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Forecasting the Brazilian Real and the Mexican Peso: Asymmetric Loss, Forecast Rationality, and Forecaster Herding

  • Ulrich Fritsche

    ()

    (Department for Socioeconomics, Department for Economics, University of Hamburg)

  • Christian Pierdzioch

    ()

    (Helmut-Schmidt-University, Department of Economics)

  • Jan-Christoph Ruelke

    ()

    (WHU – Otto Beisheim School of Management)

  • Georg Stadtmann

    ()

    (University of Southern Denmark, Department of Business and Economics, and European-University Viadrina)

Using forecasts of the Brazilian real and the Mexican peso, we analyze the shape of the loss function of exchange-rate forecasters and the rationality of their forecasts. We find a substantial degree of cross-sectional heterogeneity with respect to the shape of the loss function. While some forecasters seem to forecasts under an asymmetric loss function, symmetry of the loss function cannot be rejected for other forecasters. An asymmetric loss function does not necessarily make survey data of exchange-rate forecasts look rational, and the loss function seems to depend not only on the forecast error.

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File URL: http://www.wiso.uni-hamburg.de/repec/hepdoc/macppr_2_2012.pdf
File Function: First version, 2012
Download Restriction: no

Paper provided by Hamburg University, Department Wirtschaft und Politik in its series Macroeconomics and Finance Series with number 201202.

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Length: 29 pages
Date of creation: Feb 2012
Date of revision:
Handle: RePEc:hep:macppr:201202
Contact details of provider: Web page: http://www.wiso.uni-hamburg.de/dwp

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  1. Dufour, J.M., 1979. "Rank Tests for Serial Dependence," Cahiers de recherche 7815, Universite de Montreal, Departement de sciences economiques.
  2. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias In Macroeconomic Forecasts," The Quarterly Journal of Economics, MIT Press, vol. 114(1), pages 293-318, February.
  3. Jörg Döpke & Ulrich Fritsche & Boriss Siliverstovs, 2009. "Evaluating German Business Cycle Forecasts Under an Asymmetric Loss Function," KOF Working papers 09-237, KOF Swiss Economic Institute, ETH Zurich.
  4. Peter F. Christoffersen & Francis X. Diebold, 1997. "Optimal prediction under asymmetric loss," Working Papers 97-11, Federal Reserve Bank of Philadelphia.
  5. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
  6. George Christodoulakis & Emmanuel Mamatzakis, 2008. "Asymmetries in the sport-forward G10 exchange rates: an answer to an old puzzle?," Discussion Paper Series 2008_12, Department of Economics, University of Macedonia, revised Sep 2008.
  7. Bernhardt, Dan & Campello, Murillo & Kutsoati, Edward, 2006. "Who herds?," Journal of Financial Economics, Elsevier, vol. 80(3), pages 657-675, June.
  8. MacDonald, Ronald, 2000. " Expectations Formation and Risk in Three Financial Markets: Surveying What the Surveys Say," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 69-100, February.
  9. Christian Pierdzioch & Jan-Christoph R�lke & Georg Stadtmann, 2012. "Exchange-rate forecasts and asymmetric loss: empirical evidence for the yen/dollar exchange rate," Applied Economics Letters, Taylor & Francis Journals, vol. 19(18), pages 1759-1763, December.
  10. Benassy-Quere, Agnes & Larribeau, Sophie & MacDonald, Ronald, 2003. "Models of exchange rate expectations: how much heterogeneity?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(2), pages 113-136, April.
  11. G. A. Christodoulakis & E. C. Mamatzakis, 2009. "Assessing the prudence of economic forecasts in the EU," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 583-606.
  12. 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.
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