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系統識別號 U0002-2106201113001800
中文論文名稱 與成交量有關之市場微結構變數對股價報酬的分析與探討
英文論文名稱 Investigate and Analyze the Effect of the Microstructure Variables Related to Trading Volume for Stock Returns.
校院名稱 淡江大學
系所名稱(中) 管理科學研究所碩士班
系所名稱(英) Graduate Institute of Management Science
學年度 99
學期 2
出版年 100
研究生中文姓名 陳柏文
研究生英文姓名 Po-Wen Chen
電子信箱 luckykevin101@yahoo.com.tw
學號 698620993
學位類別 碩士
語文別 中文
口試日期 2011-05-09
論文頁數 62頁
口試委員 指導教授-倪衍森
委員-牛涵錚
委員-蕭文姃
中文關鍵字 市場微結構  成份股  日內資料 
英文關鍵字 Microstruture  Constituent stock  Intraday data 
學科別分類 學科別社會科學管理學
中文摘要 本研究以市場微結構的觀點來探討台灣50成份股的價量關係。在採用計量模型對2005年至2009的日內資料進行分析後,獲致一些相當令人印象深刻的研究發現。在本研究實證結果中,發現開盤量與股價報酬呈負向關係,此表示開盤暴量並不有利於股價的推升,然而若當日股價漲幅達半個漲停板以上時,則開盤量增,反而與上述實證結果有所不同,亦為反而有利於股價的推升。而外資買超對台股有推升之效,此並不出人意表,但若採用外資介入比率為研究變數,且此變數在相關研究上幾乎付之闕如,本研究卻發現若外資當日買入加賣出的金額占成交量的比重越高時,則不論當日外資是否為買超,其對股價亦有顯著且正向的影響。
英文摘要 This study investigates the microstructure relationship related to price and volume for constituent stocks of Taiwan 50. By employing econometric approaches for intraday data from 2005 to 2009, this study explores several impressive findings. The studied result discloses that opening trading volume would negatively affect stock returns. It means that burst trading volume happened in the opening trading period is not a good signal for buying stocks. However, if the stock price rises up over 3.5%, the result, on the country, show a good signal for buying shares. The higher net buy from foreign institution would lift up share prices well-known by previous studies. Nevertheless, higher participation of foreign investment institution, namely, the higher the percentage of trading volume including total buying and selling volume without taking net buy or net sell into account, would positively affect stock returns, which is seldom employed and disclosed by relevant studies.
論文目次 目 錄

第壹章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究流程 5
第四節 研究架構 6
第貳章 文獻探討 7
第一節 成交量與市場微結構 7
第二節 股價與市場微結構 9
第三節 價量關係與市場微結構 11
第參章 研究假設與方法 17
第一節 資料選取與研究變數之介紹 17
第二節 研究問題與假設 23
第三節 研究分析方法 25
第四節 研究模型 27
第肆章 實證結果 29
第一節 敘述統計分析 29
第二節 迴歸模型分析 33
第三節 迴歸模型的進一步分析 45
第四節 實證結果之彙整與分析 51
第伍章 結論 53
第一節 研究結論 53
第二節 投資管理意涵 55
第三節 研究限制與後續相關研究之建議 56
參考文獻 58

表 目 錄
表 3-1 台灣 50 成份股 18
表 3-2 變數定義參照表 22
表 4-1 台灣 50 成份股各變數之敘述統計分析表 29
表 4-2 台灣 50 成份股個股報酬率之敘述統計分析表 30
表 4-3 多元迴歸模型之實證分析表 34
表 4-4 Logit 迴歸模型 1 之實證分析表 38
表 4-5 Logit 迴歸模型 2 之實證分析表 42
表 4-6 多元迴歸模型之實證分析表 (全部樣本) 45
表 4-7 Logit 迴歸模型 1 之實證分析表 (全部樣本) 47
表 4-8 Logit 迴歸模型 2 之實證分析表 (全部樣本) 49
表 4-9 實證結果之迴歸模型彙整與分析表 51

