政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143773

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143773

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113451/144438 (79%)
Visitors : 51346349 Online Users : 703

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Scope

please add "double quotation mark" for query phrases to get precise results

please goto advance search for comprehansive author search

Adv. Search

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

Goto mobile version

政大典藏 > College of Social Science > Department of Economics > Theses > Item 140.119/143773

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/143773

Title:	運用深度強化學習建立虛擬貨幣投資組合 Establish The Portfolio of Crypto Currency by Applying Deep-Reinforcement Learning
Authors:	蘇育正 Su, Yu-Cheng
Contributors:	蔡炎龍蕭明福 Thai, YenLung Shaw, MingFu 蘇育正 Su, Yu-Cheng
Keywords:	深度學習強化學習深度強化學習虛擬貨幣投資組合 Reinforcement Learning Portfolio Crypto
Date:	2022
Issue Date:	2023-03-09 18:23:05 (UTC+8)
Abstract:	本研究運用深度強化學習建立虛擬貨幣的投資組合，研究標的主要以 2021 年 12 月 31 日市值排名前 50 大的虛擬貨幣。研究期間從 2017 年 1 月 3 日至2021 年 12 月 31 日，並主要以五個因子(Factor):開盤價(Open)、最高價(High)、最低價(Low)、收盤價(Close)、成交量(Volume)為輸入資料(Input)，並在一開始先以(1)市值、(2)平均振幅抓取 30 檔虛擬幣組建投資組合，輸入給深度強化學習模型進行訓練，最終發現相較於其他種因子建立的投資組合，平均振幅打造的投資組合表現更好，也比單一持續持有比特幣來的更合適。
Reference:	[1] Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, DavidMartinez-Rego, Fan Wu and Lingbo Li. Cryptocurrency trading: a comprehensive survey. Finanical Innovation,8(13),2022. [2] Timothy King and Dimitrios Koutmos. Herding and feedback trading in cryptocurrency markets. Annals of Operations Research,300:79-97,2021. [3] WeiSun, Alisher Tohirovich, Dedahanov, Ho YoungShin and Wei PingLi. Factors affecting institutional investors to add cryptocurrency to asset portfolios. The North American Journal of Economics and Finance,volume 58,2021. [4] Paraskevi Katsiampa, Larisa Yarovaya and DamianZięba. Highfrequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis. Journal of International Financial Markets, Institutions and Money,volume 79,2022. [5] Andrés Arévalo, Jaime Niño, G. Hernández and Javier Sandoval. High-Frequency Trading Strategy Based on Deep Neural Networks.International Conference on intelligent Computing, LNAI,volume 9773,2016. [6] Maria Čuljak,BojanTomić and SašaŽiković . Benefits of sectoral cryptocurrency portfolio optimization. Research in International Business and Finance,volume 60,2022. [7] Golnoosh Babaei,Paolo Giudici and EmanuelaRaffinetti. Explainable artificial intelligence for crypto asset allocation. Finance Research Letters,volume 47,Part B,2022. [8] Leonardo Kanashiro Felizardo,Francisco CaioLima Paiva,Catharinede Vita Graves,Elia Yathie Matsumoto,Anna Helena Reali Costa,Emilio DelMoral-Hernandez and Paolo Brandimarte. Outperforming algorithmic trading reinforcement learning systems: A supervised approach to the 30 cryptocurrency market. Expert Systems with Applications,volume 202,2022. [10] Hongfeng Xu,Lei Chai,Zhiming Luo and Shaozi Li. Stock movement prediction via gated recurrent unit network based on reinforcement learning with incorporated attention mechanisms. Neurocomputing,volume 467,Pages 214-228,2022. [11] Fengrui Liu,Yang Li,Baitong Li,Jiaxin Li and Huiyang Xie . Bitcoin transaction strategy construction based on deep reinforcement learning. Applied Soft Computing,volume113,Part B,2021. [12] Thibaut Théate and Damien Ernst . An application of deep reinforcement learning to algorithmic trading. Expert Systems with Applications,volume 173,2021. [13] Liguo Weng,Xudong Sun,Min Xia,Jia Liu and Yiqing Xu. Portfolio Trading System of Digital Currencies: A Deep Reinforcement Learning with Multidimensional Attention Gating Mechanism. Neurocomputing,volume 402,Pages 171-182,2019
Description:	碩士國立政治大學經濟學系 108258034
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0108258034
Data Type:	thesis
Appears in Collections:	[Department of Economics] Theses

Files in This Item:

File	Description	Size	Format
803401.pdf		1563Kb	Adobe PDF2	39	View/Open

All items in 政大典藏 are protected by copyright, with all rights reserved.

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

DSpace Software Copyright © 2002-2004 MIT & Hewlett-Packard / Enhanced by NTU Library IR team Copyright © - Feedback