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系統識別號 U0002-0802201119544200
中文論文名稱 機構法人期貨交易行為與台灣股價指數變動之關聯性的實證研究:高頻資料的分析
英文論文名稱 Futures Trading Behaviors of Institutional Investors and Stock Price Changes in Taiwan: An Analysis with High-Fquency Data
校院名稱 淡江大學
系所名稱(中) 財務金融學系碩士在職專班
系所名稱(英) Department of Banking and Finance
學年度 99
學期 1
出版年 100
研究生中文姓名 梁雅琪
研究生英文姓名 Ya-Chi Liang
學號 797530184
學位類別 碩士
語文別 中文
口試日期 2011-01-09
論文頁數 59頁
口試委員 指導教授-邱建良
指導教授-白東岳
委員-俞海琴
委員-李命志
委員-邱哲修
中文關鍵字 機構法人  買賣價差  資訊不對稱  波動度 
英文關鍵字 Institutional investors  Bid-ask spread  Information asymmetries  Volatilities 
學科別分類
中文摘要 本研究主要探討台灣機構法人的期貨交易行為對現貨市場之影響,並著重股票報酬率及股價波動度的檢測,此外,本文透過研究買賣價差與不同交易人交易行為之間的關係,進一步分析市場深度的變化狀況,其實證結果希冀能提供主管機關及市場參與者不同之決策參考資訊。研究樣本選定台灣證券交易所發行量加權股價指數及台灣證券交易所發行量加權股價指數期貨,樣本期間則涵蓋2008年1月2日至2009年9月30日之每分鐘交易資料,而實證模型除了採用普通最小平方法外,本文進一步採用不同設定之GARCH模型進行檢測。
實證結果發現:股票波動度與現貨成交量增加期貨買賣價差,此現象可歸因於市場參與者資訊不對稱的因素所致,特別是自營商的期貨交易增加會使期貨買賣價差擴大,但投信與外資的交易和期貨買賣價差則呈現負關係。在現貨市場方面,現貨成交量和股票報酬率呈現顯著的負相關,現貨波動性與股票報酬率呈現顯著的正相關,亦顯示高風險伴隨著高報酬,另一方面,機構法人的期貨交易行為和股票報酬率呈現反向的關係,可能解釋之一是機構法人較一般投資人有資訊優勢,因此,現貨的交易資訊無法立即反應到相關股票價格上,股價將出現遞延現象。最後,機構法人的期貨交易行為和買賣價差、報酬率的波動均有顯著的關係。整合上述,相關所得結果將有助於提供主管機關制定政策及投資者訂定避險策略之市場分析。
英文摘要 This study mainly investigates the effects of trading behaviors of major institutional investors from Taiwan futures market on the spot market and focus on the bid-ask spread and spot market returns. In addition, we also further analyze the variations of market depth through examining the relationships between bid-ask spread and trading behaviors of different institutional investors. Our results will provide a well know to major authorities and market participants in deciding relevant policies. The sample selects the TWSE Capitalization Weighted Stock Index and the TAIFEX stock index futures, and the intraday data compiled over per minute trading information from January 2, 2008 to September 30, 2009. Our empirical models adopt different GARCH models except ordinary least squares method.
The empirical results show the evidence that both trading volumes and the volatilities of returns in spot market increases future spreads, and furthermore, falling in information asymmetries. In particular, the futures trading from dealer increases future spreads, but not found in foreign investors and investment trust companies. They have the negative relationships. In the spot market, the market trading volume presents significantly negative effect on the stock returns, and the positive relationship between the returns and volatilities is found in spot market. This clearly states the implication that highly investment risk will require highly expected returns. On the other hands, the trading of major institutional investors in futures market have opposite relationships with the spot market returns. One possible explanation is that the institutional investors, in general, usually hold high information advantage than individual investors. Therefore, when spot market does not immediately reflect to the market relevant information, stock price will appear lag phenomenon. Finally, the institutional futures trading present significant effects in the volatilities of both spreads and returns. In sum, our results provide some key information and implications, and the outcomes will aid to provide policy-makers and market investor in-depth analysis and understand in the decisions of policy and hedging strategy.