圖 目 錄
圖 1-1 研究流程 5
參考文獻 參考文獻

一、中文文獻
1. 丁誌魰、曾富敏,「以向量自我迴歸模式探討臺灣股價、成交量、融資融券與法人進出之關聯性」,真理財經學報,第13期,2005年,頁43-74。
2. 王毓敏、黃瑞靜,「價量關係-台股指數期貨市場之研究」,台灣金融財務季刊,第2卷,第2期,2001年,頁97-114。
3. 李修全、周賢榮,「台灣股價指數期貨價量同時關係之研究」,台灣金融財務季刊,第4卷,第4期,2003年,頁109-122。
4. 江明憲、鄭淯隆,「影響台灣股市日內股價變動因素之探討」,中山管理評論,第12卷,第1期,2004年,頁173-193。
5. 袁麗胜、宋逢明,「大額交易的生存分析與微觀市場狀態變遷」,運籌與管理,第15卷,第1期,2006年,頁73-77。
6. 莊家彰、管中閔,「台灣與美國股市價量關係的分量迴歸分析」,經濟論文,第33卷,第4期,2005年,頁379-404。
7. 菅瑞昌、王健聰、闕河士,「交易持續時間與交易價格衝擊之關係」,管理與系統,第16卷,第4期,2009年,頁 533-554。
8. 黃明棋,「成交量與匯率波動率對股票市場報酬之衝擊:以南韓股票市場報酬為例」,東亞論壇,第458期,2007年,頁67-84。
9. 韓千山,「股價動量現象之研究:理論與實證」,輔仁管理評論,第16卷,第2期,2009年,頁25-42。
10. 劉映興、陳家彬,「台灣股票市場交易值、交易量與發行量加權股價指數關係之實證研究─光譜分析之應用」,農業經濟半年刊,第72期,2002年,頁65-87。

