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Forecasting exchange rates with a large Bayesian VAR

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

Abstract

Models based on economic theory have serious problems 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, 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 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 all forecast horizons, including 1-step-ahead.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 25 (2009)
Issue (Month): 2 ()
Pages: 400-417

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Handle: RePEc:eee:intfor:v:25:y:2009:i:2:p:400-417

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Web page: http://www.elsevier.com/locate/ijforecast

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Keywords: Exchange rates Forecasting Bayesian VAR;

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  1. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  2. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank, Research Centre.
  3. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
  4. Jon Faust & John H. Rogers & Jonathan H. Wright, 2001. "Exchange rate forecasting: the errors we've really made," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.) 714, Board of Governors of the Federal Reserve System (U.S.).
  5. 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.
  6. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," Working Paper, Federal Reserve Bank of Atlanta 96-13, Federal Reserve Bank of Atlanta.
  7. 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.
  8. 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.
  9. de Zwart, Gerben & Markwat, Thijs & Swinkels, Laurens & van Dijk, Dick, 2009. "The economic value of fundamental and technical information in emerging currency markets," Journal of International Money and Finance, Elsevier, Elsevier, vol. 28(4), pages 581-604, June.
  10. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 4(1), pages 25-38, January.
  11. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report, Federal Reserve Bank of Minneapolis 93, Federal Reserve Bank of Minneapolis.
  12. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, Econometric Society, vol. 74(6), pages 1545-1578, November.
  13. repec:fth:erroem:9814/a is not listed on IDEAS
  14. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  15. 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.
  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. Jan J. J. Groen, 1999. "Long horizon predictability of exchange rates: Is it for real?," Empirical Economics, Springer, vol. 24(3), pages 451-469.
  18. 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, Elsevier, vol. 13(3), pages 276-290, June.
  19. 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.
  20. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
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