論文目次 目 錄
第一章 緒 論 1
第一節 研究背景 1
第二節 研究動機 4
第三節 研究目的 6
第四節 研究流程 7
第五節 架構 8
第二章 文獻回顧 9
第一節 期貨交易與現貨市場 9
第二節 期貨交易與市場效率性 14
第三節 股票市場報酬的特性 19
第三章 研究方法與實證模型 24
第一節 單根檢定 24
第二節 ARCH效果檢定 26
一、Q檢定 27
二、LM檢定 28
第三節 實證模型 29
一、變數定義 29
二、傳統OLS模型 31
三、GARCH-N模型 32
四、GARCH-X模型 34
五、GARCH-ST-X模型 35
第四章 資料來源、處理與分析 36
第一節 樣本資料 36
第二節 樣本資料的基本統計量 37
第五章 實證結果與分析 41
第一節 單根檢定 41
第二節 實證模型之結果分析 43
第六章 結論 52
參考文獻 54
表 目 錄
頁次
【表1-1-1】台灣期貨交易所期貨年度交易量1
【表4-2-1】變數基本敘述統計量38
【表5-1-1】ADF單根檢定法41
【表5-1-2】PP單根檢定法42
【表5-2-1】期貨市場買賣價差之GARCH(1,2)模型估計結果47
【表5-2-2】現貨報酬之GARCH(1,1)模型估計結果50
圖 目 錄
頁次
【圖1-1-1】台灣期貨市場自然人及法人交易比重2
【圖4-2-1】大盤報酬率與現貨成交量39
【圖4-2-2】大盤報酬率與自營商期貨成交量比例39
【圖4-2-3】大盤報酬率與外資期貨成交量比例40
【圖4-2-4】大盤報酬率與投信期貨成交量比例40
【圖5-2-1】期貨市場買賣價差之條件變異走勢圖51
【圖5-2-2】現貨市場股價報酬之條件變異走勢圖51


參考文獻 一、國外文獻
1. Antoniou , A., Koutmos, G. and Pericli, A., (2005), “Index Futures and Positive Feedback Trading: Evidence from Major Stock Exchanges”. Journal of Empirical
2. Bae, S. C., Kwon, T. H. and Park, J. W., (2004), “Futures Trading, Spot Market Volatility, and Market Efficiency: The Case of the Korean index futures markets”. Journal of Futures Markets, Vol. 24, No. 12, pp. 1195 – 1228.
3. Bauer, C., (2007), “A Better Asymmetric Model of Changing Volatility in Stock and Exchange Rate Returns: Trend-GARCH”. European Journal of Finance, Vol. 13, No. 1-2, pp. 65-87.
4. Bhargava, V. and Malhotra, D. K., (2007), “The Relationship between Futures Trading Activity and Exchange Rate Volatility, Revisited”. Journal of Multinational Financial Management, Vol. 17, No. 2, pp. 95-111.
5. Bollerslev, T., (1986), “Generalized Autoregressive Conditional Heteroskedasticity”. Journal of Econometrics, Vol. 31, No. 3, pp. 307-327.
6. Chen, Z. and Daigler, R. T., (2008), “An Examination of the Complementary Volume-Volatility Information Theories”. Journal of Futures Markets, Vol. 28, No. 10, pp. 963-992.
7. Copeland, L., Lam, K. and Jones, S. A., (2004), “The Index Futures Markets: Is Screen Trading More Efficient?”. Journal of Futures Markets, Vol. 24, NO. 4, pp. 337-357.
8. Danielsen, B. R., Van Ness, R. A. and Warr, R.S., (2009), “Single Stock Futures as a Substitute for Short Sales: Evidence from Microstructure Data”. Journal of Business Finance and Accounting, Vol. 36, No. 9-10, pp. 1273-1293.
9. Dettling, M. and Buhlmann, P., (2004), “Volatility and Risk Estimation with Linear and Nonlinear Methods Based on High Frequency Data”. Applied Financial Economics, Vol. 14, No. 10, pp. 717-729.
10. Engle, R. F., (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Varianceof UK Inflation”. Econometrica, Vol. 50, No. 4, pp. 987-1008.
11. Floros, C. and Vougas, D., (2006). “Index Futures Trading, Information and Stock Market Volatility: The Case of Greece”. Derivatives Use, Trading Regulation, Vol. 12, No. 1, pp. 146-166.
