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It is well documented from various empirical studies that the volatilityprocess of an asset price dynamics is stochastic. This phenomenon called for anew approach to describing the random evolution of volatility through time withstochastic models. In this paper, we propose a mean-reverting theta-rho modelfor asset price dynamics where the volatility diffusion factor of this modelfollows a highly non-linear CEV-type process. Since this model lacks aclosed-form formula, we construct a new truncated EM method to study itnumerically under the Khasminskii-type condition. We justify that the truncatedEM solutions can be used to evaluate a path-dependent financial product.

Numerical Method for Highly Non-linear Mean-reverting Asset Price Model with CEV-type Process