Abstract
We apply the concept of transfer entropy to quantify information flows between financial time series. Transfer entropy is a model-free measure designed as the Kullback-Leibler distance of transition probabilities. This approach allows to determine information transfer without being restricted to linear dynamics. We further develop a bootstrap procedure in order to allow for statistical inference of the estimates. In our empirical application, we examine the importance of the CDS and bond market for the process of pricing credit risk as well as the dynamic relation between market risk and credit risk proxied by the iTraxx Europe and the VIX.
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