Mathematical Analysis of Financial Bubbles through Fractal Dimensionality
- 作者: Plotnikov P.V.1, Nazarov D.V.1, Chueva A.A.1, Kim Z.V.1
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隶属关系:
- The Bonch-Bruevich Saint Petersburg State University of Telecommunications
- 期: 卷 3, 编号 2 (2025)
- 页面: С3
- 栏目: Articles
- URL: https://journal-vniispk.ru/3034-2201/article/view/352477
- EDN: https://elibrary.ru/ZQZCGU
- ID: 352477
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Purpose. Financial bubbles and crises are complex phenomena related to the deviation of asset prices from their fundamental value, which requires the development of new approaches to their analysis. The aim of the paper is to investigate financial bubbles through fractal analysis techniques, including fractal dimension calculation, to identify anomalies and predict market crashes. Methods. The methods used include RS analysis (Hurst method) to assess the persistence of time series, Box-count method to determine the fractal dimension and multifractal analysis to study the local features of market dynamics. Novelty. The novelty of the study lies in the comprehensive application of fractal analysis for early detection of financial bubbles, as well as in comparing the effectiveness of different methods. Results. The results show that the increase in fractal dimension correlates with the periods of bubble formation, and its sharp changes can serve as indicators of crises, which is confirmed by the examples of the dot-com crisis (2000) and the financial crisis (2008). Practical relevance. The significance of the work lies in the possibility of using the proposed approach to create systems of early warning of crises, algorithmic trading and risk management.
作者简介
P. Plotnikov
The Bonch-Bruevich Saint Petersburg State University of Telecommunications
Email: plotnikov.pv@sut.ru
Ph. D. of Physics and Mathematics Sciences, Associate Professor, Head of the Department of Higher Mathematics St. Petersburg, 193232
D. Nazarov
The Bonch-Bruevich Saint Petersburg State University of Telecommunications
Email: plotnikov.pv@sut.ru
a Third-Year Student
St. Petersburg, 193232A. Chueva
The Bonch-Bruevich Saint Petersburg State University of Telecommunications
Email: plotnikov.pv@sut.ru
a Third-Year Student
St. Petersburg, 193232Z. Kim
The Bonch-Bruevich Saint Petersburg State University of Telecommunications
编辑信件的主要联系方式.
Email: plotnikov.pv@sut.ru
a Third-Year Student
St. Petersburg, 193232参考
- Шихалиева Д. С., Беляева С. В. Траектория экономических кризисов в России в период становления и развития рыночной экономики: оценка, эволюция, управление // Вестник Университета. 2021. № 12. doi: 10.26425/1816-4277-2021-12-144-150. EDN: ULTXXW
- Плотников А. В., Харламов А. В. Направления нейтрализации негативного влияния неэкономических шоков на реальный сектор экономики России // Известия Санкт-Петербургского государственного экономического университета. 2023. № 1 (139). EDN: QQPSKE
- Чиркова Е. В. Теории финансовых пузырей // Корпоративные финансы. 2010. Т. 4. № 3 (15). С. 63–72. EDN: NBNQXD
- Кошелев В. Л., Кошелев И. В. Иррациональные трейдеры на финансовых рынках // Актуальные вопросы экономического развития регионов: Материалы Международной научно-практической конференции (Пятигорск, 8 июня 2013 г.). Пятигорск: ООО «Рекламно-информационное агентство на КМВ», 2013. С. 398–405. EDN: TRPANP
- Peters E. E. Fractal Market Analysis: Applying Chaos Theory to Investment and Economics. New York: John Wiley & Sons, 1994.
- Зиненко А. В. R/S анализ на фондовом рынке // Бизнес-информатика. 2012. № 3 (21). С. 24–30. EDN: PEOSKN
- Grech D., Mazur Z. Can One Make any Crash Prediction in Finance Using the Local Hurst Exponent Idea? // Physica A: Statistical Mechanics and its Applications. 2004. Vol. 336. Iss. 1–2. PP. 133–145. doi: 10.1016/j.physa.2004.01.018
- Kantelhardt J. W., Zschiegner S. A., Koscielny-Bunde E., Havlin S., Bunde A., et al. Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series // Physica A: Statistical Mechanics and its Applications. 2002. Vol. 316. Iss. 1–4. PP. 87–114. doi: 10.1016/S0378-4371(02)01383-3. EDN: MCPRUN
- Jiang Z. Q., Xie W. J., Zhou W. X., Sornette D. Multifractal Analysis of Financial Markets: A Review // Reports on Progress in Physics. 2019. Vol. 82. Iss. 12. P. 125901. doi: 10.1088/1361-6633/ab42fb. EDN: DARTOR
- Мансуров А. К. Прогнозирование валютных кризисов с помощью методов фрактального анализа // Проблемы прогнозирования. 2008. № 1 (106). С. 145–158. EDN: ICITYD
- Wang J. N., Liu H. C., Hsu Y. T. Time-of-Day Periodicities of Trading Volume and Volatility in Bitcoin
- Exchange: Does the Stock Market Matter? // Finance Research Letters. 2020. Vol. 34. P. 101243. doi: 10.1016/j.frl.2019.07.016. EDN: TJDFFX
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