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A symbolic test for testing independence between time series

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  • Mariano Matilla-García
  • José Miguel Rodríguez
  • Manuel Ruiz Marín

Abstract

In this article we introduce a test for independence between two processes {X_t} and {Y_t}. To this end we rely on symbolic dynamics and permutation entropy as a measure of dependence. As a result, a nonparametric (model-free) test for either linear or nonlinear processes is presented. The test is consistent for a broad range of dependent alternatives. Empirical simulations indicate and highlight the general utility of the test for time-series analysts. Copyright Copyright 2010 Blackwell Publishing Ltd

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 31 (2010)
Issue (Month): 2 (03)
Pages: 76-85

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Handle: RePEc:bla:jtsera:v:31:y:2010:i:2:p:76-85

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782

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Cited by:
  1. Matilla-García, Mariano & Marín, Manuel Ruiz & Dore, Mohammed I., 2014. "A permutation entropy based test for causality: The volume–stock price relation," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 398(C), pages 280-288.
  2. Helmut Elsinger, 2010. "Independence Tests based on Symbolic Dynamics," Working Papers, Oesterreichische Nationalbank (Austrian Central Bank) 165, Oesterreichische Nationalbank (Austrian Central Bank).

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