Renyi's information transfer between financial time series
Petr Jizba, Hagen Kleinert, Mohammad Shefaat

TL;DR
This paper introduces Renyi transfer entropy to measure directional information flow in financial time series, emphasizing specific distribution parts, and applies it to global stock indices revealing asymmetric information transfer patterns.
Contribution
It formulates Renyi transfer entropy for financial data, highlighting selective emphasis on distribution features, and provides empirical analysis of international stock market information flows.
Findings
Asymmetric information flow from Asia-Pacific to Europe and US
Renyi entropy emphasizes specific distribution sectors
Quantitative analysis of DAX and S&P500 transfer entropy
Abstract
In this paper, we quantify the statistical coherence between financial time series by means of the Renyi entropy. With the help of Campbell's coding theorem we show that the Renyi entropy selectively emphasizes only certain sectors of the underlying empirical distribution while strongly suppressing others. This accentuation is controlled with Renyi's parameter q. To tackle the issue of the information flow between time series we formulate the concept of Renyi's transfer entropy as a measure of information that is transferred only between certain parts of underlying distributions. This is particularly pertinent in financial time series where the knowledge of marginal events such as spikes or sudden jumps is of a crucial importance. We apply the Renyian information flow to stock market time series from 11 world stock indices as sampled at a daily rate in the time period 02.01.1990 -…
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