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Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce

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IMPACT FACTOR 2017: 0.855

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Volume 17, Issue 1


Using transfer entropy to measure information flows between financial markets

Thomas Dimpfl / Franziska Julia Peter
  • Corresponding author
  • Department of Statistics, Econometrics and Empirical Economics, University of Tübingen, Mohlstraße 36, 72074 Tübingen, Germany
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Published Online: 2013-02-14 | DOI: https://doi.org/10.1515/snde-2012-0044


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.

This article offers supplementary material which is provided at the end of the article.

Keywords: entropy; information flow; non-linear dynamics; price discovery; credit risk; CDS

About the article

Corresponding author: Franziska Julia Peter, Department of Statistics, Econometrics and Empirical Economics, University of Tübingen, Mohlstraße 36, 72074 Tübingen, Germany, Phone: +49 7071 29 78165, Fax: +49 7071 29 5546

Published Online: 2013-02-14

Citation Information: Studies in Nonlinear Dynamics and Econometrics, Volume 17, Issue 1, Pages 85–102, ISSN (Online) 1558-3708, ISSN (Print) 1081-1826, DOI: https://doi.org/10.1515/snde-2012-0044.

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