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Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling

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  • Kiarash Firouzi

Abstract

Extreme volatility, nonlinear dependencies, and systemic fragility are characteristics of cryptocurrency markets. The assumptions of normality and centralized control in traditional financial risk models frequently cause them to miss these changes. Four components-volatility stress testing, stablecoin hedging, contagion modeling, and Monte Carlo simulation-are integrated into this paper's modular simulation framework for crypto portfolio risk analysis. Every module is based on mathematical finance theory, which includes stochastic price path generation, correlation-based contagion propagation, and mean-variance optimization. The robustness and practical relevance of the framework are demonstrated through empirical validation utilizing 2020-2024 USDT, ETH, and BTC data.

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  • Kiarash Firouzi, 2025. "Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling," Papers 2507.08915, arXiv.org.
    • Handle: RePEc:arx:papers:2507.08915
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    References listed on IDEAS

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    1. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
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