(34.204.201.220) 您好!臺灣時間:2021/04/19 18:13
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:宋振維
研究生(外文):Chen-wei Sung
論文名稱:資訊網路結構與股票市場之關係
論文名稱(外文):The Relationship between Information Network Topology and Stock Market
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:2016
畢業學年度:104
語文別:英文
論文頁數:89
中文關鍵詞:資訊網路資產定價網路結構流動性波動性
外文關鍵詞:volatilityasset pricingnetwork topologyinformation networkliquidity
相關次數:
  • 被引用被引用:0
  • 點閱點閱:171
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:19
  • 收藏至我的研究室書目清單書目收藏:0
隨著行動網路的興起,資訊的交流變得愈來愈頻繁,近年來已有許多研究透過社會網路分析抑或是資訊網路來分析資訊的擴散與社會互動是否會對投資人的行為帶來影響,甚至是造成資產價格的改變。然而在過去的實證研究中,大多僅以結點(投資人)的角度來分析市場,幾乎沒有充分運用到整個網路結構的特質,故本研究嘗試去探究網路的內部結構究竟是如何對資產價格與市場品質造成影響。我們基於Ozsoylev et al. (2014)所提出的定義提出了投資人於個別股票上的資訊網路,當兩投資人短期間內於特定股票上具有同方向與相似價格的交易行為,且在一定期間內發生次數超過特定的門檻則代表他們彼此之間有資訊交流存在。依循這樣的規則建構網路,本文並透過網路參數,如網路的中心性 (centrality) 、平均距離 (distance) 以及模組化程度 (modularity) 來捕捉網路結構,並授予其經濟意義。
本研究主要的發現有三,(1)崩盤期間的資訊網路明顯比平常時期更為密集,代表投資人間的資訊交換更為頻繁。(2)另外,當網路結構參數的數值較高時,代表當下的資訊風險也開始增加,因此投資人會要求更高的報酬來彌補其所承擔的額外風險。(3)最後,我們可以發現到網路結構與市場品質之間存在一交互影響的關係,其中網路的平均距離與模組化程度皆會促使市場的波動性與不流動性的增加。
In recent studies, social network analysis or more generally, information networks provide a hopeful tool to help us explain the information diffusion of each investor. However, most empirical studies simply analyze the market in terms of the node level (investor), and don’t fully utilize the feature of network topology. Therefore, this study aims to investigate how asset price and market quality depend on the network’s general topological properties. We propose a methodology based on Ozsoylev et al. (2014) to define the information network of each stock. Two investors will have information linkage in a specific stock, if they trade at the same direction and similar order price within a short period. Furthermore, this behavior must exceed a certain threshold. According to this rule, we will build a network, and provide the economic meaning of network parameters, such as centrality, distance, and modularity.
The main findings of this study are as follows: (1) The information networks in crisis periods are more cluster than usual. (2) A higher degree of network parameters represents information risks are higher, hence investors would require a higher return for taking on extra risk. (3) There exists an interactive relationship between network topology and market quality. Modularity and distance both increase the volatility or illiquidity.
論文審定書 i
摘要 ii
ABSTRACT iii
I. INTRODUCTION 1
1.1 Background Information 1
1.2 Research Purpose 5
1.3 Research Structure 8
1.4 Research Contribution 10
II. LITERATURE REVIEW 11
2.1 Social Network Analysis 11
2.2 Information Network 15
III. METHODOLOGY 19
3.1 Data Description 19
3.2 Information Network 21
3.3 Measuring the Investor Performance 25
3.4 Network Topology and Asset Pricing 27
3.5 Network Topology and Market Quality 29
IV. EMPIRICAL RESULTS 31
4.1 Descriptive Statistics 31
4.2 Centrality and Investor Performance 45
4.3 Network Topology and Asset Pricing 48
4.4 Network Topology and Market Quality 58
V. CONCLUSION 64
5.1 Conclusion 64
5.2 Suggestions for future research 67
REFERENCES 68
Appendix 73
Adamic, L., Brunetti, C., Harris, J. H., & Kirilenko, A. A. (2010). Trading networks. Available at SSRN 1361184.
Ahern, K. R. (2015). Information networks: Evidence from illegal insider trading tips. Available at SSRN 2511068.
Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of financial markets, 5(1), 31-56.
Antweiler, W., & Frank, M. Z. (2004). Is all that talk just noise? The information content of internet stock message boards. The Journal of Finance, 59(3), 1259-1294.
