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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 曹承礎(Seng-Cho Chou) | |
| dc.contributor.author | Che-Wei Kuo | en |
| dc.contributor.author | 郭哲偉 | zh_TW |
| dc.date.accessioned | 2021-06-17T07:25:24Z | - |
| dc.date.available | 2029-06-27 | |
| dc.date.copyright | 2019-07-10 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-06-27 | |
| dc.identifier.citation | [1] Zhu, Y., & Zhou, G. (2009). Technical analysis: An asset allocation perspective on the use of moving averages. Journal of Financial Economics, 92(3), 519-544.
[2] Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Systems with Applications, 42(1), 259-268. [3] 洪敏洋（2013）。價量動能因子選股模型：以台灣上市股票為例。國立臺灣科技大學財務金融研究所碩士論文，台北市。 取自https://hdl.handle.net/11296/73sf5c [4] Lakonishok, J., Shleifer, A., & Vishny, R. W. (1992). The impact of institutional trading on stock prices. Journal of financial economics, 32(1), 23-43. [5] 何弘毅（2016）。三大法人從眾行為之研究—以臺股指數期貨與選擇權市場為例。國立臺灣科技大學財務金融研究所碩士論文，台北市。 取自https://hdl.handle.net/11296/kum69k [6] 陳彥豪（2002）。外資與投信法人持股比率變化對股價報酬率影響之研究-以上市電子股為例。國立中山大學財務管理學系研究所碩士論文，高雄市。 取自https://hdl.handle.net/11296/39v52k [7] 胡家麒（1998）。外資、投信法人投資機構買賣超與證券股股價報酬率之互動關係之實證研究。國立中興大學企業管理學系碩士論文，台中市。 取自https://hdl.handle.net/11296/4dgb5f [8] 陳志萍（2009）。應用關連式規則分析於主力券商分行之操作策略。國立清華大學高階經營管理碩士在職專班碩士論文，新竹市。 取自https://hdl.handle.net/11296/4v4a2m [9] 陳明汰（2014）。台灣興櫃股票市場交易集中度與異常報酬率之關係。國立臺灣大學財務金融學研究所碩士論文，台北市。 取自https://hdl.handle.net/11296/dc8957 [10] 林昌燿（2017）。應用吉尼係數測量股票籌碼集中度：建構台灣證券市場交易策略。國立臺灣科技大學財務金融研究所碩士論文，台北市。 取自https://hdl.handle.net/11296/92rv4t [11] Chen, Tianqi, and Carlos Guestrin. 'Xgboost: A scalable tree boosting system.' Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining. ACM, 2016. [12] Tapscott, A., & Tapscott, D. (2017). How blockchain is changing finance. Harvard Business Review, 1. [13] 賴紀誠, 林問一, & 劉亞秋. (2011). 台灣股市券商分析師盈餘預測之利益衝突. 臺大管理論叢, 22(1), 357-389. [14] Invictus Capital (2018) Invictus Hyperion Fund ICO Whitepaper [https://cdn.invictuscapital.com/whitepapers/hyperion.pdf] [15] CommBank (2011, August 1). Commonwealth Bank’s Investorville... Build a property portfolio without spending a cent. https://www.commbank.com.au/about-us/news/media-releases/2011/010811-Investorville.html [16] Kapitall. https://kapitall.com/landing [17] Bincentive Whitepaper (2018, September). https://wp.bincentive.com/wp-content/uploads/2018/09/Bincentive_wp_TC.pdf [18] Numerai Whitepaper (2017, February 20). Numeraire: A Cryptographic Token for Coordinating Machine Intelligence and Preventing Overfitting. https://numer.ai/static/media/whitepaper.29bf5a91.pdf | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73265 | - |
| dc.description.abstract | 本研究旨於實現新型區塊鏈投資平台的概念性驗證 (Proof-of-Concept)，並結合智能投資及遊戲化概念。雖然目前證券或軟體應用市場上存在著相關的產品和研究，但很少有研究致力於這三個概念的結合與應用。本研究由兩部分實驗組成：(1) 透過機器學習方法實作一套量化交易策略，找出一籃未來最具漲勢的股票並做多進行買入，持有N天後賣出，此階段的實驗結果會作為下一部分區塊鏈應用中的一項重要元素；(2) 建構基於區塊鏈的遊戲平台原型，並結合上一部分的量化投資策略，實現新穎的智能投資服務。在第一部分中，預測模型的表現穩健，相較於大盤指數皆能在不同的市場狀況之下獲得超額報酬；在第二部分的實驗中提出並實現了區塊鏈平台原型，透過遊戲化的概念包裝能為參與者提供更多的誘因參與此區塊鏈生態系統，而建構基於區塊鏈與智能合約的去中心化基礎之上，安全性、公平性與可靠性也能被充分實現。 | zh_TW |
