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

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Ulrich Fritsche & Christian Pierdzioch & Jan-Christoph Ruelke & Georg Stadtmann, 2012. "Forecasting the Brazilian Real and the Mexican Peso: Asymmetric Loss, Forecast Rationality, and Forecaster Herding," Macroeconomics and Finance Series 201202, University of Hamburg, Department of Socioeconomics.
  • Handle: RePEc:hep:macppr:201202
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    8. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
    9. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    10. Christian Pierdzioch & Marian Risse & Sebastian Rohloff, 2016. "Fluctuations of the real exchange rate, real interest rates, and the dynamics of the price of gold in a small open economy," Empirical Economics, Springer, vol. 51(4), pages 1481-1499, December.
    11. Goldstein, Nathan & Zilberfarb, Ben-Zion, 2021. "Do forecasters really care about consensus?," Economic Modelling, Elsevier, vol. 100(C).
    12. Charemza, Wojciech & Ladley, Daniel, 2016. "Central banks’ forecasts and their bias: Evidence, effects and explanation," International Journal of Forecasting, Elsevier, vol. 32(3), pages 804-817.
    13. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    14. Tsuchiya, Yoichi, 2015. "Herding behavior and loss functions of exchange rate forecasters over interventions and financial crises," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 266-276.
    15. Pierdzioch, Christian & Rülke, Jan-Christoph, 2015. "On the directional accuracy of forecasts of emerging market exchange rates," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 369-376.
    16. Pierdzioch, Christian & Reid, Monique B. & Gupta, Rangan, 2016. "Inflation forecasts and forecaster herding: Evidence from South African survey data," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 62(C), pages 42-50.
    17. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    18. Kiss, Tamás & Kladívko, Kamil & Silfverberg, Oliwer & Österholm, Pär, 2023. "Market participants or the random walk – who forecasts better? Evidence from micro-level survey data," Finance Research Letters, Elsevier, vol. 54(C).
    19. Frenkel, Michael & Mauch, Matthias & Rülke, Jan-Christoph, 2020. "Do forecasters of major exchange rates herd?," Economic Modelling, Elsevier, vol. 84(C), pages 214-221.
    20. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
    21. Christoph Buehren & Tim Meyer & Christian Pierdzioch, 2020. "Experimental Evidence on Forecaster (anti-) Herding in Sports Markets," MAGKS Papers on Economics 202038, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    22. Tsuchiya, Yoichi, 2016. "Asymmetric loss and rationality of Chinese renminbi forecasts: An implication for the trade between China and the US," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 116-127.
    23. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.

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    Keywords

    Exchange rate; Forecasting; Loss function;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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