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Forecasting disconnected exchange rates

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  • Travis J. Berge

Abstract

Catalyzed by the work of Meese and Rogoff (1983), a large literature has documented the inability of empirical models to accurately forecast exchange rates out-of-sample. This paper extends the literature by introducing an empirical strategy that endogenously builds forecast models from a broad set of conventional exchange rate signals. The method is extremely flexible, allowing for potentially nonlinear models for each currency and forecast horizon that evolve over time. Analysis of the models selected by the procedure sheds light on the erratic behavior of exchange rates and their apparent disconnect from macroeconomic fundamentals. In terms of forecast ability, the Meese-Rogoff result remains intact. At short horizons, the method cannot outperform a random walk, although at longer horizons the method does outperform the random walk null. These findings are found consistently across currencies and forecast evaluation methods.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 11-12.

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Date of creation: 2011
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Handle: RePEc:fip:fedkrw:rwp11-12

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  1. Elliott, Graham & Lieli, Robert P., 2013. "Predicting binary outcomes," Journal of Econometrics, Elsevier, vol. 174(1), pages 15-26.
  2. Dueker, Michael & Neely, Christopher J., 2007. "Can Markov switching models predict excess foreign exchange returns?," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 279-296, February.
  3. Christoffersen & Diebold, . "Optimal Prediction Under Asymmetric Loss," Home Pages 167, 1996., University of Pennsylvania.
  4. Yu-chin Chen & Kwok Ping Tsang, 2009. "What Does the Yield Curve Tell Us About Exchange Rate Predictability?," Working Papers UWEC-2009-04, University of Washington, Department of Economics.
  5. Raffaella Giacomini & Barbara Rossi, 2009. "Detecting and Predicting Forecast Breakdowns," Review of Economic Studies, Oxford University Press, vol. 76(2), pages 669-705.
  6. Philippe Bacchetta & Eric van Wincoop & Toni Beutler, 2009. "Can Parameter Instability Explain the Meese-Rogoff Puzzle?," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 09.08, Université de Lausanne, Faculté des HEC, DEEP.
  7. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
  8. Lukas Menkhoff & Lucio Sarno & Maik Schmeling & Andreas Schrimpf, 2011. "Currency Momentum Strategies," BIS Working Papers 366, Bank for International Settlements.
  9. Rossi, Barbara, 2002. "Testing Long-horizon Predictive Ability with High Persistence, and the Meese-Rogoff Puzzle," Working Papers 02-10, Duke University, Department of Economics.
  10. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
  11. Burnside, Craig & Eichenbaum, Martin & Rebelo, Sérgio, 2011. "Carry Trade and Momentum in Currency Markets," CEPR Discussion Papers 8343, C.E.P.R. Discussion Papers.
  12. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
  13. Travis Berge & Òscar Jordà & Alan M. Taylor, 2010. "Currency Carry Trades," NBER Chapters, in: NBER International Seminar on Macroeconomics 2010, pages 357-387 National Bureau of Economic Research, Inc.
  14. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers 32462, Iowa State University, Department of Economics.
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