Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

The flow of information in trading: an entropy approach to market regimes

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

[thumbnail of entropy-22-01064-v2 (1).pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (825kB) | Preview

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
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

Citation Data

Cited 14 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics