Machine learning model to project the impact of Ukraine crisis

2022/03/03 by Javad T. Firouzjaee, Firouzjaee, Javad T., Pouriya Khaliliyan +1
Economics, Econometrics and Finance · Environmental Science · #Artificial Intelligence (cs.AI) #Environmental and Biological Research in Conflict Zones #FOS: Computer and information sciences #FOS: Economics and business #Market Dynamics and Volatility #Statistical Finance (q-fin.ST)

paper · pdf · doi:10.48550/arxiv.2203.01738

openalex publication_date 2022/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Russia's attack on Ukraine on Thursday 24 February 2022 hitched financial markets and the increased geopolitical crisis. In this paper, we select some main economic indexes, such as Gold, Oil (WTI), NDAQ, and known currency which are involved in this crisis and try to find the quantitative effect of this war on them. To quantify the war effect, we use the correlation feature and the relationships between these economic indices, create datasets, and compare the results of forecasts with real data. To study war effects, we use Machine Learning Linear Regression. We carry on empirical experiments and perform on these economic indices datasets to evaluate and predict this war tolls and its effects on main economics indexes.

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