Mechanism Design for Investment Regulation under Herding

TL;DR

This paper develops a game-theoretic framework using optimal control to design regulatory mechanisms that mitigate herding in financial markets, aiming to enhance social welfare.

Contribution

It introduces a novel trilateral game model for regulation, deriving optimal mechanisms with theoretical analysis to control herding effects.

Findings

Derived the follower's decision-making process.

Designed mechanisms that improve social welfare.

Analyzed the impact of regulation on investor decisions.

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.