A Theoretical Framework for Dynamic Volatility Analysis in Slot Machines: A Regime-Switching Hidden Markov Model (MS-HMM) Approach
Year: 2026
Type: preprint
Abstract: This paper presents a theoretical framework that addresses the limitations of traditional, static volatility analysis in multi-state stochastic systems. By implementing a Regime-Switching Hidden Markov Model (MS-HMM) grounded in Extreme Value Theory (EVT), this approach accurately captures the volatility dynamics and conditional heteroskedasticity inherent in modern game design. The proposed analytical framework allows for the exact calculation of a robust, dynamic volatility index without relying on Monte Carlo simulations, outperforming standard Independent and Identically Distributed (IID) assumptions.
Author: Lombardo, Wilson Andres
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7171773191
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