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Partial Symbolic Transfer Entropy

Author

Listed:
  • Papana, A.

    () (University of Macedonia)

  • Kyrtsou, K.

    () (University of Macedonia)

  • Kugiumtzis, D.

    () (Aristotle University of Thessaloniki)

  • Diks, C.G.H.

    () (University of Amsterdam)

Abstract

In this paper, we introduce the partial symbolic transfer entropy (PSTE), an extension of the symbolic transfer entropy that accounts only for the direct causal effects among the components of a multivariate system. It is an information theoretic measure, and as such does not suffer from model mis-specification bias. The PSTE is defined on the ranks of vectors that are formed from the reconstructed vectors, instead of the original time series values. The statistical significance of PSTE is assessed by randomization test making use of surrogate time series. The PSTE is evaluated on multivariate time series of different types of coupled and uncoupled systems and compared with conditional Granger causality index (CGCI). It is shown that the PSTE is not affected by the existence of outliers, it is directly applicable to time series that are non-stationary in mean and in variance, and it is also not affected by data filtering. As a real application, the causal effects among three economic indexes are investigated. Computations of PSTE and CGCI on both the initial returns and the VAR filtered returns, and only of PSTE on the original indexes, showed consistency of the PSTE in estimating the causal effect.

Suggested Citation

  • Papana, A. & Kyrtsou, K. & Kugiumtzis, D. & Diks, C.G.H., 2013. "Partial Symbolic Transfer Entropy," CeNDEF Working Papers 13-16, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Handle: RePEc:ams:ndfwpp:13-16
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    References listed on IDEAS

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    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    2. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    3. Karagianni Stella & Kyrtsou Catherine, 2011. "Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    4. Jen-Chi Cheng & Larry Taylor & Wenlong Weng, 2010. "The links between international parity conditions and Granger causality: a study of exchange rates and prices," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3491-3501.
    5. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    6. Hiemstra, Craig & Jones, Jonathan D, 1994. " Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    7. Baghli, Mustapha, 2006. "A model-free characterization of causality," Economics Letters, Elsevier, vol. 91(3), pages 380-388, June.
    8. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
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