基于技术指标的交易算法模型

Muhammad Khawar Bashir
{"title":"基于技术指标的交易算法模型","authors":"Muhammad Khawar Bashir","doi":"10.54692/lgurjcsit.2021.0501176","DOIUrl":null,"url":null,"abstract":"Today the rapid proliferation of the internet provides an environment where efficient e-commerce solutions can be developed. The electronic market is gaining more attention in the global economy, it gives buyers and sellers more liberty to trade cost-effectively and allows access to an adequate amount of data for analysis. New trading agents have been developed for the best utilization of such data. These agents design strategies using financial analysis techniques such as technical indicators. Two very well-known technical indicators used to develop strategies are Convergence-Divergence (MACD) and Stochastic Oscillator (SO). This paper aims to devise a trading algorithm that combines MACD and SO in a single strategy and check the reliability of the combined signals it generates. JTAP simulation system has been used to test the proposed strategy. In this paper, we evaluated the performance of our proposed strategy when implemented on shares of Karachi Stock Exchange, Pakistan which proves improvement of strategy.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trading Algorithm Model Based on Technical Indicators\",\"authors\":\"Muhammad Khawar Bashir\",\"doi\":\"10.54692/lgurjcsit.2021.0501176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today the rapid proliferation of the internet provides an environment where efficient e-commerce solutions can be developed. The electronic market is gaining more attention in the global economy, it gives buyers and sellers more liberty to trade cost-effectively and allows access to an adequate amount of data for analysis. New trading agents have been developed for the best utilization of such data. These agents design strategies using financial analysis techniques such as technical indicators. Two very well-known technical indicators used to develop strategies are Convergence-Divergence (MACD) and Stochastic Oscillator (SO). This paper aims to devise a trading algorithm that combines MACD and SO in a single strategy and check the reliability of the combined signals it generates. JTAP simulation system has been used to test the proposed strategy. In this paper, we evaluated the performance of our proposed strategy when implemented on shares of Karachi Stock Exchange, Pakistan which proves improvement of strategy.\",\"PeriodicalId\":197260,\"journal\":{\"name\":\"Lahore Garrison University Research Journal of Computer Science and Information Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Lahore Garrison University Research Journal of Computer Science and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54692/lgurjcsit.2021.0501176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lahore Garrison University Research Journal of Computer Science and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54692/lgurjcsit.2021.0501176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

今天,互联网的迅速普及为开发高效的电子商务解决方案提供了环境。电子市场在全球经济中受到越来越多的关注,它使买卖双方更自由地进行经济有效的交易,并允许获得足够数量的数据进行分析。为了最好地利用这些数据,开发了新的交易代理。这些代理人使用技术指标等财务分析技术来设计策略。用于制定策略的两个非常著名的技术指标是收敛-发散(MACD)和随机振荡器(SO)。本文旨在设计一种在单一策略中结合MACD和SO的交易算法,并检查其生成的组合信号的可靠性。采用JTAP仿真系统对所提出的策略进行了验证。本文以巴基斯坦卡拉奇证券交易所股票为例,对本文提出的策略的实施效果进行了评价,证明了策略的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Trading Algorithm Model Based on Technical Indicators
Today the rapid proliferation of the internet provides an environment where efficient e-commerce solutions can be developed. The electronic market is gaining more attention in the global economy, it gives buyers and sellers more liberty to trade cost-effectively and allows access to an adequate amount of data for analysis. New trading agents have been developed for the best utilization of such data. These agents design strategies using financial analysis techniques such as technical indicators. Two very well-known technical indicators used to develop strategies are Convergence-Divergence (MACD) and Stochastic Oscillator (SO). This paper aims to devise a trading algorithm that combines MACD and SO in a single strategy and check the reliability of the combined signals it generates. JTAP simulation system has been used to test the proposed strategy. In this paper, we evaluated the performance of our proposed strategy when implemented on shares of Karachi Stock Exchange, Pakistan which proves improvement of strategy.
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
自引率
0.00%
发文量
0
期刊最新文献
Classification of Microscopic Malaria Parasitized Images Using Deep Learning Feature Fusion A systematic review A Conversational interface agent for the export business acceleration Identification of Finger Vein Images with Deep Neural Networks Cloud Computing Services and Security Challenges: A Review Classifying Tweets with Keras and TensorFlow using RNN (Bi-LSTM)
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1