12. Fung, J. K.W. and Tse Y., (2008), “Efficiency of Single-Stock Futures: An Intraday Analysis”. Journal of Futures Markets, Vol. 28, No. 6, pp. 518 – 536.
13. Hansen, B., (1994), “Autoregressive conditional density estimation”. International Economic Review, Vol. 35, No. 3, pp. 705-730.
14. Harris, L. (2003), “Testing and Exchanges”. New York: Oxford University Press.
15. Huang, Y. C., (2004), “The Market Microstructure and Relative Performance of Taiwan Stock Index Futures: A Comparison of Singapore Exchange and Taiwan Futures Exchange,” Journal of Financial Markets, Vol. 7, No. 3, pp. 335-350.
16. Kumar, U. and Tse, Y., (2009), ”Single-Stock Futures: Evidence from the Indian Securities Market”, Global Finance Journal, Vol. 20, No. 3, pp. 220-234.
17. Martens, M. and Zein, J.,(2004), “Predicting Financial Volatility: High-Frequency Time-Series Forecasts Vis-a-Vis Implied Volatility”. Journal of Futures Markets, Vol. 24, No. 11, pp. 1005-1028.
18. Mclnish, T.H. and Wood, R.A., (1992), “An Analysis of Intraday Patterns in Bid/Ask Spread of the Underlying Stock”. Journal of Finance, Vol. 47, No. 2, pp. 753-764.
19. McMillan, D. G. and Raquel, Q. G., (2009), “Intra-day Volatility Forecasts”. Applied Financial Economics, Vol. 19, No. 7-9, pp. 611-623.
20. McMillan, D. G. and Speight, A. E. H., (2006), “Nonlinear Dynamics and Competing Behavioral Interpretations: Evidence from Intra-Day FTSE-100 Index and Futures Data”. Journal of Futures Markets, Vol. 26, No. 4, pp. 343-368.
21. Noh, J. and Kim, T. H., (2006), “Forecasting Volatility of Futures Market: The S&P 500 and FTSE 100 Futures Using High Frequency Returns and Implied Volatility”. Applied Economics, Vol. 38, No. 4, pp. 395-413.
22. Phillips, P. C. B. and Perron, P., (1988), “Testing for a Unit Root in Time Series Regression”. Biometrica, Vol.75, No. 2, pp. 335-346.
23. Phylaktis, K. and Manalis, G., (2008), “Futures trading and market microstructure of the underlying security: A high frequency natural experiment at the single stock future level”. Working paper.
24. Poskitt, R., (2007), “Benchmark Tipping and the Role of the Swap Market in Price Discovery”. Journal of Futures Markets, Vol. 27, No. 10, pp. 981-1001.
25. Puri, T. N. and Philippatos, G. C., (2008), “Asymmetric Volume-Return Relation and Concentrated Trading in LIFFE Futures”. European Financial Management, Vol. 14, No. 3, pp. 528-563.
26. Said, S. E. and Dickey, D. A., (1984), “Testing for Unit Roots in Autoregressive Moving Average Model for Unknown Order”. Biometrica, Vol. 71, No. 3, pp. 599-607.
27. Shastri, K., Thirumalai, R.S. and Zutter, C. J., (2008), “Information Revelation in the Futures Market: Evidence from the Single Stock Futures Market”. Journal of Futures Markets, Vol. 28, No. 4, pp. 335-353.
28. Staikouras, S. K., (2006), “Testing the Stabilization Hypothesis in the UK Short-Term Interest Rates: Evidence from a GARCH-X Model”. The Quarterly Review of Economics and Finance, Vol. 46, No. 2, pp. 169-189.
29. Taylor, N., (2004), “Modeling Discontinuous Periodic Conditional Volatility: Evidence from the Commodity Futures Market”. Journal of Futures Markets, Vol. 24, No. 9, pp. 805-834.
30. Verousis, T. and Gwilym, O., (2010). “An Improved Algorithm for Cleaning Ultra High-Frequency Data”. Journal of Derivatives and Hedge Funds, Vol. 15, No. 4, pp. 323-340.
31. Wu, C., Li, J. and Zhang, W., (2005), “Intradaily Periodicity and Volatility Spillovers between International Stock Index Futures Markets”. Journal of Futures Markets, Vol. 25, No. 6, pp. 553-585.
