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Measuring Nonlinear Serial Dependencies Using the Mutual Information Coefficient

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  • Witold Orzeszko

    () (Nicolaus Copernicus University in Torun)

Abstract

Construction, estimation and application of the mutual information measure have been presented in this paper. The simulations have been carried out to verify its usefulness to detect nonlinear serial dependencies. Moreover, the mutual information measure has been applied to the indices and the sector sub-indices of the Warsaw Stock Exchange.

Suggested Citation

  • Witold Orzeszko, 2010. "Measuring Nonlinear Serial Dependencies Using the Mutual Information Coefficient," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 97-106.
  • Handle: RePEc:cpn:umkdem:v:10:y:2010:p:97-106
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    File URL: http://www.dem.umk.pl/dem/archiwa/v10/08_WOrzeszko.pdf
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    References listed on IDEAS

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    1. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    2. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2003. "Mutual information: a dependence measure for nonlinear time series," Econometrics 0311003, EconWPA.
    3. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
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    Cited by:

    1. Piotr Fiszeder & Witold Orzeszko, 2012. "Nonparametric Verification of GARCH-Class Models for Selected Polish Exchange Rates and Stock Indices," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 430-449, November.

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