基于传统模型和人工智能模型的原油期货价格预测:比较分析

IF 1.3 Q3 ECONOMICS
Sanjeev Kadam, Anshul Agrawal, Aryan Bajaj, R. Agarwal, Rameesha Kalra, J. Shah
{"title":"基于传统模型和人工智能模型的原油期货价格预测:比较分析","authors":"Sanjeev Kadam, Anshul Agrawal, Aryan Bajaj, R. Agarwal, Rameesha Kalra, J. Shah","doi":"10.1142/s179399332350014x","DOIUrl":null,"url":null,"abstract":"Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007–2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"88 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Crude Oil Future Price Using Traditional and Artificial Intelligence-Based Model: Comparative Analysis\",\"authors\":\"Sanjeev Kadam, Anshul Agrawal, Aryan Bajaj, R. Agarwal, Rameesha Kalra, J. Shah\",\"doi\":\"10.1142/s179399332350014x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007–2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price.\",\"PeriodicalId\":44073,\"journal\":{\"name\":\"Journal of International Commerce Economics and Policy\",\"volume\":\"88 1\",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of International Commerce Economics and Policy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s179399332350014x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of International Commerce Economics and Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s179399332350014x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

摘要

原油是全球经济不可缺少的能源。由于原油的非平稳性,其未来价值很难预测。本研究的重点是评估2007-2022年期间原油的爆炸性行为,包括最近一次有影响力的危机COVID-19大流行,以预测其价格。将传统计量经济学ARIMA模型与现代基于人工智能(AI)的长短期记忆网络(ALSTM)进行原油价格预测比较。使用均方根误差(RMSE)和平均误差百分比(MAPE)值来评估这些方法的准确性。结果表明,ALSTM模型对下一个工作日原油开盘价的预测效果优于传统计量经济学ARIMA预测模型。原油投资者可以有效地将其作为日内交易模型,更准确地预测下一个工作日的开盘价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Crude Oil Future Price Using Traditional and Artificial Intelligence-Based Model: Comparative Analysis
Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007–2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.50
自引率
0.00%
发文量
18
期刊介绍: Journal of International Commerce, Economics and Policy (JICEP) is a peer-reviewed journal that seeks to publish high-quality research papers that explore important dimensions of the global economic system (including trade, finance, investment and labor flows). JICEP is particularly interested in potentially influential research that is analytical or empirical but with heavy emphasis on international dimensions of economics, business and related public policy. Papers must aim to be thought-provoking and combine rigor with readability so as to be of interest to both researchers as well as policymakers. JICEP is not region-specific and especially welcomes research exploring the growing economic interdependence between countries and regions.
×
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