Aouadi, A., Arouri, M., & Teulon, F. (2013). Investor attention and stock market activity: Evidence from France. Economic Modelling, 35, 674-681.
Aslan, H., Easley, D., Hvidkjaer, S., & O''hara, M. (2011). The characteristics of informed trading: Implications for asset pricing. Journal of Empirical Finance, 18(5), 782-801.
Asness, C., & Fabozzi, F. J. (2004). Short selling: strategies, risks, and rewards (Vol. 137): John Wiley & Sons.
Azar, P., & Lo, A. W. (2016). The Wisdom of Twitter Crowds: Predicting Stock Market Reactions to FOMC Meetings via Twitter Feeds. Available at SSRN 2756815.
Banerjee, A. V. (1992). A simple model of herd behavior. The Quarterly Journal of Economics, 797-817.
Barber, B. M., & Loeffler, D. (1993). The “Dartboard” column: Second-hand information and price pressure. Journal of Financial and Quantitative Analysis, 28(02), 273-284.
Berkman, H., & Eugster, M. (2015). Social Interaction and Risk Taking.
Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of political Economy, 992-1026.
Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.
Brennan, M. J., & Subrahmanyam, A. (1996). Market microstructure and asset pricing: On the compensation for illiquidity in stock returns. Journal of financial economics, 41(3), 441-464.
Brown, J. R., Ivković, Z., Smith, P. A., & Weisbenner, S. (2008). Neighbors matter: Causal community effects and stock market participation. The Journal of Finance, 63(3), 1509-1531.
Brunnermeier, M. K. (2008). Deciphering the liquidity and credit crunch 2007-08. Retrieved from
Chen, H., De, P., Hu, Y. J., & Hwang, B.-H. (2014). Wisdom of crowds: The value of stock opinions transmitted through social media. Review of Financial Studies, 27(5), 1367-1403.
Chen, L., Qin, L., & Zhu, H. (2015). Opinion divergence, unexpected trading volume and stock returns: Evidence from China. International Review of Economics & Finance, 36, 119-127.
Chi, K. T., Liu, J., & Lau, F. C. (2010). A network perspective of the stock market. Journal of Empirical Finance, 17(4), 659-667.
Chuang, H. (2016). Brokers’ financial network and stock return. The North American Journal of Economics and Finance.
Cohen, L., Frazzini, A., & Malloy, C. (2008). The small world of investing: Board connections and mutual fund returns. Journal of Political Economy, 116(5), 951-979.
Colla, P., & Mele, A. (2010). Information linkages and correlated trading. Review of Financial Studies, 23(1), 203-246.
Das, S. R., & Chen, M. Y. (2007). Yahoo! for Amazon: Sentiment extraction from small talk on the web. Management Science, 53(9), 1375-1388.
Ding, R., & Hou, W. (2015). Retail investor attention and stock liquidity. Journal of International Financial Markets, Institutions and Money, 37, 12-26.
Easley, D., Hvidkjaer, S., & O’hara, M. (2002). Is information risk a determinant of asset returns? The journal of finance, 57(5), 2185-2221.
Easley, D., & O''hara, M. (2004). Information and the cost of capital. The journal of finance, 59(4), 1553-1583.
Ellison, G., & Fudenberg, D. (1993). Rules of thumb for social learning. Journal of political Economy, 612-643.
Ellison, G., & Fudenberg, D. (1995). Word-of-mouth communication and social learning. The Quarterly Journal of Economics, 93-125.
Geanakoplos, J. (2010). The leverage cycle NBER Macroeconomics Annual 2009, Volume 24 (pp. 1-65): University of Chicago Press.
Givoly, D., & Palmon, D. (1985). Insider trading and the exploitation of inside information: Some empirical evidence. Journal of business, 69-87.
Grossman, S. J., & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. The American economic review, 70(3), 393-408.
Grullon, G., Kanatas, G., & Weston, J. P. (2004). Advertising, breadth of ownership, and liquidity. Review of Financial Studies, 17(2), 439-461.
Hampton, K., Goulet, L. S., Rainie, L., & Purcell, K. (2011). Social networking sites and our lives. Retrieved July 12, 2011 from.
Han, B., & Yang, L. (2013). Social networks, information acquisition, and asset prices. Management Science, 59(6), 1444-1457.
Heiberger, R. H. (2014). Stock network stability in times of crisis. Physica A: Statistical Mechanics and its Applications, 393, 376-381.