二、英文文獻
1. Abhyankar, L. and Copeland, L.S. and Wong, W. “LIFE Cycles: Intraday Evidence from the FTSE-100 Stock Index Futures Market,” European Journal of Finance, Vol.5, 1999, pp.123-139.
2. Alexakis, C. and Xanthakis, E. “Market Trend, Company Size and Microstructure Characteristics of Intraday Stock Price Formations,” European Research Studies Journal, Vol.6, 2003, pp.81-96.
3. Ait-Sahalia, Yacine, “How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise,” Review of Financial Studies, Vol.18, 2005, pp.351-416.
4. Alexakis, Christos and Balios, Dimitris, “Investigating the Effects of Market Microstructure on Stock Price Formation and Volatility: Evidence from the Athens Stock Exchange,” Applied Financial Economics Letters, Vol.4, 2008, pp.225-231.
5. Al-Saad, Khalid and Moosa, Imad, “Asymmetry in the Price-Volume Relation: Evidence Based on Individual Company Stocks Traded in an Emerging Stock Market,” Applied Financial Economics Letters, Vol.4, 2008, pp.151-155.
6. Allen, Franklin and Gorton, Gary, “Stock Price Manipulation, Market Microstructure and Asymmetric Information,” Rodney L. White Center for Financial Research Working Papers No. 21-91, 2009.
7. Biais, Bruno and Glosten, Larry and Spatt, Chester S. “The Microstructure of Stock Markets,” CEPR Discussion Papers No. 3288, 2002.
8. Bildik, Recep and Gulay, Guzhan, “Are Price Limits Effective? Evidence from the Istanbul Stock Exchange,” Journal of Financial Research, Vol.29, 2006, pp.383-403.
9. Bayraktar, Erhan and Horst, Ulrich and Sircar, Ronnie, “Queueing Theoretic Approaches to Financial Price Fluctuations,” Quantitative Finance Papers No. Math/0703832, 2007.
10. Cooper, Michael, “Filter Rules Based on Price and Volume in Individual Security Overreaction,” Review of Financial Studies, Vol.12, 1999, pp.901-35.
11. Chen, Gong-meng and Firth, Michael and Rui, Oliver M. “The Dynamic Relation between Stock Returns, Trading Volume, and Volatility,” Financial Review, Vol.36, 2001, pp.153-73.
12. Chen, Shyh-Wei and Chen, Chun-Wei, “Testing for Nonlinear Granger Causality in the Price-Volume Relations of Taiwan's Stock and Foreign Exchange Markets,” Journal of Economics and Management, Vol.2, 2006, pp.21-51.
13. Ciner, Cetin and Sackley, William H. “Transactions, Volume and Volatility: Evidence from an Emerging Market,” Applied Financial Economics Letters, Vol.3, 2007, pp.161-164.
14. Du, Yan and Liu, Qianqiu and Rhee, S. Ghon, “An Anatomy of the Magnet Effect: Evidence from the Korea Stock Exchange High-Frequency Data,” Center for Economic Institutions, CEI Working Paper No. 2005-17.
15. De Jong, Frank and Rindi, Barbara, “The Microstructure of Financial Markets,” Department of Finance, Cambridge University, Paper No. 9780521687270, 2009.
16. Darolles, Serge and Fol, Gaelle Le and Mero, Gulten, “When Market Illiquidity Generates Volumes,” Working Papers No. halshs-00536046, 2010.
17. Easley, David and O'Hara, Maureen, “Microstructure and Ambiguity,” The Journal of Finance, Vol.65, 2010, pp.1817-1846.
18. Gunduz, Lokman and Hatemi-J, Abdulnasser, “Stock Price and Volume Relation in Emerging Markets,” Emerging Markets Finance and Trade, Vol.41, 2005, pp.29-44.
19. Huang, Roger D. and Stoll, Hans R. “Market Microstructure and Stock Return Predictions,” Review of Financial Studies, Vol.7, 1994, pp.179-213.
20. Hiemstra, Craig and Jones, Jonathan D. “Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation,” Journal of Finance, Vol.49, 1994, pp.1639-64.
21. Kumar, Brajesh and Pandey, Ajay and Singh, Priyanka, “The Dynamic Relationship between Price and Trading Volume: Evidence from Indian Stock Market,” Indian Institute of Management Ahmedabad, Working Paper No. 380015, 2005.
22. Karpoff, Jonathan M. “The Relation between Price Changes and Trading Volume: A Survey,” Journal of Financial and Quantitative Analysis, Vol.22, 1987, pp.109-126.
23. Krause, Andreas, “Microstructure Effects on Daily Return Volatility in Financial Markets,” Quantitative Finance Papers No. cond-mat/0011295, 2000.
24. Louhichi, Wael, “Adjustment of Stock Prices to Earnings Announcements: Evidence from Euronext Paris,” Review of Accounting and Finance, Vol.7, 2008, pp.102-115.
25. Mixon, Scott, “Volume and Volatility: News or Noise?” Financial Review, Vol.36, 2001, pp.99-118.
26. Madhavan, Ananth and Richardson, Matthew and Roomans, Mark, “Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks,” Rodney L. White Center for Financial Research, Working Papers No. 20-94, 2008.
27. Nowak, Sylwia, “How do Public Announcements Affect the Frequency of Trading in U.S. Airline Stocks?” Centre for Applied Macroeconomic Analysis CAMA Working Papers No. 2008-38, 2008.
28. Shi, Leilei, “Does Security Transaction Volume-Price Behavior Resemble a Probability Wave?” Quantitative Finance Papers No. 1001.0880, 2004.
29. Stephan, Jens A. and Whaley, Robert E. “Intraday Price Change and Trading Volume Relations in the Stock and Stock Option Markets,” Journal of Finance, Vol.45, 1990, pp.191-220.
30. Silvapulle, Param and Choi, Jong-Seo, “Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation: Korean Evidence,” Quarterly Review of Economics and Finance, Vol.39, 1999, pp.59-76.
31. Spierdijk, L. “Empirical Studies of Market Microstructure,” Open Access Publications from Tilburg University, Paper No. 12-111973, 2003.
32. Theodosopoulos, Ted, “Uncertainty Relations in Models of Market Microstructure,” Quantitative Finance, Papers No. Math/0409076, 2005.
33. Tsutsui, Yoshiro and Hirayama, Kenjiro and Tanaka, Takahiro and Uesugi, Nobutaka, “Special Quotes Invoke Autocorrelation in Japanese Stock Prices,” Asian Economic Journal, Vol.21, 2007, pp.369-386.
34. Ulibarri, Carlos A. “Introducing Contemporaneous Open-outcry and E-trading at the Chicago Board of Trade,” MPRA Paper No. 14821, 2004.
35. Vergote, Olivier, “Financial Transaction Data and Volatility,” Open Access Publications from Katholieke Universiteit Leuven, Paper No. 1979/2067, 2008.
36. Yoruk, Nevin and Erdem, Cumhur and S. E., Meziyet, “Testing for Linear and Nonlinear Granger Causality in the Stock Price-volume Relation: Turkish Banking Firms and Close Curly Quote Evidence,” Applied Financial Economics Letters, Vol.2, 2006, pp.165-171.
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