Mehmood, AhsanLiu, Zhi-GuoUsta, FuatSamraiz, Muhammad2026-07-012026-07-012025978-044323952-6978-044323953-3https://doi.org/10.1016/B978-0-44-323952-6.00007-9https://hdl.handle.net/20.500.12684/23025In this work, we detect chaos and multiple attractors in a financial model by utilizing a modified version of the Atangana-Baleanu Caputo (MABC) fractional derivative operator (FDO) with respect to another function in a mathematical model (Mmd). This approach enhances our understanding and prediction of stock market behavior. We employ an iterative method and fixed-point theory to determine whether a unique solution exists for this model. Additionally, we convert the nonlinear kernel of the MABC into a linear one to solve the Mmd and study its accuracy. Numerical tests are conducted to confirm the results. This research is devoted to improving the precision of stock exchange evaluation and early detection, ultimately contributing to better strategic planning. Finally, the graphical representations illustrate how different choices of fractional orders affect the interest rate, investment needs, price index, and average profit margin. © 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.en10.1016/B978-0-44-323952-6.00007-9info:eu-repo/semantics/closedAccessFinancial modelFractional derivativeFractional modelingLaplace transformMittag-Leffler functionSimulationsBook Part21362-s2.0-105019743163N/A