Identifying financial crises in real time

TL;DR

This paper introduces a real-time index based on thermodynamic measures derived from multifractal analysis to detect and distinguish financial crises, demonstrating robustness on historical crashes and potential for forecasting.

Contribution

It presents a novel thermodynamic index for real-time detection of financial crises, capable of distinguishing different crisis types and providing forecasting insights.

Findings

Successfully identified major historical crashes with clear signals.

Differentiated the 2011 market fluctuations from previous crises.

Showed potential for crisis forecasting using the proposed index.

Abstract

Following the thermodynamic formulation of multifractal measure that was shown to be capable of detecting large fluctuations at an early stage, here we propose a new index which permits us to distinguish events like financial crisis in real time . We calculate the partition function from where we obtain thermodynamic quantities analogous to free energy and specific heat. The index is defined as the normalized energy variation and it can be used to study the behavior of stochastic time series, such as financial market daily data. Famous financial market crashes - Black Thursday (1929), Black Monday (1987) and Subprime crisis (2008) - are identified with clear and robust results. The method is also applied to the market fluctuations of 2011. From these results it appears as if the apparent crisis of 2011 is of a different nature from the other three. We also show that the analysis has forecasting capabilities.