Studies in Nonlinear Dynamics & Econometrics
Ed. by Mizrach, Bruce
5 Issues per year
IMPACT FACTOR 2016: 0.649
CiteScore 2016: 0.63
SCImago Journal Rank (SJR) 2016: 0.546
Source Normalized Impact per Paper (SNIP) 2016: 0.793
Mathematical Citation Quotient (MCQ) 2016: 0.03
Using transfer entropy to measure information flows between financial markets
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.
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