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Testing the Informational Efficiency of OTC Optionson Emerging Market Currencies

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  • Mr. Jorge A Chan-Lau
  • Mr. Armando Méndez Morales

Abstract

This paper analyzes the informational efficiency of OTC currency options on the Czech koruna and the Polish zloty correcting for the volatility risk premium and errors-in-variable problems, using state-of-the-art techniques (Chernov 2001). It finds that these markets are more efficient than mature markets possibly because of higher relative participation of informed dedicated investors, which offset the effects of relative illiquidity and higher transaction costs in these countries. Moreover, implied volatilities generally anticipate the direction of volatility correctly, with a bias to overpredicting volatility increases reflecting one-sided markets.

Suggested Citation

  • Mr. Jorge A Chan-Lau & Mr. Armando Méndez Morales, 2003. "Testing the Informational Efficiency of OTC Optionson Emerging Market Currencies," IMF Working Papers 2003/001, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2003/001
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    References listed on IDEAS

    as
    1. Torben G. Andersen & Luca Benzoni, 2009. "Stochastic volatility," Working Paper Series WP-09-04, Federal Reserve Bank of Chicago.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Chiras, Donald P. & Manaster, Steven, 1978. "The information content of option prices and a test of market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 213-234.
    4. Chernov, Mikhail & Ghysels, Eric, 2000. "A study towards a unified approach to the joint estimation of objective and risk neutral measures for the purpose of options valuation," Journal of Financial Economics, Elsevier, vol. 56(3), pages 407-458, June.
    5. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    6. Canina, Linda & Figlewski, Stephen, 1993. "The Informational Content of Implied Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 659-681.
    7. Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
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