Neuro-Fuzzy Modeling Techniques in Economics

Neuro-Fuzzy Modeling Techniques in Economics

Identifying stock market crashes by fuzzy measures of complexity

DOI:

10.33111/nfmte.2021.003

Анотація:
Abstract: This study, for the first time, presents the possibility of using fuzzy set theory in combination with information theory and recurrent analysis to construct indicators (indicators-precursors) of crisis phenomena in complex nonlinear systems. In our study, we analyze the 4 most important crisis periods in the history of the stock market – 1929, 1987, 2008 and the COVID-19 pandemic in 2020. In particular, using the sliding window procedure, we analyze how the complexity of the studied crashes changes over time, and how it depends on events such as the global stock market crises. For comparative analysis, we take classical Shannon entropy, approximation and permutation entropy, recurrent diagrams, and their fuzzy alternatives. Each of the fuzzy modifications uses three membership functions: exponential, sigmoidal, and simple linear functions. Empirical results demonstrate the fact that the fuzzification of classical entropy and recurrence approaches opens up prospects for constructing effective and reliable indicators-precursors of critical events in the studied complex systems
Ключові слова:
Key words: crash, critical event, stock market, entropy, recurrence plot, fuzzy set theory, indicator-precursor of crisis phenomena, fuzzy measure of complexity
УДК:
UDC:

JEL: C22 C58 G01 G17

To cite paper
In APA style
Bielinskyi, A., Soloviev, V., Semerikov, S., & Solovieva, V. (2021). Identifying stock market crashes by fuzzy measures of complexity. Neuro-Fuzzy Modeling Techniques in Economics, 10, 3-45. http://doi.org/10.33111/nfmte.2021.003
In MON style
Белінський А., Соловйов В., Семеріков С.О., Соловйова В. Identifying stock market crashes by fuzzy measures of complexity. Нейро-нечіткі технології моделювання в економіці. 2021. № 10. С. 3-45. http://doi.org/10.33111/nfmte.2021.003 (дата звернення: 19.06.2024).
With transliteration
Bielinskyi, A., Soloviev, V., Semerikov, S., Solovieva, V. (2021) Identifying stock market crashes by fuzzy measures of complexity. Neuro-Fuzzy Modeling Techniques in Economics, no. 10. pp. 3-45. http://doi.org/10.33111/nfmte.2021.003 (accessed 19 Jun 2024).
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