The Flow of Information in Trading : An Entropy Approach to Market Regimes

In this study, we use entropy-based measures to identify different types of trading behaviors. We detect the return-driven trading using the conditional block entropy that dynamically reflects the "self-causality" of market return flows. Then we use the transfer entropy to identify the news-driven trading activity that is revealed by the information flows from news sentiment to market returns. We argue that when certain trading behavior becomes dominant or jointly dominant, the market will form a specific regime, namely return-, news- or mixed regime. Based on 11 years of news and market data, we find that the evolution of financial market regimes in terms of adaptive trading activities over the 2008 liquidity and euro-zone debt crises can be explicitly explained by the information flows. The proposed method can be expanded to make "causal" inferences on other types of economic phenomena.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:22

Enthalten in:

Entropy (Basel, Switzerland) - 22(2020), 9 vom: 22. Sept.

Sprache:

Englisch

Beteiligte Personen:

Liu, Anqi [VerfasserIn]
Chen, Jing [VerfasserIn]
Yang, Steve Y [VerfasserIn]
Hawkes, Alan G [VerfasserIn]

Links:

Volltext

Themen:

Information entropy
Journal Article
Market information flows
News sentiment
Trading behavior identification

Anmerkungen:

Date Revised 10.12.2020

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/e22091064

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM318526395