A perspective on correlation-based financial networks and entropy measures
Abstract
In this brief review, we critically examine the recent work done on correlation-based networks in financial systems. The structure of empirical correlation matrices constructed from the financial market data changes as the individual stock prices fluctuate with time, showing interesting evolutionary patterns, especially during critical events such as market crashes, bubbles, etc. We show that the study of correlation-based networks and their evolution with time is useful for extracting important information of the underlying market dynamics. We, also, present our perspective on the use of recently developed entropy measures such as structural entropy and eigen-entropy for continuous monitoring of correlation-based networks.
Cite
@article{arxiv.2004.09448,
title = {A perspective on correlation-based financial networks and entropy measures},
author = {Vishwas Kukreti and Hirdesh K. Pharasi and Priya Gupta and Sunil Kumar},
journal= {arXiv preprint arXiv:2004.09448},
year = {2020}
}
Comments
10 pages, 2 figures. This paper is submitted to Frontiers in Physics, Research Topic "From Physics to Econophysics and Back: Methods and Insights"; Topic Editor(s): Siew Ann Cheong, Takayuki Mizuno, Wei-Xing Zhou, Gabjin Oh, Anirban Chakraborti, Damien Challet