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Mutual information: a dependence measure for nonlinear time series

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Author Info
Andreia Dionisio (University of Evora)
Rui Menezes (ISCTE)
Diana A. Mendes (ISCTE)

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Abstract

This paper investigates the possibility to analyse the structure of unconditional or conditional (and possibly nonlinear) dependence in financial returns without requiring the specification of mean-variance models or a theoretical probability distribution. The main goal of the paper is to show how mutual information can be used as a measure of dependence in financial time series. One major advantage of this approach resides precisely in its ability to account for nonlinear dependencies with no need to specify a theoretical probability distribution or use of a mean-variance model.

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File URL: http://129.3.20.41/eps/em/papers/0311/0311003.pdf
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Publisher Info
Paper provided by EconWPA in its series Econometrics with number 0311003.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 36 pages
Date of creation: 11 Nov 2003
Date of revision:
Handle: RePEc:wpa:wuwpem:0311003

Note: Type of Document - Acrobat PDF; prepared on Win98; pages: 36; figures: 4. 36 pages, 4 figures, 21 tables
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Web page: http://129.3.20.41

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Related research
Keywords: Mutual information; nonlinear dependence; market efficiency;

Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

This paper has been announced in the following NEP Reports:

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This page was last updated on 2009-11-20.

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