Quantitative Trading Using Artificial Intelligence on Trend-Following Indicators: An Example in 2020

IF 0.6 Q4 BUSINESS, FINANCE
Raúl Gómez-Martínez, Carmen Orden-Cruz, maRía lUISa meDRanO-GaRCía
{"title":"Quantitative Trading Using Artificial Intelligence on Trend-Following Indicators: An Example in 2020","authors":"Raúl Gómez-Martínez, Carmen Orden-Cruz, maRía lUISa meDRanO-GaRCía","doi":"10.3905/joi.2022.1.235","DOIUrl":null,"url":null,"abstract":"Currently, algorithmic trading systems are one of the biggest challenges for machine learning (ML) and artificial intelligence (AI). In this article, an AI model is proposed using predictor variables based on trend-following momentum indicators. Using a data sample of highly traded futures contracts and their technical indicators, the results show a predictive capacity greater than 50% of the market trend of the next session. However, ML did not allow a profitable algorithmic trading system during the testing process.","PeriodicalId":45504,"journal":{"name":"Journal of Investing","volume":"32 1","pages":"35 - 49"},"PeriodicalIF":0.6000,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Investing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/joi.2022.1.235","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

Abstract

Currently, algorithmic trading systems are one of the biggest challenges for machine learning (ML) and artificial intelligence (AI). In this article, an AI model is proposed using predictor variables based on trend-following momentum indicators. Using a data sample of highly traded futures contracts and their technical indicators, the results show a predictive capacity greater than 50% of the market trend of the next session. However, ML did not allow a profitable algorithmic trading system during the testing process.
在趋势跟踪指标上使用人工智能的量化交易:以2020年为例
目前,算法交易系统是机器学习(ML)和人工智能(AI)面临的最大挑战之一。在本文中,使用基于趋势跟踪动量指标的预测变量提出了一个人工智能模型。使用交易量大的期货合约及其技术指标的数据样本,结果显示预测能力大于下一交易日市场趋势的50%。然而,ML在测试过程中不允许盈利的算法交易系统。
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
Journal of Investing
Journal of Investing BUSINESS, FINANCE-
CiteScore
1.10
自引率
16.70%
发文量
42
×
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