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博碩士論文 etd-0527117-143257 詳細資訊
Title page for etd-0527117-143257
論文名稱
Title
從投資人交易網絡結構,解釋資產定價、價格走勢型態與市場交易型態
Explaining asset pricing, price trend pattern and market trading pattern from investor trading network topology
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
81
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2017-06-21
繳交日期
Date of Submission
2017-06-27
關鍵字
Keywords
網絡結構參數、資產定價、價格走勢型態、投資人交易型態、機器學習
investor trading pattern, asset pricing, machine learning, network topologies, price pattern
統計
Statistics
本論文已被瀏覽 5781 次,被下載 27
The thesis/dissertation has been browsed 5781 times, has been downloaded 27 times.
中文摘要
本研究旨在建構台灣股票市場個股網絡 (stock network) 以及經紀商交易策略網絡 (broker trading network),並且探討網絡結構 (network topology) 與資產定價、價格走勢型態與市場交易型態之間的關係。透過社會網絡 (social network) 之分析方法,本研究可以從投資人網絡中萃取出網絡結構參數,例如網絡中心性 (centrality) 與模組化程度 (modularity) 等等。透過鑽研其中的變化,可以探討隱藏於股價變化表面之下的網絡結構變化現象。
關於網絡結構與資產報酬率的關係,本文採用三因子資產定價模型去驗證結構參數是否能解釋價格定價。結果三種網絡中以同策略網絡以及策略跟隨網絡獲得顯著結果,迴歸係數之表現也符合合理的網絡參數經濟意含。除此以外,本文以機器學習方式透過網絡結構參數特徵資料,對於股價走勢形態進行分類判定與預測。預測結果效果良好,顯示網絡結構之變化能有效反映股價變化。
Abstract
In this study, we construct stock network and broker trading network to explore the relationship between network topologies, returns, price patterns, and market trading patterns. Through social network topologies parameters such as centrality and modular-ity, we may be able to detect what’s underneath the price changes, that is, how the in-formation flow moves and changes overtime.
This study employs Fama-MacBeth regression model to verify the relationship between network topology and asset pricing. Results show that among the three net-works we have constructed, broker same strategy network and broker follow trade network provide significant results which are consistent with rational economic inter-pretations. Besides, this study also performs machine learning method to judge the pat-tern of price trend by using different network measures and the prediction results are satisfying.
目次 Table of Contents
論文審定書 i
摘要 ii
ABSTRACT iii
CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES vii
Chapter 1 INTRODUCTION 1
1.1 Background Information 1
1.2 Research Purpose 3
1.3 Research Structure 4
1.4 Research Contribution 6
Chapter 2 LITERATURE REVIEW 7
2.1 Social Network Analysis 7
2.1.1 Construction of social networks in financial area 7
2.1.2 Application of Network Topology in Finance 8
Chapter 3 METHODOLOGY 12
3.1 Data Description 12
3.2 Network Construction 14
3.2.1 Stock Return Correlation Network 14
3.2.2 Broker Same Strategy Trading Network 21
3.2.3 Broker Follow Trade Network 26
3.3 Network Topology and Asset Pricing 29
3.4 Measuring Broker Performance 31
3.5 Machine Learning Verification 33
Chapter 4 EMPIRICAL RESULTS 35
4.1 Descriptive Statistics 35
4.1.1 Stock and Market Data 35
4.1.2 Stock Return Correlation Network 36
4.1.3 Broker Trading Networks 43
4.2 The Relationship between Market and Network 50
4.3 Network Topology and Asset Pricing 54
4.4 Broker Centrality and Performance 57
4.5 Network Topology Trading Strategy 59
Chapter 5 CONCLUSION 62
5.1 Conclusion 62
5.2 Suggestion for Future Research 64
REFERENCES 65
APPENDIX 69
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