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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. Christoffersen, Peter F. & Diebold, Francis X., 1997. "Optimal Prediction Under Asymmetric Loss," Econometric Theory, Cambridge University Press, vol. 13(06), pages 808-817, December.
  2. Michael Dueker & Christopher J. Neely, 2006. "Can Markov switching models predict excess foreign exchange returns?," Working Papers 2001-021, Federal Reserve Bank of St. Louis.
  3. Raffaella Giacomini & Barbara Rossi, 2009. "Detecting and Predicting Forecast Breakdowns," Review of Economic Studies, Oxford University Press, vol. 76(2), pages 669-705.
  4. Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics 572, Boston College Department of Economics.
  5. 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.
  6. Craig Burnside & Martin S. Eichenbaum & Sergio Rebelo, 2011. "Carry Trade and Momentum in Currency Markets," NBER Working Papers 16942, National Bureau of Economic Research, Inc.
  7. Menkhoff, Lukas & Sarno, Lucio & Schmeling, Maik & Schrimpf, Andreas, 2012. "Currency Momentum Strategies," CEPR Discussion Papers 8747, C.E.P.R. Discussion Papers.
  8. 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.).
  9. 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.
  10. Philippe Bacchetta & Eric van Wincoop & Toni Beutler, 2010. "Can Parameter Instability Explain the Meese-Rogoff Puzzle?," NBER Chapters, in: NBER International Seminar on Macroeconomics 2009, pages 125-173 National Bureau of Economic Research, Inc.
  11. Yu-chin Chen & Kwok Ping Tsang, 2010. "What Does the Yield Curve Tell Us about Exchange Rate Predictability?," Working Papers 292010, Hong Kong Institute for Monetary Research.
  12. Travis Berge & �scar Jord� & Alan M. Taylor, 2011. "Currency Carry Trades," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 7(1), pages 357 - 388.
    • 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.
  13. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers 32462, Iowa State University, Department of Economics.
  14. Elliott, Graham & Lieli, Robert P., 2013. "Predicting binary outcomes," Journal of Econometrics, Elsevier, vol. 174(1), pages 15-26.
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