Paper: arXiv 2604.11100

Authors: Huisheng Wang, H. Vicky Zhao

Abstract

Herding, where investors imitate others’ decisions rather than relying on their own analysis, is a prevalent phenomenon in financial markets. Excessive herding distorts rational decisions, amplifies volatility, and can be exploited by manipulators to harm the market. Traditional regulatory tools, such as information disclosure and transaction restrictions, are often imprecise and lack theoretical guarantees for effectiveness. This calls for a quantitative approach to regulating herding. We propose a regulator-leader-follower trilateral game framework based on optimal control theory to study the complex dynamics among them. The leader makes rational decisions, the follower maximizes utility while aligning with the leader’s decisions, whereas the regulator designs a mechanism to maximize social welfare and minimize regulatory cost. We derive the follower’s decisions and the regulator’s mechanisms, theoretically analyze the impact of regulation on decisions, and investigate effective mechanisms to improve social welfare.

Complexity vs Empirical Score

  • Math Complexity: 8.0/10
  • Empirical Rigor: 2.5/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper introduces a novel trilateral game framework using optimal control theory and mechanism design to address financial market herding. While mathematically sophisticated and theoretical complete, it lacks empirical validation, backtesting, or real-world market data application.

Research Flowchart

  flowchart TD
    A[Research Goal: Regulate Financial Herding to Maximize Social Welfare] --> B[Input Parameters: Investor Utilities, Herding Tendencies & Regulatory Costs]
    B --> C[Trilateral Game Framework: Regulator, Leader & Follower]
    C --> D[Computational Engine: Optimal Control Theory]
    D --> E[Derive Follower Response & Design Regulatory Mechanism]
    E --> F[Outcomes: Quantitative Mechanism Minimizes Volatility & Improves Social Welfare]

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5 of 79 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.