32. Xu, X. E. and Fung, H. G., (2005), “Cross-Market linkages between U.S. and Japanese Precious Metals Futures Trading”. Journal of International Financial Markets, Institutions and Money, Vol. 15, No. 2, pp. 107-124.
二、國內文獻
1. 丁誌魰,曾富敏(2005) 以向量自我迴歸模式探討台灣股價、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,頁43-74。
2. 王子湄,蕭朝興(2008) 台灣股市三大法人委託型態與價格行為的實證分析,管理與系統,第15卷第1期,頁55-92。
3. 王毓敏,黃瑞靜(2001) 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,頁97-114。
4. 余尚武,吳嘉欽(2000) 股價指數期貨對股票市場波動性的影響,企業管理學報,第47期,頁135-160。
5. 李存修,蔡垂君(2004) 近月台股期貨在交易、非交易、以及跨越交易與非交易期間之訊息傳遞實證-價格發現與價格波動率內涵,財務金融學刊,第12卷第1期,頁53-80。
6. 李存修,蔡垂君(2006) 由市場微觀結構論探討台灣10年期公債期貨日內不對稱的價量關係,財務金融學刊,第14卷第1期,頁125-152。
7. 李命志.洪瑞成.劉洪鈞(2006) 厚尾GARCH 模型之波動性預測能力比較,輔仁管理評論,第14卷第2期,頁47-72。
8. 周雨田,李志宏,巫春洲,(2002) 台灣期貨對現貨市場的資訊傳遞效果分析,財務金融學刊,第10卷第2期,頁1-22。
9. 林昭賢,許溪南(2004) 期貨交易者之交易行為及績效之研究,台灣管理學刊,第4卷第1期,頁107-121。
10. 柯美珠,蕭慧玲,邱敬貿(2006) 市場深度、價差與委託單不均衡之關聯分析,績效與策略研究,第3卷第2期,頁129-156。
11. 柏婉貞,黃柏農(2007) 台股指數貨與現貨市場日內報酬波動與交易量非線性行為之研究,經濟研究,第43卷第2期,頁181-208。
12. 胡緒寧,蘇欣玫,蘇榮斌(2006) 台指現貨與期貨上下變幅對波動性之分析-GARCH-X模型的應用,真理財經學報,第15期,頁 29-46。
13. 莊忠柱,胡文正,(2005) 具有狀態轉換過程下的台灣股價指數與股價指數期貨市場的報酬與波動性動態關係,財務金融學刊,第13卷第2期,頁71-96。
14. 許溪南,徐守德,郭玟秀,鄭麗慧(2007) 外資介入對台股指數與指數期貨正逆價差之影響,經濟研究,第43卷第1期,頁65-91。
15. 黃玉娟,林明白,(2003) 買賣單不平衡、價差和報酬之探討:以台指期貨在台灣期貨交易所及新加坡交易所為例,財務金融學刊,第11卷第1期,頁71-98。
16. 黃玉娟,陳嘉琳(2004) 買賣價差之分解-TAIFEX與SGX-DT之比較,管理評論,第23卷第1期,頁49-72。
17. 黃健銘,張惠雅(2009) 股市基差訊息對現貨報酬之影響:厚尾模型的應用,台灣金融財務季刊,第10卷第1期 頁81-106。
18. 楊聲勇,董澍琦,李昭蓉,黃喬郁(2006) 台灣股票市場與期貨市場間價格與波動性傳遞關係之探討-EGARCH-DCC模型之應用,中國統計學報,第44卷第4期,頁417-435。
19. 盧智強,古永嘉(2005) 台股報酬率不對稱均值反轉型態與反向投資之研究,輔仁管理評論第12卷第2期,頁67-97。
20. 盧陽正,翁振益,方豪(2008) 台灣股市三大法人持股調整、群聚效應、回饋交易、串流行為與群聚之動量持續性,管理與系統,第15卷第4期,頁523-543。
21. 薛舜仁(2004) 專業外資(QFII)買賣超與我國股市、期貨市場的關聯性研究,正修學報,第17期,頁189-208。
22. 謝文良(2002) 價格發現、資訊傳遞、與市場整合—台股期貨市場之研究,財務金融學刊,第10卷第3期,頁1-31。
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