SENTINEL: Symbiotic Ecosystem Networks for Transparent, Intelligent, and Ecologically-Locked Trading - An AI Immune System for Global Financial Markets

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Authors: Hari Vignesh BALAJI
Cited by: 0

Abstract

Something is breaking inside global financial markets, and most of the instruments we have built to watch for trouble are pointed in the wrong direction. Algorithmic trading systems—now responsible for the overwhelming majority of transactions on major exchanges—are converging on identical strategies at an accelerating rate, producing what we term algorithmic monoculture: a condition in which the strategic diversity required for stable price discovery quietly collapses while every surface-level metric of market health appears normal. Existing safeguards—circuit breakers, position limits, post-hoc surveillance—were architected for a world of human traders and remain structurally blind to this new category of systemic fragility. This paper introduces SENTINEL (Symbiotic Ecosystem Networks for Transparent, Intelligent, and Ecologically Locked Trading), a prototype system that reconceives market protection through the lens of computational immunology, Lotka-Volterra population dynamics, and multi-agent reinforcement learning. We present three contributions that, to our knowledge, have no direct precedent in the literature: (1) the Algorithmic Biodiversity Index (ABI), a formally derived, real-time metric for quantifying strategic diversity with proved boundedness, monotonicity, and Lipschitz continuity; (2) Adversarial Diversity Injection (ADI), a controlled mechanism for introducing counter-strategies that restore ecosystem heterogeneity; and (3) Predictive Cascade Mapping via temporal graph networks. Agent-based simulations across 10,000 market episodes demonstrate 73% cascade reduction, 4.2× faster shock recovery, and sustained biodiversity above critical collapse thresholds. The core argument is simple, if uncomfortable: markets now need immune systems, and we had better build them before the next crash forces the question.

Fields of Study & Subjects

Complex Systems and Time Series Analysis Financial Markets and Investment Strategies Artificial Immune Systems Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
4 March 2026
Language
EN
Document type
Preprint