MODELING THE IMPACT OF THE RUSSIAN-UKRAINIAN WAR ON THE FOREIGN EXCHANGE MARKET
Main Article Content
Abstract
The article is dedicated to modeling the foreign exchange market to assess the impact of the Russian-Ukrainian war. For this purpose, methods such as the calculation of the Hurst exponent, the local Hurst exponent, and recurrence analysis were utilized. The study examined currency pairs including BTC/USD, ETH/USD, EUR/USD, GBP/USD, CNY/USD, USD/RUB, and USD/UAH. Based on the modeling results, it was concluded that certain changes in the dynamics of these currency pairs were observed from 2022 to November 2024. The calculated Hurst exponent allowed for an assessment of the persistence of the currency pairs. The local Hurst exponent provided further insights into the states of the foreign exchange market at different points in the study period. Recurrence analysis was conducted, which helped refine conclusions regarding the impact of crises on the foreign exchange market.
The obtained models demonstrated that all analyzed currency pairs experienced negative effects due to Russia's full-scale invasion of Ukraine. The authors argue that the response of the EUR/USD currency pair can be explained by the European Union's dependence on Russian energy resources. Additionally, the introduction of economic and political sanctions against Russia has had a significant impact on the foreign exchange market, as these sanctions restrict access to international financial markets, reduce foreign investment and trade volumes, thereby decreasing liquidity and increasing the volatility of the national currency. Moreover, sanctions create significant uncertainty among investors, disrupt supply chains, and force the country to seek alternative financial and economic partnerships, ultimately affecting the stability of the foreign exchange market and the overall economic situation.
Evidently, the war in Ukraine has also influenced the USD/UAH and USD/RUB currency pairs, as the hryvnia and ruble are the national currencies of Ukraine and Russia, respectively. An interesting result was observed in the modeling of the CNY/USD currency pair. The war in Ukraine was found to have an impact on this pair as well, given that China, while maintaining ties with Russia, seeks to strengthen its global position, whereas the United States supports Ukraine, further influencing the foreign exchange market. This occurs in the broader context of U.S.-China rivalry.
For cryptocurrency pairs, the models demonstrated a relatively low dependence on events in Ukraine. The findings of the study suggest that the use of fractal and recurrence analysis is advisable, as these methods offer new opportunities for a deeper understanding of the foreign exchange market and the development of adaptive strategies for managing economic risks, which is particularly relevant in the context of global instability.
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
Honak, I.M. (2022). Mozhlyvosti investuvannya u kryptovalyuty v umovakh aktyvnoyi fazy pandemiyi COVID-19 u 2020–2021 rr. ta konventsijnoyi rosijsko-ukrayinskoyi vijny 2022 r. [Investment opportunities in cryptocurrencies during the active phase of the COVID-19 pandemic in 2020–2021 and the conventional Russian-Ukrainian war in 2022]. Naukovi zapysky Natsionalʹnoho universytetu "Ostrozʹka akademiya". Seriya "Ekonomika", 25(53), 67–77.
Burtnyak, I.V., Suduk, N.V., & Kashevskyi, R.M. (2024). R/S-analiz valyutnoho rynku [R/S analysis of the currency market]. Aktualʹni problemy rozvytku ekonomiky rehionu, 2(20), 245–251. https://doi.org/10.15330/apred.2.20.245-251
Martyanov, D., Viklyuk, Y., & Fleichuk, M. (2023). Modelyuvannya dynamiky rynku kryptovalyut z vykorystannyam instrumentiv mashynnoho navchannya [Modeling the dynamics of the cryptocurrency market using machine learning tools]. System Research and Information Technologies, (4), 54–68.
Derbentsev, V.D., Bezkorovainyi, V.S., & Ovcharenko, A.A. (2020). Modelyuvannya korotkostrokovoyi dynamiky valyutnykh kursiv z vykorystannyam hlybokykh nejronnykh merezh [Modeling the short-term dynamics of exchange rates using deep neural networks]. Naukovyi visnyk Odesʹkoho natsionalʹnoho ekonomichnoho universytetu, (3-4), 153–163.
Hossain, A.T., Masum, A.-A., & Saadi, S. (2024). The impact of geopolitical risks on foreign exchange markets: Evidence from the Russia-Ukraine war. Finance Research Letters, 59, 104750. URL : https://doi.org/10.1016/j.frl.2023.104750 (Accessed: 15.12.2024).
Aliu, F., Apanovych, Y., Bajra, U., & Nuhiu, A. (2024). Assessing the impact of the Russia-Ukraine war and COVID-19 on selected European currencies and key commodities. Journal of Business Economics and Management, 25(5), 1097–1119. https://doi.org/10.3846/jbem.2024.22518
Danylchuk, H., Kibalnyk, L., Kovtun, O., Kiv, A., Pursky, O., & Berezhna, G. (2020). Modelling of cryptocurrency market using fractal and entropy analysis in COVID-19. CEUR Workshop Proceedings. URL : https://ceur-ws.org/Vol-2713/paper40.pdf (Accessed: 15.12.2024).
Danylchuk, H.B., Kibalnyk, L.O., Kovtun, O.A., Pursky, O.I., Kyryliuk, Y.M., & Kravchenko, O.O. (2023). The impact of the war in Ukraine on globalization processes and world financial markets: A wavelet entropy analysis. CEUR Workshop Proceedings. URL : https://ceur-ws.org/Vol-3465/paper20.pdf (Accessed: 15.12.2024).
Statystyka indeksiv svitovoho valyutnoho rynku [Statistics of world currency market indices]. (n.d.). URL : http://finance.yahoo.com (Accessed: 15.12.2024).
Hurst, H.E. (1951). Long-term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers, 116(1), 770–799.
Weron, R. (2002). Estimating long-range dependence: Finite sample properties and confidence intervals. Physica A: Statistical Mechanics and its Applications, 312(1–2), 285–299.
Eckmann, J.-P., Kamphorst, S.O., & Ruelle, D. (1987). Recurrence plots of dynamical systems. Europhysics Letters.
Marwan, N., et al. (2007). A recurrence plot-based method for characterizing time series. Physics Reports.