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Finding a Connection Between Exchange Rates and Fundamentals, How Should We Model Revisions to Forecasting Strategies?

  • Peter H. Sullivan

In this paper I compare the performance of three approaches to modeling temporal instability of the relationship between the euro-dollar exchange rate and macroeconomic fundamentals. Each of the three approaches considered -- adaptive learning, Markov-switching and Imperfect Knowledge Economics (IKE) -- recognize that market participants revise forecasting strategies, at least intermittently, and, as a result, the relationship between the exchange rate and fundamentals is temporally unstable. The central question in the literature addressed by this paper is which of the three approaches to modeling revisions of market participants' forecasting strategies is most empirically relevant for understanding the connection between currency fluctuations and fundamentals? One of the objectives of comparing the out-of-sample forecasting of the three approaches to change is to test to what extent growth-of-knowledge considerations, as proposed by Frydman and Goldberg (2007, 2011), are empirically relevant for our understanding of currency fluctuations. I find that only the IKE model, developed from Sullivan (2013) is able to significantly outperform the random walk benchmark, suggesting that different sets of fundamentals matter during different time periods in ways that do not conform to an overarching probability law.

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Paper provided by Job Market Papers in its series 2013 Papers with number psu387.

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Date of creation: 10 Nov 2013
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Handle: RePEc:jmp:jm2013:psu387
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  1. Yin-Wong Cheung & Menzie D. Chinn & Antonio Garcia-Pascual, 2005. "Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?," Working Papers 122005, Hong Kong Institute for Monetary Research.
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  4. Richard Clarida & Lucio Sarno & Mark Taylor & Giorgio Valente, 2001. "The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond," NBER Working Papers 8601, National Bureau of Economic Research, Inc.
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  7. Peter Reinhard Hansen, 2000. "Structural Changes in the Cointegrated Vector Autoregressive Model," Working Papers 2000-20, Brown University, Department of Economics.
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  9. Jon Faust & John H. Rogers & Shing-Yi B. Wang & Jonathan H. Wright, 2003. "The high-frequency response of exchange rates and interest rates to macroeconomic announcements," International Finance Discussion Papers 784, Board of Governors of the Federal Reserve System (U.S.).
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  11. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
  12. Nelson C. Mark, 2005. "Changing Monetary Policy Rules, Learning, and Real Exchange Rate Dynamics," NBER Working Papers 11061, National Bureau of Economic Research, Inc.
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  14. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  15. Joscha Beckmann & Ansgar Belke & Michael Kühl, 2011. "The dollar-euro exchange rate and macroeconomic fundamentals: a time-varying coefficient approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer, vol. 147(1), pages 11-40, April.
  16. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
  17. 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.
  18. Torben G. Andersen & Tim Bollerslev, 1998. "Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," Journal of Finance, American Finance Association, vol. 53(1), pages 219-265, 02.
  19. Meese, Richard A, 1986. "Testing for Bubbles in Exchange Markets: A Case of Sparkling Rates?," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 345-73, April.
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