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標題: 台灣股市價量關係:分量迴歸分析之應用
Price-Volume Relation in Taiwan Stock Market: An Application of Quantile Regressions
作者: 柯純琥
Ke, Chun-Hu
關鍵字: V-shaped pattern
Quantile regression
Local quantile regression
Price-volume relation
Turnover rate
Trading volume
出版社: 財務金融系所
引用: 一、中文部分 王甡,(民84),報酬衝擊對條件波動所造成之不對稱效果--台灣股票市場之實證分析,證券市場發展季刊,7,125-160。 許和鈞、劉永欽 (民85),台灣地區股票市場價量之線性與非線性Granger因果關係之研究,證券市場發展季刊,8(4),23-49。 許溪南、黃文芳 (民86),台灣股市價量線性與非線性關係之研究,管理學報,14,177-195。 郭修旻、李秀雯 (民88),股票市場波動性與總體經濟波動性及市場交易量之關係─台灣市場實証研究,中國工商學報,21,249-272。 郭維裕與董慧萍,(民91),台灣地區股市『價』、『量』間非線性關係之探討--變動切換馬可夫轉換機率模型下的實證結果,中山管理評論,461-495。 莊家彰、管中閔(民94),台灣與美國股市價量關係的分量迴歸分析,經濟論文,33(4),379-404。 陳仕偉、陳俊偉(民95),台灣股票及外匯市場價量非線性因果關係之探討,經濟與管理論叢,2(1),21-51。 楊踐為與許至榮,(民86),台灣股票集中與店頭市場價量因果關係之探討,證券金融季刊,54,19-32。 葉銀華,(民80),台灣股票市場成交量與股價關係之實證研究--轉換函數模式,台北市銀月刊,22(11),57-70。 劉映興與陳家彬,(民91),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,72,65-87。 蕭幸金 (民82),股價與成交量相依程度之探討-台灣股市實証分析,政治大學會計研究所未出版之碩士論文。 聶建中與姚蕙芸,(民90),空頭走勢期間台灣股票市場成交量與股價之關聯性研究,2001會計理論與實務研討會論文集。 二、英文部分 Ackert, L.F. and G.Athanassakos, 2005, “The Relationship between Short Interest and Stock Returns in the Canadian Market,” Journal of Banking and Finance, 29, 1729–1749. Admati, A. R., and P. Pfleiderer, 1988, “A Theory of Intraday Patterns: Volume and Price Variability,” Review of Financial Studies 1, 3-40. Buchinsky, M., 1997, “Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research,” Journal of Human Resources 3, 125-145 Blume, L., D. Easley, and M. O’Hara, 1994, “Market Statistics and Technical Analysis: The Role of Volume,” Journal of Finance 49,153–182. Bohl, M.T. and H. Henke, 2003, “Trading Volume and Stock Market Volatility: The Polish Case,” International Review of Financial Analysis 12, 513–525. Campbell, J. Y., S. J. Grossman, and J. Wang, 1993, “Trading Volume and Serial Correlation in Stock Returns,” Quarterly Journal of Economics 108, 905-939. Copeland, T. E., 1977, “A Probability Model of Asset Trading,” Journal of Financial and Quantitative Analysis 12, 563-578. Cornell, B., 1981, “The Relationship between Volume and Price Variability in Futures Markets,” The Journal of Futures Markets 1, 303-316. Crouch, R. L., 1970, “The Volume of Transactions and Price Changes on the New Yew York Stock Exchange,” Financial Analysts Journal 26, 104-109. Episcopos, A., 1996, “Stock Return Volatility and Time-Varying Betas in the Toronto Stock Exchange,” Quarterly Journal of Business Economics 4, 28-38. Epps, T. W., 1975, “Security Price Changes and Transaction Volumes: Theory and Evidence,” American Economic Review 65, 586-597. Epps, T. W., 1977, “Security Price Changes and Transaction Volumes: Some Additional Evidence,” Journal of Financial and Quantitative Analysis 12, 141-146. Epps, T. W., 1978, “Security Price Changes and Transaction Volumes: Reply,” American Economic Review 68, 698-700. Epps, T. W. and M. L. Epps, 1976, “The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis,” Econometrica 44, 305-321. Gallo, G. M. and B. Pacini, 2000, “The Effects of Trading Activity on Marke Volatility,” European Journal of Finance 6, 163–175. Hamao, Y., R.W. Masulis and V. Ng, 1990, “Correlations in Price Changes and Volatility across International Stock Markets,” Review of Financial Study 3, 281–307. Hiemstra, C. and J. D. Jones, 1994, “Testing for Linear and Nonlinear Grange Causality in the Stock Price-Volume Relation,” Journal of Finance 49, 1639-1664. Huang, R. D. and R. W. Masulis, 2003, “Trading Activity and Stock Price Volatility: Evidence from the London Stock Exchange,” Journal of Empirical