ANALYSIS OF VOLATILITY AND AUTOCORRELATION PROPERTIES OF THE BTC-USD CRYPTOCURRENCY PAIR IN THE CONTEXT OF GLOBAL SOCIO-ECONOMIC SHOCKS
Main Article Content
Abstract
Introduction. This article investigates the nonlinear dynamics and statistical properties of the BTC-USD cryptocurrency pair between September 1, 2015, and August 1, 2025. The study is timely due to the unique nature of cryptocurrencies as a new asset class and the highly turbulent global socioeconomic environment during the analyzed period. The theoretical foundation of the work is based on econophysics concepts and the theory of complex systems, specifically the analysis of stylized facts of financial markets. Traditional linear models, which assume a Gaussian distribution, have proven inadequate for describing and forecasting the behavior of cryptocurrencies, especially during periods of high uncertainty.
Purpose. The main goal of this article is to identify and analyze nonlinear patterns in the BTC-USD dynamics from 2015 to 2025 and to interpret these patterns in the context of major global socioeconomic and geopolitical events. The research methodology includes calculating and analyzing autocorrelation functions for the price series, returns, and absolute returns, as well as using a moving window method to assess the dynamics of volatility and autocorrelation over time.
Results. The scientific novelty of this work lies in its comprehensive analysis of the evolution of key nonlinear indicators—volatility and autocorrelation—for the BTC-USD pair over a long period that includes a sequence of diverse global crises (pandemic, geopolitical, monetary). Unlike most previous research that focused on the market's reaction to single events, this study examined the cumulative effect and interaction of these shocks as they are reflected in the dynamics of the market's statistical properties. The findings underscore the need for a shift from traditional retrospective analysis to a proactive forecasting system based on an understanding of the nonlinear nature of financial markets.
Conclusion. The study confirms that the dynamics of the BTC-USD market are characterized by pronounced nonlinear properties, making classical linear models based on a Gaussian distribution inadequate for description and forecasting. The results highlight the deep integration of the cryptocurrency market into the global financial system and its high sensitivity to macroeconomic uncertainty. The research emphasizes the need to use nonlinear dynamics and econophysics to model the behavior of financial assets under conditions of high uncertainty.
Article Details
The authors published in this journal agree with following conditions:
1. The authors reserve to themselves the right to the authorship of their works and transfer the right of their first publication to the journal on the terms of Creatіve Common Attrіbutіon Lіcense which allows to freely extend to other persons the published work with an obligatory reference to the authors of the original work and its first publication in this journal.
2. The authors have the right to complete independent additional agreements concerning the not exclusive distribution of their work in the form in which it was published in this journal (for example, to place the work in the electronic storehouse of an establishment or to publish as a monograph component), under the condition of the preservation of the reference to the first publication of the work in this journal.
3. The journal’s policy allows and encourage the authors to place their manuscripts into the Internet (for example, in depositories of establishments or on personal web-sites) either before submitting of the manuscript for publication or during its editorial processing as it assists the occurrence of a productive scientific discussion and positively affects the efficiency and dynamics of citing of the published work.
AGREEMENT
ABOUT TRANSMISSION OF COPYRIGHT
I, the author of the article / We, the authors of the manuscript _______________________________________________________________________
in case of its acceptance for publication, we transfer the following rights to the founders and editorial boards of the scientific publication "BULLETIN OF THE CHERKASY BOHDAN KHMELNYTSKY NATIONAL UNIVERSITY. ECONOMIC SCIENCES. SERIES "ECONOMIC SCIENCES":
1. Publication of this article in Ukrainian (English, Russian, Polish) and distribution of its printed version.
2. Dissemination of the electronic version of the article through any electronic means (placing on the official journal web site, in electronic databases, repositories, etc.).
At the same time we reserve the right without consent of the editorial board and the founders:
1. Use the materials of the article in whole or in part for educational purposes.
2. To use the materials of the article in whole or in part for writing your own theses.
3. Use article materials to prepare abstracts, conference reports, and oral presentations.
4. Post electronic copies of the article (including the final electronic version downloaded from the journal's official website) to:
a. personal web-pecypcax of all authors (web sites, web pages, blogs, etc.);
b. web-pecypcax of the institutions where the authors work (including electronic institutional repositories);
with. non-profit, open-source web-pecypcax (such as arXiv.org).
With this agreement, we also certify that the submitted manuscript meets the following criteria:
1. Does not contain calls for violence, incitement of racial or ethnic enmity, which are disturbing, threatening, shameful, libelous, cruel, indecent, vulgar, etc.
2. Does not infringe the copyrights and intellectual property rights of others or organizations; contains all the references to the cited authors and / or publications envisaged by applicable copyright law, as well as the results and facts used in the article by other authors or organizations.
