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Forecasting Exchange Rates with a Large Bayesian VAR

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  • A. Carriero
  • G. Kapetanios
  • M. Marcellino

Abstract

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis-a-vis the US Dollar. Since exchange rates tend to co-move, the use of a large set of them can contain useful information for forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is strong evidence of them in the data. We produce forecasts for all the 33 exchange rates in the panel, and show that our model produces systematically better forecasts than a random walk for most of the countries, and at any forecast horizon, including at 1-step ahead.

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Bibliographic Info

Paper provided by European University Institute in its series Economics Working Papers with number ECO2008/33.

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Date of creation: 2008
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Handle: RePEc:eui:euiwps:eco2008/33

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Keywords: Exchange Rates; Forecasting; Bayesian VAR;

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  1. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  2. Christine De Mol & Domenico Giannone & Lucrezia Reichlin, 2008. "Forecasting using a large number of predictors: is Bayesian shrinkage a valid alternative to principal components?," ULB Institutional Repository 2013/6411, ULB -- Universite Libre de Bruxelles.
  3. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  4. Marcellino, Massimiliano & Stock, James H & Watson, Mark W, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
  5. Faust, Jon & Rogers, John H. & H. Wright, Jonathan, 2003. "Exchange rate forecasting: the errors we've really made," Journal of International Economics, Elsevier, vol. 60(1), pages 35-59, May.
  6. Chinn, Menzie D. & Meese, Richard A., 1995. "Banking on currency forecasts: How predictable is change in money?," Journal of International Economics, Elsevier, vol. 38(1-2), pages 161-178, February.
  7. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  8. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
  9. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
  10. Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics 572, Boston College Department of Economics.
  11. Pesaran, M Hashem & Timmermann, Allan G, 2004. "Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks," CEPR Discussion Papers 4401, C.E.P.R. Discussion Papers.
  12. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-18, March.
  13. Jeremy Berkowitz & Lorenzo Giorgianni, 2001. "Long-Horizon Exchange Rate Predictability?," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 81-91, February.
  14. MacDonald, Ronald & Taylor, Mark P., 1994. "The monetary model of the exchange rate: long-run relationships, short-run dynamics and how to beat a random walk," Journal of International Money and Finance, Elsevier, vol. 13(3), pages 276-290, June.
  15. de Zwart, G.J. & Markwat, T.D. & Swinkels, L.A.P. & van Dijk, D.J.C., 2007. "The Economic Value of Fundamental and Technical Information in Emerging Currency Markets," ERIM Report Series Research in Management ERS-2007-096-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
  16. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
  17. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-68, November.
  18. Ronald MacDonald & Ian W. Marsh, 1997. "On Fundamentals And Exchange Rates: A Casselian Perspective," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 655-664, November.
  19. Jan J. J. Groen, 1999. "Long horizon predictability of exchange rates: Is it for real?," Empirical Economics, Springer, vol. 24(3), pages 451-469.
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