Wealth or Stealth? The Camouflage Effect in Insider Trading

ArXiv ID: 2512.06309 “View on arXiv”

Authors: Jin Ma, Weixuan Xia, Jianfeng Zhang

Abstract

We consider a Kyle-type model where insider trading takes place among a potentially large population of liquidity traders and is subject to legal penalties. Insiders exploit the liquidity provided by the trading masses to “camouflage” their actions and balance expected wealth with the necessary stealth to avoid detection. Under a diverse spectrum of prosecution schemes, we establish the existence of equilibria for arbitrary population sizes and a unique limiting equilibrium. A convergence analysis determines the scale of insider trading by a stealth index $γ$, revealing that the equilibrium can be closely approximated by a simple limit due to diminished price informativeness. Empirical aspects are derived from two calibration experiments using non-overlapping data sets spanning from 1980 to 2018, which underline the indispensable role of a large population in insider trading models with legal risk, along with important implications for the incidence of stealth trading and the deterrent effect of legal enforcement.

Keywords: Kyle-type Model, Insider Trading, Equilibrium Analysis, Legal Risk, Stealth Index, Equities

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 5.0/10
  • Quadrant: Holy Grail
  • Why: The paper employs advanced game theory (Kyle-type model) with convergence analysis and a unique stealth index, indicating high mathematical complexity. It also includes empirical calibration with long-term non-overlapping data (1980-2018) and references specific datasets, demonstrating substantial empirical rigor.
  flowchart TD
    A["Research Goal<br>Modeling Insider Trading<br>with Legal Risk & Camouflage"] --> B["Methodology<br>Kyle-Type Model &<br>Stealth Index Gamma"]
    B --> C["Computation<br>Equilibrium Existence &<br>Limiting Approximation"]
    C --> D["Data Inputs<br>Equities Data 1980-2018<br>(Two Calibration Sets)"]
    D --> E{"Calibration &<br>Analysis"}
    E --> F["Key Findings<br>Large Population Necessity<br>Deterrent Effect of Legal Risk<br>Stealth Trading Implications"]