IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i8p1240-d1631329.html
   My bibliography  Save this article

Granular Fuzzy Fractional Financial Systems Governed by Granular Caputo Fractional Derivative

Author

Listed:
  • Feryal Abdullah Aladsani

    (Department of Mathematics and Statistics, College of Science, King Faisal University, Hafuf 31982, Al Ahsa, Saudi Arabia)

  • Ghulam Muhammad

    (Department of Mathematics, Lahore Garrison University, Lahore 54000, Pakistan)

  • Sayed K. Elagan

    (Department of Mathematics and Computer Sciences, Faculty of Science, Menoufia University, Shebin Elkom 32511, Egypt
    Department of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

Abstract

A granular fuzzy fractional financial system (GFFFS) is important for modeling real-world market uncertainties and complexities compared to conventional financial models. Unlike traditional approaches, a GFFFS offers enhanced precision in risk assessment, captures the long-term memory effects with the fractional derivatives, and effectively deals with the uncertainty and granularity in financial data through fuzzy logic. This model overcomes the limitations of the traditional model by accurately representing nonlinear dynamics, extreme volatility, and uncertain behavioral shifts in financial markets. The study of such models can be complex and challenging. However, developing an effective technique for solving such systems analytically and approximately is essential. This article aims to introduce and investigate a GFFFS using granular Caputo fractional derivatives. The behavior of the proposed model is studied using two distinct approaches, including an analytical approach, by applying the fuzzy Laplace transform technique and a numerical approach by employing fuzzy integral equations. Moreover, the existence and uniqueness of the extracted fuzzy solution are determined using the Banach contraction principle. To analyze the nonlinearity of the proposed model, the introduced numerical scheme is employed to illustrate the uncertain behavior of the proposed model graphically. This research provides deeper insights that can help decision-makers make better financial market decisions.

Suggested Citation

  • Feryal Abdullah Aladsani & Ghulam Muhammad & Sayed K. Elagan, 2025. "Granular Fuzzy Fractional Financial Systems Governed by Granular Caputo Fractional Derivative," Mathematics, MDPI, vol. 13(8), pages 1-24, April.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:8:p:1240-:d:1631329
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/8/1240/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/8/1240/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rami Ahmad El-Nabulsi & Waranont Anukool, 2025. "Qualitative financial modelling in fractal dimensions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-47, December.
    2. Syed Ali, M. & Narayanan, Govindasamy & Shekher, Vineet & Alsulami, Hamed & Saeed, Tareq, 2020. "Dynamic stability analysis of stochastic fractional-order memristor fuzzy BAM neural networks with delay and leakage terms," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    3. Chalco-Cano, Y. & Román-Flores, H., 2008. "On new solutions of fuzzy differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 38(1), pages 112-119.
    4. Xu, Zhao & Sun, Kehui & Wang, Huihai, 2024. "Dynamics and function projection synchronization for the fractional-order financial risk system," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    5. Chian, Abraham C.-L. & Rempel, Erico L. & Rogers, Colin, 2006. "Complex economic dynamics: Chaotic saddle, crisis and intermittency," Chaos, Solitons & Fractals, Elsevier, vol. 29(5), pages 1194-1218.
    6. H. Mesgarani & Y. Esmaeelzade Aghdam & A. Beiranvand & J. F. Gómez-Aguilar, 2024. "A Novel Approach to Fuzzy Based Efficiency Assessment of a Financial System," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1609-1626, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. Rufián-Lizana & Y. Chalco-Cano & G. Ruiz-Garzón & H. Román-Flores, 2014. "On some characterizations of preinvex fuzzy mappings," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 771-783, July.
    2. Yang, Zhanying & Zhang, Jie & Zhang, Zhihui & Mei, Jun, 2023. "An improved criterion on finite-time stability for fractional-order fuzzy cellular neural networks involving leakage and discrete delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 910-925.
    3. Thanh-Lam Nguyen, 2017. "Methods in Ranking Fuzzy Numbers: A Unified Index and Comparative Reviews," Complexity, Hindawi, vol. 2017, pages 1-13, July.
    4. Dominique Guégan & Justin Leroux, 2008. "Local Lyapunov exponents: Zero plays no role in Forecasting chaotic systems," Cahiers de recherche 08-10, HEC Montréal, Institut d'économie appliquée.
    5. Richter, Hendrik, 2008. "On a family of maps with multiple chaotic attractors," Chaos, Solitons & Fractals, Elsevier, vol. 36(3), pages 559-571.
    6. Ding, Yuting & Jiang, Weihua & Wang, Hongbin, 2012. "Hopf-pitchfork bifurcation and periodic phenomena in nonlinear financial system with delay," Chaos, Solitons & Fractals, Elsevier, vol. 45(8), pages 1048-1057.
    7. Xu, Changjin & Liu, Zixin & Liao, Maoxin & Li, Peiluan & Xiao, Qimei & Yuan, Shuai, 2021. "Fractional-order bidirectional associate memory (BAM) neural networks with multiple delays: The case of Hopf bifurcation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 471-494.
    8. Eman Hussain & Ayad Ali, 2013. "Homotopy Analysis Method for Solving Fuzzy Integro-Differential Equations," Modern Applied Science, Canadian Center of Science and Education, vol. 7(3), pages 1-15, March.
    9. Dominique Guegan & Justin Leroux, 2009. "Forecasting chaotic systems: The role of local Lyapunov exponents," PSE-Ecole d'économie de Paris (Postprint) halshs-00431726, HAL.
    10. Nguyen Dinh Phu, 2016. "On Nonlocal Initial Problems for Fuzzy Differential Equations and Environmental Pollution Problems," Academic Journal of Applied Mathematical Sciences, Academic Research Publishing Group, vol. 2(8), pages 77-92, 08-2016.
    11. Chen, Wei-Ching, 2008. "Nonlinear dynamics and chaos in a fractional-order financial system," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1305-1314.
    12. Chagas, T.P. & Toledo, B.A. & Rempel, E.L. & Chian, A.C.-L. & Valdivia, J.A., 2012. "Optimal feedback control of the forced van der Pol system," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1147-1156.
    13. Ho Vu, 2017. "Random Fuzzy Differential Equations with Impulses," Complexity, Hindawi, vol. 2017, pages 1-11, June.
    14. Vasily E. Tarasov, 2019. "Rules for Fractional-Dynamic Generalizations: Difficulties of Constructing Fractional Dynamic Models," Mathematics, MDPI, vol. 7(6), pages 1-50, June.
    15. Alijani, Zahra & Baleanu, Dumitru & Shiri, Babak & Wu, Guo-Cheng, 2020. "Spline collocation methods for systems of fuzzy fractional differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    16. Li, Jiaorui & Ren, Zhengzheng & Wang, Zuoren, 2008. "Response of nonlinear random business cycle model with time delay state feedback," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5844-5851.
    17. Oliveira, José J., 2022. "Global stability criteria for nonlinear differential systems with infinite delay and applications to BAM neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    18. Harb, Ahmad M. & Smadi, Issam A., 2009. "Tracking control of DC motors via mimo nonlinear fuzzy control," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 702-710.
    19. Zhang, Guodong & Cao, Jinde, 2023. "New results on fixed/predefined-time synchronization of delayed fuzzy inertial discontinuous neural networks: Non-reduced order approach," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    20. Dominique Guegan & Justin Leroux, 2009. "Forecasting chaotic systems: The role of local Lyapunov exponents," Post-Print halshs-00431726, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:13:y:2025:i:8:p:1240-:d:1631329. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.