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Author
C.G.H. Diks
S. Manzan
Year
2001
Title
Tests for serial independence and linearity based on correlation integrals
Number of pages
21
Publisher
Amsterdam / Rotterdam: Tinbergen Institute
Serie
Tinbergen Institute Discussion Paper
Volume | Edition (Serie)
TI 2001-085/1
Document type
Working paper
Faculty
Faculty of Economics and Business (FEB)
Institute
Amsterdam School of Economics Research Institute (ASE-RI)
Abstract
We propose information theoretic tests for serial independence and linearity in time series. The test statisticsare based on the conditional mutual information, a general measure of dependence between lagged variables. In caseof 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 signi[tanceof the test statistics is determined with a permutation procedure and a parametric bootstrap in the testsfor serial independence and linearity, respectively.The size and power properties of the tests are examined numerically and illustrated with applications to somebenchmark time series.
Link
Link
Language
English
Permalink
http://hdl.handle.net/11245/1.188385

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