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研究生:賴芊卉
研究生(外文):Chien-hui Lai
論文名稱:跨市場股票、石油、黃金、白銀及外匯之報酬相關性網絡分析
論文名稱(外文):Network analysis of Cross markets stocks, Oil, Gold, Silver and Forex
指導教授:馬黛馬黛引用關係
指導教授(外文):Tai Ma
學位類別:碩士
校院名稱:國立中山大學
系所名稱:財務管理學系研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:84
中文關鍵詞:中心性跨市場金融商品分析社會網絡分析股票相關性網絡
外文關鍵詞:commodity analysiscross-market analysissocial networkcentralityreturn correlation network
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  • 被引用被引用:1
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  • 下載下載:97
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在本研究中我們建構跨市場中上市股票、商品和外匯之相關性網路。不同以往研究關於市場傳染性傳統的文章,本研究試圖使用社會網絡拓樸學去分析跨市場股票及金融商品的資訊流動。股票相關性網路的變化可以透過eigenvector centrality、degree、betweenness、closeness、modularity及density等網路參數充份表現出來。這些網絡參數提供有趣的經濟意涵包括資訊不對稱、從眾效應以及資訊的流動,它們比傳統的 VAR 分析在市場傳染性的研究中提供更多豐富洞見。例如,我們可以回應的問題有 : 在跨市場中,那支股票或是金融商品在資訊傳遞中是最重要的? 或是在跨產業中,哪個產業在資訊中是最重要的? 在特定事件發生前後,整個相關性網絡是如何變化? 以及更重要的一點,網絡參數與全球市場報酬率的分配之間的關係為何?本研究將建構每日的股票及金融商品相關性網絡,進而去估計與報酬率特性之間的關係。

本研究是首篇將相關性網絡分析應用在跨股票、跨商品市場的研究,本文的目的主要有三方面:

1. 估計每檔股票或金融商品在跨市場訊息傳遞的網絡"重要性"。
2. 透過將資料動態視覺化,觀察在重要的事件發生時,網絡結構的變化,並據以探討發生此變化背後的原因。
3. 實證分析跨市場網絡結構參數與報酬率特性之間的關係。
In this study we construct return correlation network for cross market listed stocks, commodities and foreign exchanges. Unlike conventional studies of market contagion, this study attempt to analyze the information flow among stocks using social network topologies. The change in return correlation network can be manifested by network parameters such as eigenvector centrality, degree, betweenness, closeness, modularity and density. These parameters have interesting economic connotation in terms of information asymmetry, herding, and information flow, and they can offer far more rich observation than traditional VAR analysis in market contagion studies. For example, we may be able to answer question such as which stock is the most important stock in information transmission across-markets or across industries, or how the correlation structure changes before and after certain events. More importantly, we can also identify the relationship between network topologies and global markets’ return distribution.

This is the first study to apply network analysis to cross market securities and cross products. The purposes are threefold:

1. To estimate the ‘importance’ of each stock in cross-market information transmission.
2. To observe changes in topologies at important market events using dynamic data visualization, and investigate the underlying causes.
3. To empirically test the relationship between return topologies and return attributes.
論文審定書...................................................................................................i
摘要..............................................................................................................ii
ABSTRACT...................................................................................................iii
I. INTRODUCTION...................................................................................1
1.1 BACKGROUND INFORMATION...........................................................1
1.2 RESEARCH PURPOSE........................................................................4
1.3 RESEARCH STRUCTURE....................................................................7
1.4 RESEARCH CONTRIBUTION...............................................................9
II. LITERATURE REVIEW.........................................................................10
2.1 SOCIAL NETWORK IN FINANCIAL FIELD..........................................10
2.2 CROSS MARKETS RESEARCH..........................................................12
III. METHODOLOGY...................................................................................17
3.1 DATA DESCRIPTION............................................................................17
3.2 RETURN CORRELATION NETWORK.................................................19
3.3 PANEL REGRESSION..........................................................................21
3.4 CROSS MARKETS NETWORK VISUALIZATION................................25
3.5 Z-SCORE FOR DEGREE.....................................................................26
IV. EMPIRICAL RESULTS.........................................................................28
4.1 DESCRIPTIVE STATISTICS............................................................... .28
4.2 NETWORK TOPOLOGY AND RETURN ATTRIBUTIONS....................51
4.3 Z-SCORE ANALYSIS.............................................................................60
4.4 MODULARITY VISUALIZATION............................................................62
V. CONCLUSION........................................................................................64
5.1 CONCLUSION........................................................................................64
5.2 SUGGESTIONS FOR FUTURE RESEARCH.........................................66
REFERENCES................................................................................................67
APPENDIX......................................................................................................69
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