Identifying stock market crashes by fuzzy measures of complexity

dc.contributor.authorBielinskyi, Andrii
dc.contributor.authorSoloviov, Volodymyr
dc.contributor.authorSemerikov, Serhii
dc.contributor.authorSoloviova, Viktoriia
dc.date.accessioned2024-04-01T09:14:29Z
dc.date.available2024-04-01T09:14:29Z
dc.date.issued2021
dc.description.abstractThis 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.
dc.identifier.citationIdentifying stock market crashes by fuzzy measures of complexity / Andrii Bielinskyi, Vladimir Soloviev, Serhiy Semerikov, Viktoria Solovieva // Нейро-нечіткі технології моделювання в економіці : наук.-анал. журн. / М-во освіти і науки України, ДВНЗ «Київ. нац. екон. ун-т ім. Вадима Гетьмана» ; [редкол.: А. В. Матвійчук (голов. ред.) та ін.]. – Київ : КНЕУ, 2021. – № 10. – С. 3–45.
dc.identifier.doi10.33111/nfmte.2021.003
dc.identifier.issn2306-3289
dc.identifier.urihttps://ir.kneu.edu.ua/handle/2010/43383
dc.language.isoen
dc.publisherДВНЗ «Київський національний економічний університет імені Вадима Гетьмана»
dc.subjectcrash
dc.subjectcritical event
dc.subjectstock market
dc.subjectentropy
dc.subjectrecurrence plot
dc.subjectfuzzy set theory
dc.subjectindicator-precursor of crisis phenomena
dc.subjectfuzzy measure of complexity
dc.titleIdentifying stock market crashes by fuzzy measures of complexity
dc.typeArticle
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