Preprint / Version 1

Markets as Adversarial Control Systems: Stability, Metastability, and Feedback-Induced Instability

##article.authors##

  • Krishna Bajpai Individual Researcher

DOI:

https://doi.org/10.31224/6076

Keywords:

Control theory, Algorithmic Trading, metastability, market microstructure

Abstract

Modern electronic markets have undergone a structural transition from human-mediated exchange mechanisms to high-frequency adversarial control systems governed by competing algorithmic feedback laws. While traditional economic theory attributes market dislocations to behavioral biases or exogenous shocks, such explanations fail to account for instabilities arising in environments populated by rational, mathematically optimized agents. This paper reframes financial markets as dynamical plants controlled by heterogeneous, interacting controllers operating under latency, information, and impact constraints. We show that instability is not anomalous but emerges endogenously from optimal feedback operating in non-normal, metastable state spaces. Introducing the concepts of metastable markets, non-normal transient amplification, and a quantitative Control Fragility Index (CFI), we demonstrate how markets can appear statistically stable while remaining critically sensitive to marginal changes in control gain, synchronization, or delay. We further identify a six-part taxonomy of feedbackinduced instabilities—including reflexive resonance, information gradient collapse, and liquidity phase transitions—that arise without manipulation, deception, or irrational behavior. Finally, we argue that market stability must be treated as a firstclass design constraint and propose design-level regulatory interventions grounded in control theory rather than behavioral restriction. Our results suggest that systemic instability is the natural byproduct of local optimality in adversarial feedback environments and that equilibrium existence alone is insufficient to guarantee dynamical safety.

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Posted

2025-12-23