找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: A Machine Learning based Pairs Trading Investment Strategy; Sim?o Moraes‘Sarmento,Nuno Horta Book 2021 The Editor(s) (if applicable) and T

[復(fù)制鏈接]
查看: 30536|回復(fù): 40
樓主
發(fā)表于 2025-3-21 19:03:52 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱A Machine Learning based Pairs Trading Investment Strategy
影響因子2023Sim?o Moraes‘Sarmento,Nuno Horta
視頻videohttp://file.papertrans.cn/142/141370/141370.mp4
發(fā)行地址Discusses unsupervised learning applied in pairs trading.Presents exclusive trading models.Simulates the performance of a pairs trading strategy using commodity-linked ETFs with 5-min frequency price
學(xué)科分類(lèi)SpringerBriefs in Applied Sciences and Technology
圖書(shū)封面Titlebook: A Machine Learning based Pairs Trading Investment Strategy;  Sim?o Moraes‘Sarmento,Nuno Horta Book 2021 The Editor(s) (if applicable) and T
影響因子. .This book investigates the application of promising machine learning techniques to?address?two problems: (i) how to find profitable pairs while constraining the search space and (ii) how to avoid long decline periods due to prolonged divergent pairs. It also proposes the integration of an unsupervised learning algorithm, OPTICS, to handle problem (i), and demonstrates that the suggested technique can outperform the common pairs search methods, achieving an average portfolio Sharpe ratio of 3.79, in comparison to 3.58 and 2.59 obtained using standard approaches. For problem (ii), the authors introduce a forecasting-based trading model capable of reducing the periods of portfolio decline by 75%. However, this comes at the expense of decreasing overall profitability. The authors also test the proposed strategy using an ARMA model, an LSTM and an LSTM encoder-decoder..
Pindex Book 2021
The information of publication is updating

書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy影響因子(影響力)




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy影響因子(影響力)學(xué)科排名




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy被引頻次




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy被引頻次學(xué)科排名




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy年度引用




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy年度引用學(xué)科排名




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy讀者反饋




書(shū)目名稱A Machine Learning based Pairs Trading Investment Strategy讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 22:27:25 | 只看該作者
Book 2021 introduce a forecasting-based trading model capable of reducing the periods of portfolio decline by 75%. However, this comes at the expense of decreasing overall profitability. The authors also test the proposed strategy using an ARMA model, an LSTM and an LSTM encoder-decoder..
板凳
發(fā)表于 2025-3-22 03:32:19 | 只看該作者
Olivia Nocentini,Jaeseok Kim,Filippo Cavalloe criteria adopted to select potentially profitable pairs from the clusters previously formed are outlined. In the end, a summary diagram connecting the different concepts introduced throughout the chapter is presented, for consolidation purposes.
地板
發(fā)表于 2025-3-22 06:50:10 | 只看該作者
Jana Clement,Joern Ploennigs,Klaus Kabitzschained in detail. To complement, other possible alternatives are introduced as well. At last, an overview of the current state-of-the-art concerning the application of Machine Learning in the field of Pairs Trading is provided.
5#
發(fā)表于 2025-3-22 11:30:17 | 只看該作者
Olivia Nocentini,Jaeseok Kim,Filippo Cavalloremaining part of the chapter investigates which forecasting algorithm may be more suitable to integrate the proposed trading model, exploring the ARMA model, along with two Deep Learning based models, an LSTM and an LSTM Encoder-Decoder.
6#
發(fā)表于 2025-3-22 16:29:34 | 只看該作者
7#
發(fā)表于 2025-3-22 21:05:09 | 只看該作者
Lecture Notes in Electrical Engineeringncerning the new proposed forecasting-based trading model (in Chap.?4) are analyzed next. Some insightful conclusions are inferred regarding the suitability of a forecasting based trading model in this setup.
8#
發(fā)表于 2025-3-22 22:05:17 | 只看該作者
2191-530X tegy using commodity-linked ETFs with 5-min frequency price . .This book investigates the application of promising machine learning techniques to?address?two problems: (i) how to find profitable pairs while constraining the search space and (ii) how to avoid long decline periods due to prolonged div
9#
發(fā)表于 2025-3-23 03:06:20 | 只看該作者
10#
發(fā)表于 2025-3-23 09:22:24 | 只看該作者
A Machine Learning based Pairs Trading Investment Strategy978-3-030-47251-1Series ISSN 2191-530X Series E-ISSN 2191-5318
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-8 14:53
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
巴东县| 图们市| 镇康县| 子洲县| 西林县| 五原县| 八宿县| 乌兰察布市| 项城市| 普洱| 苏州市| 伊川县| 江油市| 临潭县| 沧源| 大宁县| 天台县| 扬州市| 巍山| 庆云县| 文成县| 探索| 旅游| 永胜县| 嘉鱼县| 绥芬河市| 周宁县| 萝北县| 定日县| 台南市| 汝阳县| 鲁甸县| 永安市| 华阴市| 堆龙德庆县| 渝中区| 龙游县| 宽城| 南城县| 卓尼县| 门源|