A New Attempt to Identify Long-term Precursors for Endogenous Financial Crises in the Market Correlation Structures

TL;DR

This paper investigates long-term precursors to financial crises by analyzing the evolution of market correlation structures and identifying quasi-stationary market states over a 16-year period, including major crises.

Contribution

It introduces a novel approach using market states derived from correlation structures to find potential long-term indicators of systemic risk.

Findings

Certain market states precede major crises

Market correlation structures show identifiable patterns before crises

Some features may serve as early warning indicators

Abstract

Prediction of events in financial markets is every investor's dream and, usually, wishful thinking. From a more general, economic and societal viewpoint, the identification of indicators for large events is highly desirable to assess systemic risks. Unfortunately, the very nature of financial markets, particularly the predominantly non-Markovian character as well as non-stationarity, make this challenge a formidable one, leaving little hope for fully fledged answers. Nevertheless, it is called for to collect pieces of evidence in a variety of observables to be assembled like the pieces of a puzzle that eventually might help to catch a glimpse of long-term indicators or precursors for large events - if at all in a statistical sense. Here, we present a new piece for this puzzle. We use the quasi-stationary market states which exist in the time evolution of the correlation structure in financial markets. Recently, we identified such market states relative to the collective motion of the market as a whole. We study their precursor properties in the US stock markets over 16 years, including two endogenous crises, the dot-com bubble burst and the pre-phase of the Lehman Brothers crash. We identify certain interesting features and critically discuss their suitability as indicators.