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Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding

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  • Fritsche, Ulrich
  • Pierdzioch, Christian
  • Rülke, Jan-Christoph
  • Stadtmann, Georg

Abstract

Using forecasts of exchange rates of the Brazilian real and the Mexican peso against the US dollar, we analyze the symmetry of the loss function of exchange-rate forecasters and the rationality of their forecasts. Symmetry of the loss function can be rejected for some forecasters but not all. Even when allowing for asymmetric loss functions, the predictions of some forecasters do not fit the traditional definition of rational forecasts. We interpret our results in terms of recent research on forecaster (anti-)herding.

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  • Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    • Handle: RePEc:eee:intfor:v:31:y:2015:i:1:p:130-139
    DOI: 10.1016/j.ijforecast.2014.08.010
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    Cited by:

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    3. Pierdzioch, Christian & Reid, Monique B. & Gupta, Rangan, 2016. "Forecasting the South African inflation rate: On asymmetric loss and forecast rationality," Economic Systems, Elsevier, vol. 40(1), pages 82-92.
    4. 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.
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    7. 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.
    8. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Michael Frenkel & Jin-Kyu Jung & Jan-Christoph Rülke, 2017. "Rationalizing the Bias in Central Banks' Interest Rate Projections," WHU Working Paper Series - Economics Group 17-03, WHU - Otto Beisheim School of Management.
    17. Michael Frenkel & Jin-Kyu Jung & Jan-Christoph Rülke, 2022. "Testing for the rationality of central bank interest rate forecasts," Empirical Economics, Springer, vol. 62(3), pages 1037-1078, March.
    18. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A quantile-boosting approach to forecasting gold returns," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 38-55.
    19. Goldstein, Nathan & Zilberfarb, Ben-Zion, 2021. "Do forecasters really care about consensus?," Economic Modelling, Elsevier, vol. 100(C).
    20. 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.
    21. 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).
    22. Frenkel, Michael & Mauch, Matthias & Rülke, Jan-Christoph, 2020. "Do forecasters of major exchange rates herd?," Economic Modelling, Elsevier, vol. 84(C), pages 214-221.
    23. 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).

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    More about this item

    Keywords

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

    JEL classification:

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

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