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A note on forecasting emerging market exchange rates: Evidence of anti-herding

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

Abstract

Using survey forecasts of a large number of Asian, European, and South American emerging market exchange rates, we studied empirically whether evidence of herding or antiherding behavior of exchange-rate forecasters can be detected in the cross-section of forecasts. Emerging market exchange-rate forecasts are consistent with herding (anti-herding) if forecasts are biased towards (away from) the consensus forecast. Our empirical findings provide strong evidence of anti-herding of emerging market exchange-rate forecasters.

Suggested Citation

  • Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "A note on forecasting emerging market exchange rates: Evidence of anti-herding," Discussion Papers 324, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
  • Handle: RePEc:zbw:euvwdp:324
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    References listed on IDEAS

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    1. Ottaviani, Marco & Sorensen, Peter Norman, 2006. "The strategy of professional forecasting," Journal of Financial Economics, Elsevier, vol. 81(2), pages 441-466, August.
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    Cited by:

    1. Rybacki Jakub, 2020. "Macroeconomic forecasting in Poland: The role of forecasting competitions," Central European Economic Journal, Sciendo, vol. 7(54), pages 1-11, January.
    2. 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.
    3. 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.
    4. Yoichi Tsuchiya, 2021. "Crises, market shocks, and herding behavior in stock price forecasts," Empirical Economics, Springer, vol. 61(2), pages 919-945, August.
    5. Lukas Richau & Florian Follert & Monika Frenger & Eike Emrich, 2021. "The sky is the limit?! Evaluating the existence of a speculative bubble in European football," Journal of Business Economics, Springer, vol. 91(6), pages 765-796, August.
    6. 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.
    7. Hamid Baghestani & Liliana Danila, 2014. "Interest Rate and Exchange Rate Forecasting in the Czech Republic: Do Analysts Know Better than a Random Walk?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 282-295, September.
    8. Xolani Sibande & Rangan Gupta & Riza Demirer & Elie Bouri, 2023. "Investor Sentiment and (Anti) Herding in the Currency Market: Evidence from Twitter Feed Data," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(1), pages 56-72, January.
    9. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    10. 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.
    11. Frenkel, Michael & Mauch, Matthias & Rülke, Jan-Christoph, 2020. "Do forecasters of major exchange rates herd?," Economic Modelling, Elsevier, vol. 84(C), pages 214-221.
    12. 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

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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