Metastable Financial Markets

TL;DR

This paper models financial markets as metastable systems, proposing that market states drive the evolution of financial time series, which offers a new perspective for risk assessment and investment strategies.

Contribution

It introduces a novel theory linking market metastability to the evolution of financial time series, emphasizing the role of market states in driving investment performance.

Findings

Financial time series can be modeled as hidden Markov models.

Market states influence the non-stationary behavior of financial data.

The approach improves risk assessment by accounting for metastable market dynamics.

Abstract

Metastability is a phenomenon observed in stochastic systems which stay in a false-equilibrium within a region of its state space until the occurrence of a sequence of rare events that leads to an abrupt transition to a different region. This paper presents financial markets as metastable systems and shows that, under this assumption, financial time series evolve as hidden Markov models. In special, we propose a theory that outlines an explicit causal relation between a financial market and the evolution of a financial time series. In the context of financial economics and causal factor investment, this theory introduces a paradigm shift, suggesting that investment performance fluctuations are primarily driven by the market state rather than direct causation by other variables. While not incompatible with traditional causal inference, our approach addresses the non-stationary evolution of time series through changes in market states, enhancing risk assessment and enabling mitigation strategies.