Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies
Our study is based on the hypothesis that stock exchanges, being nonlinear, open and dissipative systems, are capable of self-organization to the edge of a phase transition. To empirically support the hypothesis, we find segments in hourly stock volume series for 3,000 stocks of publicly traded comp...
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| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Physics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2024.1508465/full |
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| author | Andrey Dmitriev Andrey Dmitriev Andrey Lebedev Vasily Kornilov Victor Dmitriev |
| author_facet | Andrey Dmitriev Andrey Dmitriev Andrey Lebedev Vasily Kornilov Victor Dmitriev |
| author_sort | Andrey Dmitriev |
| collection | DOAJ |
| description | Our study is based on the hypothesis that stock exchanges, being nonlinear, open and dissipative systems, are capable of self-organization to the edge of a phase transition. To empirically support the hypothesis, we find segments in hourly stock volume series for 3,000 stocks of publicly traded companies, corresponding to the time of stock exchange’s stay to the edge of a phase transition. We provide a theoretical justification of the hypothesis and present a phenomenological model of stock exchange self-organization to the edge of the first-order phase transition and to the edge of the second-order phase transition. In the model, the controlling parameter is entropy as a measure of uncertainty of information about a share of a public company, guided by which stock exchange players make a decision to buy/sell it. The order parameter is determined by the number of buy/sell transactions by stock exchange players of a public company’s shares, i.e., stock’s volume. By applying statistical tests and the AUC metric, we found the most effective early warning measures from the set of investigated critical deceleration measures, multifractal measures and reconstructed phase space measures. The practical significance of our study is determined by the possibility of early warning of self-organization of stock exchanges to the edge of a phase transition and can be extended with high frequency data in the future research. |
| format | Article |
| id | doaj-art-5d5ff8733dba4ba2b6897cc325f94b90 |
| institution | Kabale University |
| issn | 2296-424X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj-art-5d5ff8733dba4ba2b6897cc325f94b902025-01-22T05:19:51ZengFrontiers Media S.A.Frontiers in Physics2296-424X2025-01-011210.3389/fphy.2024.15084651508465Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studiesAndrey Dmitriev0Andrey Dmitriev1Andrey Lebedev2Vasily Kornilov3Victor Dmitriev4Big Data and Information Retrieval School, HSE University, Moscow, RussiaCybersecurity Research Center, University of Bernardo O’Higgins, Santiago, ChileBig Data and Information Retrieval School, HSE University, Moscow, RussiaGraduate School of Business, HSE University, Moscow, RussiaBig Data and Information Retrieval School, HSE University, Moscow, RussiaOur study is based on the hypothesis that stock exchanges, being nonlinear, open and dissipative systems, are capable of self-organization to the edge of a phase transition. To empirically support the hypothesis, we find segments in hourly stock volume series for 3,000 stocks of publicly traded companies, corresponding to the time of stock exchange’s stay to the edge of a phase transition. We provide a theoretical justification of the hypothesis and present a phenomenological model of stock exchange self-organization to the edge of the first-order phase transition and to the edge of the second-order phase transition. In the model, the controlling parameter is entropy as a measure of uncertainty of information about a share of a public company, guided by which stock exchange players make a decision to buy/sell it. The order parameter is determined by the number of buy/sell transactions by stock exchange players of a public company’s shares, i.e., stock’s volume. By applying statistical tests and the AUC metric, we found the most effective early warning measures from the set of investigated critical deceleration measures, multifractal measures and reconstructed phase space measures. The practical significance of our study is determined by the possibility of early warning of self-organization of stock exchanges to the edge of a phase transition and can be extended with high frequency data in the future research.https://www.frontiersin.org/articles/10.3389/fphy.2024.1508465/fullphase transitionself-organized criticalityearly warning signalssandpile cellular automatastock exchangeeconophysical modeling |
| spellingShingle | Andrey Dmitriev Andrey Dmitriev Andrey Lebedev Vasily Kornilov Victor Dmitriev Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies Frontiers in Physics phase transition self-organized criticality early warning signals sandpile cellular automata stock exchange econophysical modeling |
| title | Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies |
| title_full | Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies |
| title_fullStr | Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies |
| title_full_unstemmed | Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies |
| title_short | Self-organization of the stock exchange to the edge of a phase transition: empirical and theoretical studies |
| title_sort | self organization of the stock exchange to the edge of a phase transition empirical and theoretical studies |
| topic | phase transition self-organized criticality early warning signals sandpile cellular automata stock exchange econophysical modeling |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2024.1508465/full |
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