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A study on the fractional Black–Scholes option pricing model of the financial market via the Yang-Abdel-Aty-Cattani operator.

Authors :
Ghosh, Surath
Source :
Engineering Computations. 2024, Vol. 41 Issue 3, p611-629. 19p.
Publication Year :
2024

Abstract

Purpose: Financial mathematics is one of the most rapidly evolving fields in today's banking and cooperative industries. In the current study, a new fractional differentiation operator with a nonsingular kernel based on the Robotnov fractional exponential function (RFEF) is considered for the Black–Scholes model, which is the most important model in finance. For simulations, homotopy perturbation and the Laplace transform are used and the obtained solutions are expressed in terms of the generalized Mittag-Leffler function (MLF). Design/methodology/approach: The homotopy perturbation method (HPM) with the help of the Laplace transform is presented here to check the behaviours of the solutions of the Black–Scholes model. HPM is well known for its accuracy and simplicity. Findings: In this attempt, the exact solutions to a famous financial market problem, namely, the BS option pricing model, are obtained using homotopy perturbation and the LT method, where the fractional derivative is taken in a new YAC sense. We obtained solutions for each financial market problem in terms of the generalized Mittag-Leffler function. Originality/value: The Black–Scholes model is presented using a new kind of operator, the Yang-Abdel-Aty-Cattani (YAC) operator. That is a new concept. The revised model is solved using a well-known semi-analytic technique, the homotopy perturbation method (HPM), with the help of the Laplace transform. Also, the obtained solutions are compared with the exact solutions to prove the effectiveness of the proposed work. The different characteristics of the solutions are investigated for different values of fractional-order derivatives. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02644401
Volume :
41
Issue :
3
Database :
Academic Search Index
Journal :
Engineering Computations
Publication Type :
Academic Journal
Accession number :
177166497
Full Text :
https://doi.org/10.1108/EC-08-2023-0452