Hellwig, M. F. (1980). On the aggregation of information in competitive markets. Journal of economic theory, 22(3), 477-498.
Hong, H., Kubik, J. D., & Stein, J. C. (2004). Social interaction and stock‐market participation. The journal of finance, 59(1), 137-163.
Jackson, M. O. (2008). Social and economic networks (Vol. 3): Princeton university press Princeton.
Jackson, M. O., & Rogers, B. W. (2007). Relating network structure to diffusion properties through stochastic dominance. The BE Journal of Theoretical Economics, 7(1).
Kaustia, M., & Knüpfer, S. (2012). Peer performance and stock market entry. Journal of Financial Economics, 104(2), 321-338.
Kuzubaş, T. U., Ömercikoğlu, I., & Saltoğlu, B. (2014). Network centrality measures and systemic risk: An application to the Turkish financial crisis. Physica A: Statistical Mechanics and its Applications, 405, 203-215.
Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 1315-1335.
Kyriakopoulos, F., Thurner, S., Puhr, C., & Schmitz, S. W. (2009). Network and eigenvalue analysis of financial transaction networks. The European Physical Journal B, 71(4), 523-531.
Manela, A. (2014). The value of diffusing information. Journal of Financial Economics, 111(1), 181-199.
Massa, M., & Simonov, A. (2006). Hedging, familiarity and portfolio choice. Review of Financial Studies, 19(2), 633-685.
Minoiu, C., & Reyes, J. A. (2013). A network analysis of global banking: 1978–2010. Journal of Financial Stability, 9(2), 168-184.
Nobi, A., Maeng, S. E., Ha, G. G., & Lee, J. W. (2013). Network topologies of financial market during the global financial crisis.
Ozsoylev, H. N. (2005). Asset pricing implications of social networks. Paper presented at the AFA 2006 Boston meetings paper.
Ozsoylev, H. N., & Walden, J. (2011). Asset pricing in large information networks. Journal of Economic Theory, 146(6), 2252-2280.
Ozsoylev, H. N., Walden, J., Yavuz, M. D., & Bildik, R. (2014). Investor networks in the stock market. Review of Financial Studies, 27(5), 1323-1366.
Pareek, A. (2012). Information networks: Implications for mutual fund trading behavior and stock returns. Paper presented at the AFA 2010 Atlanta Meetings Paper.
Peralta, G., & Zareei, A. (2015). A network approach to portfolio selection. Available at SSRN 2430309.
Sandler, L., & Raghavan, A. (1996). Salomon holders watch for possible buffetting. Wall Street Journal, 23, C1.
Shiller, R. J., & Pound, J. (1986). Survey evidence on diffusion of interest among institutional investors. Retrieved from
Shiller, R. J., & Pound, J. (1989). Survey evidence on diffusion of interest and information among investors. Journal of Economic Behavior & Organization, 12(1), 47-66.
Shin, H. S. (2010). Risk and liquidity: OUP Oxford.
Simon, D., & Heimer, R. (2012). Facebook finance: How social interaction propagates active investing. Paper presented at the AFA 2013 San Diego Meetings Paper.
Sprenger, T. O., Tumasjan, A., Sandner, P. G., & Welpe, I. M. (2014). Tweets and trades: The information content of stock microblogs. European Financial Management, 20(5), 926-957.
Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. The Journal of Finance, 62(3), 1139-1168.
Tetlock, P. C. (2010). Does public financial news resolve asymmetric information? Review of Financial Studies, 23(9), 3520-3557.
Tetlock, P. C., SAAR‐TSECHANSKY, M., & Macskassy, S. (2008). More than words: Quantifying language to measure firms'' fundamentals. The Journal of Finance, 63(3), 1437-1467.
Tumarkin, R., & Whitelaw, R. F. (2001). News or noise? Internet postings and stock prices. Financial Analysts Journal, 57(3), 41-51.
Ugander, J., Karrer, B., Backstrom, L., & Marlow, C. (2011). The anatomy of the facebook social graph.
Varian, H. R. (1985). Divergence of opinion in complete markets: A note. The Journal of Finance, 40(1), 309-317.
Walden, J. (2014). Trading, profits, and volatility in a dynamic information network model. Available at SSRN 2561055.
Yan, X.-G., Xie, C., & Wang, G.-J. (2014). The stability of financial market networks. EPL (Europhysics Letters), 107(4), 48002.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