Financial markets represent complex adaptive systems characterized by nonlinear dynamics, volatility clustering, regime shifts, and metastable behavior. Despite extensive advances in quantitative finance, the early detection of structural market destabilization remains a fundamentally unresolved problem. Most conventional indicators rely primarily on price trajectories or local statistical transformations and fail to capture the degradation of relaxation dynamics preceding critical market transitions. This study introduces PSI (Perturbation Susceptibility Index), a novel stability-based framework designed to quantify structural market susceptibility through the relationship between perturbation intensity and the system’s relaxation capacity. The proposed metric is defined as PSI = σ / λ², where σ denotes realized volatility and λ represents a relaxation parameter derived from the autocorrelation structure of absolute returns. High PSI values correspond to states in which volatility growth is accompanied by slowing relaxation dynamics, indicating elevated structural fragility and increased susceptibility to volatility expansions and regime transitions. The empirical analysis utilizes intraday and high-frequency historical data across multiple asset classes, including cryptocurrency futures, equity indices, index futures, commodities, and energy markets. The results demonstrate that elevated PSI values systematically precede periods of increased realized volatility, breakout events, and transitions into unstable market regimes, particularly in highly liquid intraday environments characterized by pronounced microstructural dynamics. The findings further suggest that PSI captures not only the instantaneous amplitude of volatility but also deeper degradation of market relaxation stability. At the same time, the framework should not be interpreted as a deterministic forecasting model or universal volatility predictor. Instead, PSI appears to function primarily as a probabilistic indicator of structural market susceptibility under conditions of intraday market stress. The study integrates concepts from stochastic volatility, critical slowing down, market microstructure, and complex systems theory into a unified framework for analyzing instability and critical transitions in financial markets.
Martin Petrásek (Sun,) studied this question.