Type-3 fuzzy logic and Lyapunov approach for dynamic modeling and analysis of financial markets
Yan S.-R. Mohammadzadeh A. Ghaderpour E.
15 July 2024Elsevier Ltd
Heliyon
2024#10Issue 13
Chaos theory offers a new way to investigate variations in financial markets data that cannot be obtained with traditional methods. The primary approach for diagnosing chaos is the existence of positive small Lyapunov views. The positive Lyapunov index indicates the average instability and the systems chaotic nature. The negativity indicates the average rate of non-chaoticness. In this paper, a new approach on basis of type-3 fuzzy logic systems is introduced for modeling the chaotic dynamics of financial data. Also, the attracting dimension tests and the Lyapunov views in the reconstructed dynamics are used for examinations. The simulations on case-study currency market show the applicability and good accuracy of the suggested approach.
Financial chaotic systems , Financial markets , Fuzzy logic systems , Learning , Lyapunov views , Type-3 fuzzy logic
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School of Finance, Guangzhou Huashang University, Guangzhou, 511300, China
Department of Computational and Data Science, Astana IT University, Prospekt Mangilik Yel., Astana, 020000, Kazakhstan
Earth and Space Inc., Calgary, T3A 5B1, Canada
Department of Earth Sciences, Sapienza University of Rome, P.le Aldo Moro, 5, RM, Rome, 00185, Italy
School of Finance
Department of Computational and Data Science
Earth and Space Inc.
Department of Earth Sciences
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