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Exchange rates and fundamentals under adaptive learning

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  • Kim, Young Se

Abstract

This paper studies a monetary model that is standard in all respects except that market participants have incomplete knowledge about the economic structure and employ adaptive learning rules to learn about the economic environment. Market participants also must contend with unannounced regime shifts. Simulation results suggest that the models under adaptive learning, especially constant-gain learning combined with a structural change, dominate the alternative specifications of expectations in their ability to account for why fundamentals predict exchange-rate returns over long horizons but not over short horizons, and for generating excessively volatile returns and persistent deviations of the exchange rate from the monetary fundamentals.

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  • 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.
  • Handle: RePEc:eee:dyncon:v:33:y:2009:i:4:p:843-863
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    2. de Truchis, Gilles & Dell’Eva, Cyril & Keddad, Benjamin, 2017. "On exchange rate comovements: New evidence from a Taylor rule fundamentals model with adaptive learning," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 82-98.
    3. Djeutem, Edouard & Kasa, Kenneth, 2013. "Robustness and exchange rate volatility," Journal of International Economics, Elsevier, vol. 91(1), pages 27-39.
    4. 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.
    5. De Grauwe, Paul & Markiewicz, Agnieszka, 2013. "Learning to forecast the exchange rate: Two competing approaches," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 42-76.
    6. Chang, Ming-Jen & Su, Che-Yi, 2014. "The dynamic relationship between exchange rates and macroeconomic fundamentals: Evidence from Pacific Rim countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 220-246.
    7. Agnieszka Markiewicz, 2012. "Model Uncertainty And Exchange Rate Volatility," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 815-844, August.
    8. Agnieszka Markiewicz, 2010. "Monetary Policy, Model Uncertainty and Exchange Rate Volatility," CESifo Working Paper Series 2949, CESifo.
    9. Honkapohja, Seppo & Evans, George W., 2011. "Learning as a Rational Foundation for Macroeconomics and Finance," CEPR Discussion Papers 8340, C.E.P.R. Discussion Papers.
    10. Peter H. Sullivan, 2013. "Finding a Connection Between Exchange Rates and Fundamentals, How Should We Model Revisions to Forecasting Strategies?," 2013 Papers psu387, Job Market Papers.
    11. Reed, Jason R., 2019. "The forward premium puzzle and Markov-switching adaptive learning," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 1-17.
    12. Elias, Christopher J., 2016. "A heterogeneous agent exchange rate model with speculators and non-speculators," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 203-223.
    13. Young Se Kim & Gwi Hwan Seol, 2016. "Monetary Policy Regime Shifts and Uncovered Interest Parity Revisited: The Euro–US Dollar Exchange Rate," International Economic Journal, Taylor & Francis Journals, vol. 30(3), pages 360-378, July.
    14. Habimana, Olivier, 2017. "The multiscale relationship between exchange rates and fundamentals differentials: Empirical evidence from Scandinavia," MPRA Paper 75956, University Library of Munich, Germany.

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