Information-theoretic measures for non-linear causality detection: application to social media sentiment and cryptocurrency prices

Information transfer between time series is calculated by using the asymmetric information-theoretic measure known as transfer entropy. Geweke's autoregressive formulation of Granger causality is used to find linear transfer entropy, and Schreiber's general, non-parametric, information-theoretic formulation is used to detect non-linear transfer entropy. We first validate these measures against synthetic data. Then we apply these measures to detect causality between social sentiment and cryptoc...