Financial stress evaluation: a complexity science approach

Abstract Financial markets typically exhibit dynamically complex properties as they continuously interact with economic and environmental factors. For example, the efficient market hypothesis suggests a considerable 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 physiological stress of bio-signals, we investigate whether physical stress indices in bio-systems can be adopted and modified to measure “standard stress” in financial markets. We employ structural complexity analysis based on univariate and multivariate sample entropy variants to estimate the overall stress level of financial markets and the performance of individual financial indices. Furthermore, we propose a novel graphical framework to determine the sensitivity of individual assets and stock markets to financial crises. Catastrophe theory and entropy-based stress evaluations are used to ascertain the unique performance of each index or individual stock in response to different types of crisis. Four major indices and four individual equities with gold prices are considered over 31 years, from 1991 to 2021. Results show the feasibility of measuring financial stress and reveal the relationship between structural complexity among economic indices and within each price time series.