Complexity-based Financial Stress Evaluation

TL;DR

This paper introduces a complexity-based approach using entropy measures to evaluate financial market stress and asset sensitivity during crises, supporting the Efficient Market Hypothesis.

Contribution

It develops a novel entropy-based framework and graphical analysis to assess market stress and asset sensitivity to crises, integrating Catastrophe Theory.

Findings

Market complexity correlates with financial crises.

Assets show distinct stress responses to crises.

Framework supports the Efficient Market Hypothesis.

Abstract

Financial markets typically exhibit dynamically complex properties as they undergo continuous interactions with economic and environmental factors. The Efficient Market Hypothesis indicates a rich difference in the structural complexity of security prices between normal (stable markets) and abnormal (financial crises) situations. Considering the analogy between market undulation of price time series and physical stress of bio-signals, we investigate whether stress indices in bio-systems can be adopted and modified so as to measure 'standard stress' in financial markets. This is achieved by employing structural complexity analysis, based on variants of univariate and multivariate sample entropy, to estimate the stress level of both financial markets on the whole and the performance of the individual financial indices. Further, we propose a novel graphical framework to establish the sensitivity of individual assets and stock markets to financial crises. This is achieved through Catastrophe Theory and entropy-based stress evaluations indicating the unique performance of each index/individual stock in response to different crises. Four major indices and four individual equities with gold prices are considered over the past 32 years from 1991-2021. Our findings based on nonlinear analyses and the proposed framework support the Efficient Market Hypothesis and reveal the relations among economic indices and within each price time series.