FORECASTING THE EXCHANGE RATE OF THE UKRAINIAN HRYVNIA USING MACHINE LEARNING METHODS

V. Pryimak, Bohdan Bartkiv, O. Holubnyk
{"title":"FORECASTING THE EXCHANGE RATE OF THE UKRAINIAN HRYVNIA USING MACHINE LEARNING METHODS","authors":"V. Pryimak, Bohdan Bartkiv, O. Holubnyk","doi":"10.31891/csit-2023-1-10","DOIUrl":null,"url":null,"abstract":"This article describes the concept of currency exchange rate and the typology of various factors that influence it. A multifactor regression model was constructed to investigate the influence of factors on the exchange rate of the Ukrainian hryvnia and to forecast the dynamics of this rate based on the studied factors using Data Science technologies. \nThe purpose of this work is to study the peculiarities of the formation of the exchange rate of the Ukrainian hryvnia, the characteristics of the influence of various external factors on this rate, and the creation of an effective forecasting model of the Ukrainian national currency rate, based on a certain number of fundamental financial and economic factors that influence this rate. \nMacroeconomic indicators that theoretically have an impact on the dynamics of the currency exchange rate were chosen to build the model. Data on the exchange rate of the Ukrainian hryvnia to the US dollar and economic indicators for selected factors were collected from 2010 to September 2022. During the implementation of the task, the collected data was processed, brought into a uniform form, and normalized. Machine learning methods were used for regression modeling, specifically the XGBoost gradient boosting method. \nAs a result, a retrospective forecast of the Ukrainian hryvnia exchange rate was obtained, based on factor variables, and an estimate of the impact of each selected feature on the currency exchange rate was calculated. The scientific novelty of this work lies in the application of modern machine learning methods and technologies for the analysis, modeling, and forecasting of the exchange rate of the Ukrainian national currency. \nThe practical significance of this article lies in the possibility of using the proposed approaches to forecasting the exchange rate of the Ukrainian hryvnia with the use of machine learning methods by all interested parties, including financial institutions of Ukraine, to achieve stability of the national currency, which in turn will affect the development of the national economy as a whole and the welfare of the population of the country.","PeriodicalId":353631,"journal":{"name":"Computer systems and information technologies","volume":"693 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer systems and information technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31891/csit-2023-1-10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This article describes the concept of currency exchange rate and the typology of various factors that influence it. A multifactor regression model was constructed to investigate the influence of factors on the exchange rate of the Ukrainian hryvnia and to forecast the dynamics of this rate based on the studied factors using Data Science technologies. The purpose of this work is to study the peculiarities of the formation of the exchange rate of the Ukrainian hryvnia, the characteristics of the influence of various external factors on this rate, and the creation of an effective forecasting model of the Ukrainian national currency rate, based on a certain number of fundamental financial and economic factors that influence this rate. Macroeconomic indicators that theoretically have an impact on the dynamics of the currency exchange rate were chosen to build the model. Data on the exchange rate of the Ukrainian hryvnia to the US dollar and economic indicators for selected factors were collected from 2010 to September 2022. During the implementation of the task, the collected data was processed, brought into a uniform form, and normalized. Machine learning methods were used for regression modeling, specifically the XGBoost gradient boosting method. As a result, a retrospective forecast of the Ukrainian hryvnia exchange rate was obtained, based on factor variables, and an estimate of the impact of each selected feature on the currency exchange rate was calculated. The scientific novelty of this work lies in the application of modern machine learning methods and technologies for the analysis, modeling, and forecasting of the exchange rate of the Ukrainian national currency. The practical significance of this article lies in the possibility of using the proposed approaches to forecasting the exchange rate of the Ukrainian hryvnia with the use of machine learning methods by all interested parties, including financial institutions of Ukraine, to achieve stability of the national currency, which in turn will affect the development of the national economy as a whole and the welfare of the population of the country.
使用机器学习方法预测乌克兰格里夫纳的汇率
本文介绍了货币汇率的概念以及影响货币汇率的各种因素的类型。建立多因素回归模型,探讨各因素对乌克兰格里夫纳汇率的影响,并利用数据科学技术,基于所研究的因素预测乌克兰格里夫纳汇率的动态。这项工作的目的是研究乌克兰格里夫纳汇率形成的特点,各种外部因素对该汇率的影响特点,并根据影响该汇率的若干基本金融和经济因素,建立乌克兰本国货币汇率的有效预测模型。选择理论上对货币汇率动态有影响的宏观经济指标来构建模型。从2010年到2022年9月,乌克兰格里夫纳对美元的汇率和选定因素的经济指标数据被收集。在任务执行过程中,对收集到的数据进行处理,形成统一的形式,并进行规范化。机器学习方法用于回归建模,特别是XGBoost梯度增强方法。结果,基于因素变量,获得了乌克兰格里夫纳汇率的回顾性预测,并计算了每个选定特征对货币汇率的影响的估计。这项工作的科学新颖性在于应用现代机器学习方法和技术来分析、建模和预测乌克兰国家货币的汇率。本文的实际意义在于,包括乌克兰金融机构在内的所有利益相关方都有可能使用所提出的方法来预测乌克兰格里夫纳的汇率,并使用机器学习方法来实现本国货币的稳定,这反过来又会影响整个国民经济的发展和该国人口的福利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信