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Can we beat the random walk in forecasting CEE exchange rates?

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Abstract

It is commonly known that various econometric techniques fail to consistently outperform a simple random walk model in forecasting exchange rates. The aim of this study is to analyse whether this also holds for selected currencies of the CEE region as the literature relating to the ability of forecasting these exchange rates is scarce. We tackle this issue by comparing the random walk based out-of-sample forecast errors of the Polish zloty, the Czech koruna and the Hungarian forint exchange rates against the euro with the corresponding errors generated by various single- and multi-equation models of these exchange rates. The results confirm that it is very difficult to outperform a simple random walk model in our CEE currencies forecasting contest.

Suggested Citation

  • Jakub Muck & Pawel Skrzypczynski, 2012. "Can we beat the random walk in forecasting CEE exchange rates?," NBP Working Papers 127, Narodowy Bank Polski, Economic Research Department.
  • Handle: RePEc:nbp:nbpmis:127
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    File URL: http://www.nbp.pl/publikacje/materialy_i_studia/127_en.pdf
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    1. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    2. Michał Rubaszek & Paweł Skrzypczyński & Grzegorz Koloch, 2010. "Forecasting the Polish Zloty with Non-Linear Models," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 2(2), pages 151-167, March.
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    Cited by:

    1. 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.

    More about this item

    Keywords

    CEE currencies; exchange rate forecasting; random walk; VAR; BVAR;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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