Liu, Anqi ORCID: https://orcid.org/0000-0002-9224-084X, Chen, Jing ORCID: https://orcid.org/0000-0001-7135-2116, Yang, Steve Y. and Hawkes, Alan G. 2020. The flow of information in trading: an entropy approach to market regimes. Entropy 22 (9) , 1064. 10.3390/e22091064 |
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Abstract
In this study, we use entropy-based measures to identify different types of trading behaviors.1We 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-driven3trading activity that is revealed by the information flows from news sentiment to market returns. We argue that when certain trading behaviour 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。
Item Type: | Article |
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Date Type: | Published Online |
Status: | Published |
Schools: | Mathematics |
Subjects: | H Social Sciences > HA Statistics H Social Sciences > HG Finance Q Science > QA Mathematics |
Publisher: | MDPI |
ISSN: | 1099-4300 |
Date of First Compliant Deposit: | 23 September 2020 |
Date of Acceptance: | 21 September 2020 |
Last Modified: | 23 May 2023 20:59 |
URI: | https://orca.cardiff.ac.uk/id/eprint/134953 |
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