Modelling the Intervention of UAH/USD Exchange Rates as a Result of 2022 Russian Invasion of Ukraine

Document Type : Research Note

Authors

1 Department of Mathematics, Rivers State University, Port Harcourt, Nigeria

2 Department of Statistics, Federal University of Technology, Owerri, Nigeria

3 Department of Statistics, University of Uyo, Uyo, Nigeria

Abstract

Russia and Ukraine are in a war, with the former invading the latter. This puts the latter under great stress, many have died in the process and many more have been displaced and many more have fled from Ukraine. This has resulted in intervention in many time series related to Ukraine. For example, the time series of the daily exchange rates of Ukrainian Hryvnia (UAH) and United States Dollars (USD) experienced an intervention on the first day of Russian incursion. By Box and Tiao (1975) approach, a realization of the time series from 1 January 2022 to 15 March 2022 is analyzed. The intervention model arrived at is found adequate. It can be the basis for management and planning.

Keywords

Main Subjects


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©2022 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

Box, G. E. P. and Jenkins, G. M. (1976) Time Series Analysis, Forecasting and Control. Holden-Day, San Francisco.
Box, G. E. P. and Tiao, G. C. (1975). Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical Association, Volume 70, No. 349, pp. 70-79.
Etuk, E. H. and Eleki, A. G. (2016). Intervention Analysis of Daily Yuan-Naira Exchange Rates. CARD International Journal of Science and Advanced Innovation Research, Volume 1, Number 1. http://www.casirmediapublishing.com
Giordano, G., Blanchini, F., Bruno, R., Colaneri, P., Fillipo, A. D., Matteo, A. D. and Colaneri, M. (2020). Modelling the covid-19 epidemic nd implementation in Italy. Nature Medicine 26, 855-860.
Helfenstein, U. (1991). The use of transfer function models, intervention analysis and related time series methods in epidemiology. Int J Epidemiology, 1991 Sep., 20(3): 808-815. Doi:10.1093/ije/20.3.808. PMID: 1955267.
Ma, Z., Kuller, L. H., Fisher, M. A. and Ostroff, S. M. (2013). Use of interrupted time series method to evaluate the impact of cigarette excise tax increases in Pennsylvania, 2000-2009. Preventing Chronic Disease, 2013;10:120268. DOI: http://dx.doi.org/10.5888/pcd10.120268  
Mohammed, H., Abdul-Aziz, A. R. and Saeed, B. I. I. (2016). Modeling the Ghanaian inflation rates using interrupted Time Series Analysis Approach.  Mathematical Theory and Modelling, Volume 6, No. 2. https://www.iiste.org
Oreko, B. U., Nwobi-Okoye, C. C., Okyl, S. and Igboanugo, A. C. (2017). Modeling the impact of intervention measures on total accident cases in Nigeria using Box-Jenkins methodology: A case study of federal road safety commission. Cogent Engineering, Volume 4, Issue 1. https://doi.org/10.1080/23311916.2017.1345043   
Ray, M., Ramasubramanian, V., Kumar, A. and Rai, A. (2014). Application of Time Series Intervention Modelling and Forecasting Cotton Yield. Statistics and Applications, Volume 12, Nos. 1&2, pp. 61-70.
Yaacob, W.F.W., Husin, W.Z.W., Aziz, N. A., and Nordin, N. I. (2011). An Intervention Model of Road Accidents: The Case of OPS Sikap Intervention. Journal of Applied Sciences, 11: 1105-1112.