Conditional independence graph for nonlinear time series and its application to international financial markets
Conditional independence graphs are proposed for describing the dependence structure of multivariate nonlinear time series, which extend the graphical modeling approach based on partial correlation. The vertexes represent the components of a multivariate time series and edges denote direct dependence between corresponding series. The conditional independence relations between component series are tested efficiently and consistently using conditional mutual information statistics and a bootstrap procedure. Furthermore, a method combining information theory with surrogate data is applied to test the linearity of the conditional dependence. The efficiency of the methods is approved through simulation time series with different linear and nonlinear dependence relations. Finally, we show how the method can be applied to international financial markets to investigate the nonlinear independence structure.
Volume (Year): 392 (2013)
Issue (Month): 10 ()
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- Alessio Moneta, 2008. "Graphical causal models and VARs: an empirical assessment of the real business cycles hypothesis," Empirical Economics, Springer, vol. 35(2), pages 275-300, September.
- Abdelwahab Allali & Amor Oueslati & Abdelwahed Trabelsi, 2011. "Detection of Information Flow in Major International Financial Markets by Interactivity Network Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(3), pages 319-344, September.
- Bessler, David A. & Yang, Jian, 2003. "The structure of interdependence in international stock markets," Journal of International Money and Finance, Elsevier, vol. 22(2), pages 261-287, April.
- Diks Cees & Manzan Sebastiano, 2002.
"Tests for Serial Independence and Linearity Based on Correlation Integrals,"
Studies in Nonlinear Dynamics & Econometrics,
De Gruyter, vol. 6(2), pages 1-22, July.
- Diks, C.G.H. & Manzan, S., 2001. "Tests for serial independence and linearity based on correlation integrals," CeNDEF Working Papers 01-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Makram Talih & Nicolas Hengartner, 2005. "Structural learning with time-varying components: tracking the cross-section of financial time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(3), pages 321-341.
- Dean Prichard & James Theiler, 1994. "Generating Surrogate Data for Time Series with Several Simultaneously Measured Variables," Working Papers 94-04-023, Santa Fe Institute.
- repec:sbe:breart:v:16:y:1996:i:1:a:2878 is not listed on IDEAS
- Eichler, Michael, 2007. "Granger causality and path diagrams for multivariate time series," Journal of Econometrics, Elsevier, vol. 137(2), pages 334-353, April.
- Eun, Cheol S. & Shim, Sangdal, 1989. "International Transmission of Stock Market Movements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(02), pages 241-256, June. Full references (including those not matched with items on IDEAS)
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