Rényi Transfer Entropy Estimators for Financial Time Series †

Abstract

In this paper, we discuss the statistical coherence between financial time series in terms of Rényi’s information measure or entropy. In particular, we tackle the issue of the directional information flow between bivariate time series in terms of Rényi’s transfer entropy. The latter represents a measure of information that is transferred only between certain parts of underlying distributions. This fact is particularly relevant in financial time series, where the knowledge of “black swan” events such as spikes or sudden jumps is of key importance. To put some flesh on the bare bones, we illustrate the essential features of Rényi’s information flow on two coupled GARCH((Formula presented.)) processes.