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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳信希(Hsin-Hsi Chen) | |
| dc.contributor.author | Ting-Wei Hsu | en |
| dc.contributor.author | 許庭瑋 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:07:14Z | - |
| dc.date.available | 2021-09-11 | |
| dc.date.available | 2022-11-23T09:07:14Z | - |
| dc.date.copyright | 2021-09-11 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-09-03 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79677 | - |
| dc.description.abstract | 在進行投資決策時，投資者都會面臨著風險與收益的權衡。然而，以往在自然語言處理領域的工作大多集中在預測股票價格或波動率的走勢上，而沒有考慮其他投資議題。這篇論文介紹三個基於社群媒體意見的投資任務—配對交易、投資組合選擇以及股票價格/風險動向預測。首先，為了對沖市場風險，我們提出了一種基於社群媒體的配對交易策略。與先前的任務設置相比較，我們的實驗結果表明，採用配對任務設置的神經網絡模型在準確性和盈利性指標上均都有較好的表現。第二，很少有研究在處理投資組合選擇時考慮金融界的非結構化數據。我們引入了一種新穎的基於財務文本的投資組合選擇任務，並提出了新的目標函數去處理投資者不同的風險偏好。同時討論了夏普比率和波動率兩個指標對選擇投資組合的實證研究。第三，我們提出了語義保留的增廣方法，並在六個公開資料集上均達到更好的表現，且據此來更精準地預測金融市場未來股票的價格與風險動向。此外，我們將以上研究成果發展成展示網站，提供投資者財務決策上的建議。綜上所述，本研究為未來基於財金社群媒體的群眾智慧投資決策引入了新的研究方向。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:07:14Z (GMT). No. of bitstreams: 1 U0001-3008202115362000.pdf: 6096229 bytes, checksum: 159504d7a0df1d65a706db9d7e81554a (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | Chapter 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Overview of Related Literature . . . . . . . . . . . . . . . . . . . . 1 1.3 Organization of This Thesis . . . . . . . . . . . . . . . . . . . . . . 2 Chapter 2 Opinion-based Pair Trading 5 2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . 7 Chapter 3 Opinion-based Portfolio Selection 9 3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.3.1 Task Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.3.2 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.3.3 Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.3.4 Risk-aware Regularization . . . . . . . . . . . . . . . . . . . . . . 13 3.3.5 Trend-based Loss Functions . . . . . . . . . . . . . . . . . . . . . 14 3.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.4.1 Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.4.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.4.3 Backtesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Chapter 4 Stock Price/Risk Movement Prediction 19 4.1 Semantics-Preserved Data Augmentation . . . . . . . . . . . . . . . 19 4.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.2.1 Data Augmentation . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.2.2 Aspect-Based Sentiment Analysis . . . . . . . . . . . . . . . . . . 21 4.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3.1 An Auxiliary Sentence Approach . . . . . . . . . . . . . . . . . . . 22 4.3.2 Selective Perturbed Masking (SPM) . . . . . . . . . . . . . . . . . 23 4.3.3 Token Replacement Strategy . . . . . . . . . . . . . . . . . . . . . 24 4.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.4.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.4.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.5.1 Multilingual Experiment . . . . . . . . . . . . . . . . . . . . . . . 28 4.5.2 Influence of Augmentation Size . . . . . . . . . . . . . . . . . . . 28 4.5.3 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 4.6 Stock Price/Risk Movement Prediction . . . . . . . . . . . . . . . . 30 4.6.1 Influence of Auxiliary Sentence . . . . . . . . . . . . . . . . . . . 31 Chapter 5 Demonstration 33 Chapter 6 Conclusion 35 References 37 | |
| dc.language.iso | en | |
| dc.title | 群眾智慧投資決策 – 配對交易、投資組合選擇以及股票價格/風險動向預測 | zh_TW |
| dc.title | "Opinion-based Investment Decisions – Pair Trading, Portfolio Selection, and Stock Price/Risk Movement Prediction" | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 陳孟彰(Meng Chang Chen) | |
| dc.contributor.oralexamcommittee | 陳建錦(Hsin-Tsai Liu),陳冠宇(Chih-Yang Tseng),王釧茹 | |
| dc.subject.keyword | 意見探勘,自然語言處理,財金社群媒體, | zh_TW |
| dc.subject.keyword | Opinion Mining,Natural Language Processing,Financial Social Media, | en |
| dc.relation.page | 44 | |
| dc.identifier.doi | 10.6342/NTU202102899 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-09-06 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資料科學學位學程 | zh_TW |
| 顯示於系所單位： | 資料科學學位學程 | |
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