Rényi Transfer Entropy Estimators for Financial Time Series
| Autor: | Petr Jizba, Zlata Tabachová, Hynek Lavička |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Finance
Series (mathematics) business.industry Computer science Autoregressive conditional heteroskedasticity Estimator Bivariate analysis Coherence (statistics) 01 natural sciences Measure (mathematics) 010305 fluids & plasmas 0103 physical sciences Entropy (information theory) Transfer entropy business 010301 acoustics |
| Zdroj: | The 7th International conference on Time Series and Forecasting. |
| DOI: | 10.3390/engproc2021005033 |
| Popis: | In this paper, we discuss the statistical coherence between financial time series in terms of Renyi’s information measure or entropy. In particular, we tackle the issue of the directional information flow between bivariate time series in terms of Renyi’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 Renyi’s information flow on two coupled GARCH(1,1) processes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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