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Tests for serial independence and linearity based on correlation integrals

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Author Info
Diks, C.G.H.
Manzan, S. () (Universiteit van Amsterdam)

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Abstract

We propose information theoretic tests for serial independence and linearity in time series. The test statistics are based on the conditional mutual information, a general measure of dependence between lagged variables. In case of rejecting the null hypothesis, this readily provides insights into the lags through which the dependence arises. The conditional mutual information is estimated using the correlation integral from chaos theory. The significance of the test statistic is determined with a permutation procedure and a parametric bootstrap in the tests for independence and linearity, respectively. The size and power properties of the tests are examined numerically and illustrated with applications to some benchmark time series.

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Publisher Info
Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Working Papers with number 01-02.

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Date of creation: 2001
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Handle: RePEc:ams:ndfwpp:01-02

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Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands
Phone: + 31 20 525 52 58
Fax: + 31 20 525 52 83
Web page: http://www.fee.uva.nl/cendef/
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For technical questions regarding this item, or to correct its listing, contact: (Cees C.G. Diks).

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. R. Tschernig & L. Yang, . "Nonparametric Lag Selection for Time Series," Sonderforschungsbereich 373 1997-59, Humboldt Universitaet Berlin.
  2. Robinson, P M, 1991. "Consistent Nonparametric Entropy-Based Testing," Review of Economic Studies, Blackwell Publishing, vol. 58(3), pages 437-53, May. [Downloadable!] (restricted)
  3. W. A. Broock & J. A. Scheinkman & W. D. Dechert & B. LeBaron, 1996. "A test for independence based on the correlation dimension," Econometric Reviews, Taylor and Francis Journals, vol. 15(3), pages 197-235. [Downloadable!] (restricted)
  4. Diks, C.G.H., 1999. "Consistent Testing for Serial Independence," CeNDEF Working Papers 99-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  5. repec:att:wimass:199520 is not listed on IDEAS
  6. F. M. Aparicio & A. Escribano, 1998. "Information-Theoretic Analysis of Serial Dependence and Cointegration," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 3(3). [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
  2. Diks, C.G.H. & Panchenko, V., 2006. "Rank-based entropy tests for serial independence," CeNDEF Working Papers 06-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
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