This study aims to fill a gap in cryptocurrency regulation research by establishing a dynamic framework that balances market stability and capital flight. It seeks to derive an optimal, adaptive regulatory strategy that reconciles stringent enforcement with its unintended consequences. Ultimately, the study provides insights to guide policymakers in designing interventions that sustain financial stability while supporting efficient market functioning in the evolving digital asset environment.
This study develops a differential game-theoretic model to capture the dynamic interplay between cryptocurrency regulators and market participants. Using stochastic differential equations to model market stability and capital flight, the framework derives Nash equilibrium conditions for optimal regulatory intensity and liquidity migration. The model is validated through Monte Carlo simulations that examine various market scenarios and sensitivity analyses for robustness across different parameter settings.
Results indicate that an aggressive initial regulatory stance rapidly enhances market stability, albeit at the cost of a temporary increase in capital flight. Over time, adaptive regulatory adjustments lead to a self-stabilizing equilibrium where volatility diminishes and liquidity migration is contained. The Nash equilibrium analysis confirms that a balanced enforcement strategy can effectively mitigate the adverse impacts of capital flight while maintaining overall market resilience, as supported by consistent outcomes from the simulation experiments.
The model’s simplifying assumptions, including a homogeneous market and single regulator framework, limit its immediate real world applicability. It uses a continuous time approach and normally distributed shocks, which may not capture discrete regulatory events or extreme market disruptions. Additionally, the analysis is sensitive to parameter calibration. These limitations suggest further research is needed to incorporate multi-agent dynamics, market microstructure factors and alternative stochastic processes to improve empirical validation and practical relevance.
The study provides policymakers a dynamic framework for calibrating regulatory intensity to balance market stability with the risk of capital flight. It emphasizes that while strict initial enforcement can stabilize markets, subsequent moderation is key to sustaining resilience. The derived equilibrium conditions provide actionable insights for designing adaptive, real-time interventions that minimize liquidity outflows and improve overall market integrity, supporting a regulatory approach that promotes innovation while mitigating systemic risks.
This research pioneers the application of differential game theory to cryptocurrency regulation, integrating market stability and capital flight into a single dynamic model. By deriving Nash equilibrium conditions and validating the framework through numerical experiments, the paper advances current literature and provides a novel, theoretically rigorous tool. Its innovative perspective equips policymakers with a nuanced approach to designing responsive regulatory strategies in the fast-evolving digital asset space.
