Analytical Formula for Fractional-Order Conditional Moments of Nonlinear Drift CEV Process with Regime Switching: Hybrid Approach with Applications

TL;DR

This paper derives an exact analytical formula for fractional-order conditional moments of nonlinear drift CEV processes with regime switching, improving modeling and valuation in stochastic financial environments.

Contribution

It introduces a hybrid approach to obtain closed-form expressions for moments of regime-switching nonlinear CEV processes, enhancing analytical tractability and practical applications.

Findings

Validated formulas with Monte Carlo simulations

Demonstrated improved derivative pricing accuracy

Enhanced understanding of regime-switching stochastic models

Abstract

This paper introduces an analytical formula for the fractional-order conditional moments of nonlinear drift constant elasticity of variance (NLD-CEV) processes under regime switching, governed by continuous-time finite-state irreducible Markov chains. By employing a hybrid system approach, we derive exact closed-form expressions for these moments across arbitrary fractional orders and regime states, thereby enhancing the analytical tractability of NLD-CEV models under stochastic regimes. Our methodology hinges on formulating and solving a complex system of interconnected partial differential equations derived from the Feynman-Kac formula for switching diffusions. To illustrate the practical relevance of our approach, Monte Carlo simulations for process with Markovian switching are applied to validate the accuracy and computational efficiency of the analytical formulas. Furthermore, we apply our findings for the valuation of financial derivatives within a dynamic nonlinear mean-reverting regime-switching framework, which demonstrates significant improvements over traditional methods. This work offers substantial contributions to financial modeling and derivative pricing by providing a robust tool for practitioners and researchers who are dealing with complex stochastic environments.