A Collocation Method Using Diagonal Polynomials for Pricing Geometric Asian Options Under the Mixed Fractional Heston Model

In this paper, we introduce an efficient computational framework for pricing geometric Asian options based on a collocation method. The approach employs a collocation scheme utilizing a specific class of diagonal polynomials to construct operational matrices. The sparse structure of these matrices, containing a significant number of zeros, enhances computational efficiency. We solve the governing partial differential equation (PDE) by representing the solution as a series of multivariate diagonal functions with unknown coefficients. Subsequently, we derive the operational matrices for the differential operators and their associated partial derivatives, demonstrating how this formalism transforms the original pricing problem into a tractable system of nonlinear algebraic equations. Furthermore, we provide a rigorous convergence analysis of the proposed collocation method. Finally, we present numerical examples that demonstrate the method’s applicability, robustness, and computational effectiveness. The obtained results, supported by a strong theoretical foundation, indicate the considerable potential of this approach for practical financial applications.

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Publication Details

Journal
Mathematics
Published
2026-04-24
DOI
https://doi.org/10.3390/math14091439
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00

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article

A Collocation Method Using Diagonal Polynomials for Pricing Geometric Asian Options Under the Mixed Fractional Heston Model

Fares Alazemi, Abdulaziz Alsenafi
Mathematics
Stochastic processes and financial applications
article

A Collocation Method Using Diagonal Polynomials for Pricing Geometric Asian Options Under the Mixed Fractional Heston Model

Fares Alazemi, Abdulaziz Alsenafi
article en

Abstract

In this paper, we introduce an efficient computational framework for pricing geometric Asian options based on a collocation method. The approach employs a collocation scheme utilizing a specific class of diagonal polynomials to construct operational matrices. The sparse structure of these matrices, containing a significant number of zeros, enhances computational efficiency. We solve the governing partial differential equation (PDE) by representing the solution as a series of multivariate diagonal functions with unknown coefficients. Subsequently, we derive the operational matrices for the differential operators and their associated partial derivatives, demonstrating how this formalism transforms the original pricing problem into a tractable system of nonlinear algebraic equations. Furthermore, we provide a rigorous convergence analysis of the proposed collocation method. Finally, we present numerical examples that demonstrate the method’s applicability, robustness, and computational effectiveness. The obtained results, supported by a strong theoretical foundation, indicate the considerable potential of this approach for practical financial applications.

MathematicsVol. 14(9)
Kuwait University (KW)
Kuwait University
Decent work and economic growth
Openalex Percentile: Top 15%
Stochastic processes and financial applications
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