence from the lab," Post-Print hal-00753041, HAL.
    5. Westerhoff Frank H. & Reitz Stefan, 2003. "Nonlinearities and Cyclical Behavior: The Role of Chartists and Fundamentalists," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-15, December.
    6. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    7. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 95-132, February.
    8. Paul De Grauwe & Marianna Grimaldi, 2014. "Exchange Rate Puzzles: A Tale of Switching Attractors," World Scientific Book Chapters, in: Exchange Rates and Global Financial Policies, chapter 3, pages 71-117, World Scientific Publishing Co. Pte. Ltd..
    9. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    10. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    11. repec:bla:ecorec:v:0:y:1986:i:0:p:24-38 is not listed on IDEAS
    12. Paul De Grauwe & Marianna Grimaldi, 2014. "Heterogeneity of Agents, Transactions Costs and the Exchange Rate," World Scientific Book Chapters, in: Exchange Rates and Global Financial Policies, chapter 2, pages 33-70, World Scientific Publishing Co. Pte. Ltd..
    13. Paul De Grauwe & Marianna Grimaldi, 2005. "The Exchange Rate and its Fundamentals in a Complex World," Review of International Economics, Wiley Blackwell, vol. 13(3), pages 549-575, August.
    14. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2010. "Heterogeneity of agents and exchange rate dynamics: Evidence from the EMS," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1652-1669, December.
    15. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
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    1. Li, Xiao-Ping & Zhou, Chun-Yang & Tong, Bin, 2019. "Carry trades, agent heterogeneity and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 343-358.
    2. Qian Zhang & Kuo-Jui Wu & Ming-Lang Tseng, 2019. "Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method," Sustainability, MDPI, vol. 11(12), pages 1-26, June.

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