3. It has not been previously published in other publishers and has not been published in other publications.
4. Does not include materials that are not subject to publication in the open press, in accordance with applicable law.
____________________ ___________________
First name, Last name, signature of the author
"___" __________ 20__
References
Lahmiri, S., & Bekiros, S. (2020). The impact of COVID-19 on the stylized facts of major cryptocurrencies: A statistical and econometric analysis. Finance Research Letters, 36, 101693. (in Eng)
Goodell, J. W., & Goutte, S. (2021). Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. Finance Research Letters, 38, 101625. (in Eng)
Aysan, A. F., Khan, A., & Topuz, H. (2021). The impact of the COVID-19 pandemic on the interconnectedness of cryptocurrency and financial markets. Research in International Business and Finance, 58, 101489. (in Eng)
Umar, Z., Bossman, A., & Choi, S. (2023). The Russia–Ukraine war and the behavior of cryptocurrency markets: New evidence. Finance Research Letters, 54, 103736. (in Eng)
Fang, Y., Bouri, E., & Saeed, T. (2023). Geopolitical risk and the cryptocurrency market: The case of the Russia–Ukraine conflict. Energy Economics, 119, 106553. (in Eng)
Al-Yahyaee, K. H., Kutan, A. M., & Rehman, M. U. (2023). The role of the Federal Reserve’s policy in the cryptocurrency market. Journal of International Financial Markets, Institutions and Money, 83, 101736. (in Eng)
Dubrov, D. V., & Kozmenko, S. V. (2022). Perspektyvy ta ryzyky intehratsii kryptovaliut u finansovu systemu Ukrainy v umovakh voiennoho stanu [Prospects and risks of cryptocurrency integration into the financial system of Ukraine under martial law]. Finansy Ukrainy, (8), 24–41. (in Ukr)
Diakonova, I. V., & Kravchuk, O. S. (2023). Analiz ryzykiv investuvannia v tsyfrovi aktyvy na rynku Ukrainy [Risk analysis of investing in digital assets in the Ukrainian market]. Ekonomika ta derzhava, (2), 55–61. (in Ukr)
Bielinskyi, A., Soloviev, V., Solovieva, V., Matviychuk, A., & Semerikov, S. (2023). The analysis of multifractal cross-correlation connectedness between Bitcoin and the stock market. In E. Faure, O. Danchenko, M. Bondarenko, Y. Tryus, C. Bazilo, & G. Zaspa (Eds.), Information technology for education, science, and technics (pp. 323–345). Springer Nature Switzerland. (in Eng)
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2021). The econometrics of financial markets. Princeton University Press. (in Eng)
Soloviev, V. N., & Belinskyi, A. (2018). Methods of nonlinear dynamics and the construction of cryptocurrency crisis phenomena precursors. In V. Ermolayev et al. (Eds.), Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications: Integration, Harmonization and Knowledge Transfer (Vol. 2104, pp. 116–127). CEUR-WS.org. (in Eng)
Soloviov, V. M., Serdiuk, O. A., & Danylchuk, H. B. (2016). Modeliuvannia skladnykh system [Modeling of complex systems]. Cherkasy: Vydavets O. Yu. Vovchok. (in Ukr)
Kibalyk, L., Kibalyk, V., Danylchuk, H., & Sereda, D. (2024). Modeliuvannia vplyvu rosiisko-ukrainskoi viiny na valiutnyi rynok [Modeling the impact of the Russia–Ukraine war on the foreign exchange market]. Visnyk Cherkaskoho natsionalnoho universytetu imeni Bohdana Khmelnytskoho. Ekonomichni nauky, 28(3–4), 17–27. (in Ukr)
Taylor, S. J. (2008). Modelling financial time series. John Wiley & Sons. (in Eng)
Mandelbrot, B. (1963). The variation of certain speculative prices. The Journal of Business, 36(4), 394–419. (in Eng)
Conlon, T., Corbet, S., & McGee, R. J. (2020). Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic. Research in International Business and Finance, 54, 101248. (in Eng)
Baur, D. G., & Dimpfl, T. (2021). The volatility of Bitcoin and its role as a medium of exchange and a store of value. Empirical Economics, 61(5), 2663–2683. (in Eng)
Phillip, A., Chan, J. S.-K., & Peiris, S. (2018). A new look at stylized facts of cryptocurrencies. Economics Letters, 170, 25–28. (in Eng)
Farmer, J. D. (2002). The economy as a complex adaptive system. Daedalus, 131(4), 98–108. (in Eng)
Yahoo Finance. (2025). Stock market live, quotes, business & finance news. Retrieved June 1, 2025, from https://finance.yahoo.com/ (in Eng)
Derbentsev, V. D., Serdiuk, O. A., Soloviov, V. M., & Sharapov, O. D. (2010). Synerhetychni ta ekonofizychni metody doslidzhennia dynamichnykh ta strukturnykh kharakterystyk ekonomichnykh system [Synergetic and econophysical methods for studying dynamic and structural characteristics of economic systems]. Cherkasy: Brama-Ukraina. (in Ukr)