| dc.description.abstract | This study is a proof of concept (PoC) of constructing an investment gaming platform based on Blockchain, quantitative trading and gamification. Although there exist some related products and researches in the current marketplace. But few studies work on the combination of these three concepts. This study consists of two parts: (1) developing a quantitative trading strategy through machine learning approach to find out the most profitable stocks in the future and the results will be used as a feature of the proposed gaming platform; (2) building a blockchain-based gaming application incorporating with the concept of smart trading. In the first part, the performance of the predictive model is quite well and the model can beat the market under different market situations. In the second part, a prototype is proposed and implemented. Through gamification, it is capable of providing more incentives for people to participate. Safety and reliability can also be ensured by the nature of Blockchain and smart contracts. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T07:25:24Z (GMT). No. of bitstreams: 1 ntu-108-R05725010-1.pdf: 1929103 bytes, checksum: a295dbe3731ad5c857e8826fde06c0c2 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi LIST OF TABLES viii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Objectives 1 1.3 Outline 3 Chapter 2 Related Works 4 2.1 Technical Analysis 4 2.2 Chip Analysis 5 2.3 XGBoost 8 2.4 Gamification in Finance 8 2.4.1 Investorville 9 2.4.2 Kapitall 9 2.5 Related Blockchain Applications 9 2.5.1 Invictus Capital 10 2.5.2 Bincentive 11 2.5.3 Numerai 12 Chapter 3 Methodology 13 3.1 Establish Trading Strategy through Machine Learning Technique 13 3.1.1 Problem Definition 13 3.1.2 Data 13 3.1.3 Data Preprocessing & Feature Engineering 14 3.1.4 Model 25 3.1.5 Experiment Design 26 3.2 Construct a Blockchain-based Investment Platform with Gamification 27 3.2.1 Problems 27 3.2.2 Proposed Solution 29 Chapter 4 Experiment Result 31 4.1 Backtesting and Model Performance Evaluation 31 4.2 Architecture and Implementation of the Blockchain-based Investing Game 38 Chapter 5 Conclusion and Future Works 41 REFERENCE 43 | |
| dc.language.iso | en | |
| dc.subject | 概念驗證 | zh_TW |
| dc.subject | 遊戲化 | zh_TW |
| dc.subject | 智能合約 | zh_TW |
| dc.subject | 去中心化應用 | zh_TW |
| dc.subject | 區塊鏈 | zh_TW |
| dc.subject | 機器學習 | zh_TW |
| dc.subject | 量化投資 | zh_TW |
| dc.subject | Blockchain | en |
| dc.subject | Decentralized Application | en |
| dc.subject | Smart Contracts | en |
| dc.subject | PoC | en |
| dc.subject | Quantitative Trading | en |
| dc.subject | Machine Learning | en |
| dc.subject | Gamification | en |
| dc.title | 台股投資更聰穎：從機器學習到區塊鏈結合遊戲化應用 | zh_TW |
| dc.title | Make Stock Portfolios Work Intelligently: From Machine Learning to Blockchain and Gamification | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳建錦(Chien-Chin Chen),盧信銘(Hsin-Min Lu) | |
| dc.subject.keyword | 概念驗證,量化投資,機器學習,區塊鏈,去中心化應用,智能合約,遊戲化, | zh_TW |
| dc.subject.keyword | PoC,Quantitative Trading,Machine Learning,Blockchain,Decentralized Application,Smart Contracts,Gamification, | en |
| dc.relation.page | 44 | |
| dc.identifier.doi | 10.6342/NTU201900958 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-06-28 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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|---|---|---|---|
| ntu-108-1.pdf 未授權公開取用 | 1.88 MB | Adobe PDF |
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