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Global Financial Crisis and the Puzzling Exchange Rate Path in CEE Countries

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Abstract
In the present paper we examine whether financial markets could have helped predict exchange rates in three selected Central and Eastern European (CEE) economies of the EU, namely the Czech Republic, Hungary and Poland, during the current financial crisis. To this end, we derive risk-neutral densities from the implied volatilities of FX options, which approximate market expectations about exchange rate developments. Based on these risk-neutral density estimates, we then assess the out-of-sample predictive power of indicators. The forecasting results suggest that models based on FX options are inferior to the random walk in terms of the forecasting error, confirming a stylized fact about the short-term forecasting of exchange rates. Yet, we also find that, for the Czech Republic and Poland, risk-neutral densities contain useful information on the direction of change of the exchange rate.

Suggested Citation

  • Jesús Crespo Cuaresma & Adam Gersl & Tomáš Slačík, 2010. "Global Financial Crisis and the Puzzling Exchange Rate Path in CEE Countries," Working Papers IES 2010/24, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2010.
    • Handle: RePEc:fau:wpaper:wp2010_24
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    File URL: http://ies.fsv.cuni.cz/default/file/download/id/14092
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    References listed on IDEAS

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    1. Crespo Cuaresma, Jesús & Slacik, Tomas, 2009. "On the determinants of currency crises: The role of model uncertainty," Journal of Macroeconomics, Elsevier, vol. 31(4), pages 621-632, December.
    2. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    3. Jesús Crespo Cuaresma & Martin Feldkircher, 2013. "Spatial Filtering, Model Uncertainty And The Speed Of Income Convergence In Europe," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 720-741, June.
    4. Pavel Bouc & Martin Cincibuch, 2004. "An Interpretation of Czech FX Options," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 54(7-8), pages 286-304, July.
    5. 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.
    6. Jesus Crespo Cuaresma, "undated". "Forecasting euro exchange rates: How much does model averaging help?," Working Papers 2007-24, Faculty of Economics and Statistics, Universität Innsbruck.
    7. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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    Cited by:

    1. Torój, Andrzej & Bednarek, Elżbieta & Bęza-Bojanowska, Joanna & Osińska, Joanna & Waćko, Katarzyna & Witkowski, Dariusz, 2012. "EMU: the (post-)crisis perspective. Literature survey and implications for the euro-candidates," MF Working Papers 12, Ministry of Finance in Poland, revised 06 Mar 2012.

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    More about this item

    Keywords

    Options; implied volatility; risk-neutral density; exchange rate forecasting; Bayesian model averaging; subprime crisis; emerging markets;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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