Measuring information flow among international stock markets: An approach of entropy-based networks on multi time-scales

Peng-Cheng Kuang

Physica A: Statistical Mechanics and its Applications, 2021, vol. 577, issue C

Abstract: Information flow among stock markets leads to the co-movement of stock prices and even the financial risk contagion globally. Measuring information flow on multi time-scales helps to develop optimal portfolio strategy for market participants and establish targeted financial regulation for policy makers, but is a challenge for traditional econometrics. This study aims to construct the information flow networks on multi time-scales among international stock markets. First, we use the data of 31 stock market indices during 2007 to 2018, and decompose each of stock index series into short and mid-long time-scale components by empirical mode decomposition (EMD). Then, we extend a novel concept in information science, called transfer entropy (TE), to measure information flow and characterize causality structure between two stock markets, and find that information flows inside of EU stock markets only cluster on short time-scale but not on mid-long time-scale. Moreover, both out-node and in-node centrality measurements for developed markets in the entropy-based networks are much higher on short time-scale, indicating that these markets are more dominant but more vulnerable to short-term risk contagion. Finally, based on the minimum spanning tree (MST) model, we extract the most probable risk contagion paths from entropy-based networks. The results show that outflow MSTs on short time-scale follow a star-like structure to precipitate the risk contagion in the international stock markets, especially during crisis period (2007∼2010). Overall, we emphasize the financial risk contagion on short time-scale.

Keywords: Stock market co-movements; Information flow; Entropy-based networks; Multi time-scales analysis (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437121003411
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:577:y:2021:i:c:s0378437121003411

DOI: 10.1016/j.physa.2021.126068

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().