Using transfer entropy to measure information flows between financial markets

Thomas Dimpfl and Peter Franziska Julia ()
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Peter Franziska Julia: Department of Statistics, Econometrics and Empirical Economics, University of Tübingen, Mohlstraße 36, 72074 Tübingen, Germany

Studies in Nonlinear Dynamics & Econometrics, 2013, vol. 17, issue 1, 85-102

Abstract: We use transfer entropy to quantify information flows between financial markets and propose a suitable bootstrap procedure for statistical inference. Transfer entropy is a model-free measure designed as the Kullback-Leibler distance of transition probabilities. Our approach allows to determine, measure and test for information transfer without being restricted to linear dynamics. In our empirical application, we examine the importance of the credit default swap market relative to the corporate bond market for the pricing of credit risk. We also analyze the dynamic relation between market risk and credit risk proxied by the VIX and the iTraxx Europe, respectively. We conduct the analyses for pre-crisis, crisis and post-crisis periods.

Keywords: entropy; information flow; non-linear dynamics; price discovery; credit risk; CDS (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1515/snde-2012-0044

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