{"title":"汇率与油价动态:适应性分析与预测","authors":"L. Orlik, I. Khasanova","doi":"10.2991/aebmr.k.200509.042","DOIUrl":null,"url":null,"abstract":"Multivariate generalizations of the modified and adaptive time series correlation coefficients are obtained using the example of the dependence of currency pairs quotations and Brent crude oil price. The analysis of the movement of exchange rates and oil price in the R software environment. A much more detailed data analysis than the classical theory suggestion is obtained. Based on the identified trends in the dynamics of these markets, short-term forecasting was carried out using ARIMA, TBATS models and neural networks.","PeriodicalId":191445,"journal":{"name":"Proceedings of the International Conference on Economics, Management and Technologies 2020 (ICEMT 2020)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamics of Exchange Rates and Oil Price: Adaptive Analysis and Forecasting\",\"authors\":\"L. Orlik, I. Khasanova\",\"doi\":\"10.2991/aebmr.k.200509.042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multivariate generalizations of the modified and adaptive time series correlation coefficients are obtained using the example of the dependence of currency pairs quotations and Brent crude oil price. The analysis of the movement of exchange rates and oil price in the R software environment. A much more detailed data analysis than the classical theory suggestion is obtained. Based on the identified trends in the dynamics of these markets, short-term forecasting was carried out using ARIMA, TBATS models and neural networks.\",\"PeriodicalId\":191445,\"journal\":{\"name\":\"Proceedings of the International Conference on Economics, Management and Technologies 2020 (ICEMT 2020)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Economics, Management and Technologies 2020 (ICEMT 2020)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/aebmr.k.200509.042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Economics, Management and Technologies 2020 (ICEMT 2020)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/aebmr.k.200509.042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamics of Exchange Rates and Oil Price: Adaptive Analysis and Forecasting
Multivariate generalizations of the modified and adaptive time series correlation coefficients are obtained using the example of the dependence of currency pairs quotations and Brent crude oil price. The analysis of the movement of exchange rates and oil price in the R software environment. A much more detailed data analysis than the classical theory suggestion is obtained. Based on the identified trends in the dynamics of these markets, short-term forecasting was carried out using ARIMA, TBATS models and neural networks.