Finance 10, 249-269. Jaffe, J. and R. Westerfield, 1985, “The Weekend Effect in Common Stock Returns: The International Evidence,” Journal of Finance 40, 433–454. Jain, P. and G. Joh, 1988, “The Dependence between Hourly Prices and Trading Volume,” Journal of Financial and Quantitative Analysis 23, 269-84. Kanas, A., 2000, “Volatility Spillovers between Stock Returns and Exchange Rate Changes: International Evidence,” Journal of Business Finance and Accounting 27, 447-467. Karpoff, J. M., 1986, “A Theory of Trading Volume,” Journal of Finance 41, 1069-1087. Karpoff, J. M., 1987, “The Relation between Price Changes and Trading Volume: A Survey,” Journal of Financial and Quantitative Analysis 22, 109-126. Kim, S. J., 2005, “Information Leadership in the Advanced Asia–Pacific Stock Markets: Return, Volatility and Volume Information Spillovers from the US and Japan,” Journal of The Japanese and International Economies 19, 338-365. Koenker, R. and G. Basset, 1978,“Regression Quantiles,”Econometrica 46, 33-50. Koenker, R. and F. Hallok, 2001, “Quantile Regression,”Journal of Econometrics 15,143-156 Kuan, C.-M., 2004, “Introduction to Quantile Regression,” Lecture Notes, Institute of Economics, Academia Sinica ( Kwiatkowski, D., P. Phillips, P. Schmidt and Y. Shin, 1992, “Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root: How Sure are We that Economic Time Series have a Unit Root?” Journal of Econometrics 54, 159-178. Lakonishok, J. and S. Smidt, 1989, “Past Price Changes and Current Trading Volume,” Journal of Portfolio Management 15, 18–24. Lo, A.W. and J. Wang, 2000, “Trading Volume: Definitions, Data Analysis, and Implications of PortfolioTheory,” Review of Financial Studies 13, 257–300. Lee, B. S. and O. M. Rui, 2002, “The Dynamic Relationship between Stock Returns and Trading Volume: Domestic and Cross-country Evidence,” Journal of Banking and Finance 26, 51–78. Leign, W., N. Modani and R. Hightower, 2004, “A Computational Implementation of Stock Charting: Abrupt Volume Increase as Signal for Movement in New York Stock Exchange Composite Index,” Decision Support Systems 37, 515-530. Morse, D., 1980, “Asymmetrical Information in Securities Markets and Trading Volume,” Journal of Financial and Quantitative Analysis 15, 1129-1148. Morse, D., 1981, “Price and Trading Volume Reaction Surrounding Earnings Announcements: A Closer Examination,” Journal of Accounting Research 19, 374-383. Phillips, P. and P. Perron, 1988, “Testing for Unit Root in Time Series Regression,” Biometrika 75, 335-346. Schneller, M. I., 1978, “Security Price Changes and Transaction Volumes: Comment,” American Economic Review 68, 696-697. Smirlock, M., and L. Starks, 1985, “A Further Examination of Stock Price Changes and Transactions Volume,” Journal of Financial Research 8, 217-225 .Suominen, M., 2001, “Trading Volume and Information Revelation in Stock Markets,” Journal of Financial and Quantitative Analysis 36, 545–565. Wang, C. Y. and N. S. Cheng, 2004, “Extreme Volumes and Expected Stock Returns: Evidence from China''s Stock Market,” Pacific-Basin Finance Journal 12, 577-597. Ying, C. C., 1966, “Stock Market Prices and Volumes of Sales,” Econometrica 34, 676-685. Yu, K. and M.C. Jones,1998 , “Local linear Quantile Regression,” Journal of the American Statistical Association 93, 228-237
摘要: This thesis uses quantile regression to analyze price-volume relation in Taiwan Stock Market. Empirical data is collected from 2/27/1985 to 4/18/2008, totally 6296 daily observations. We use daily return of Taiwan Stock Market index as the price variable, and turnover rate and trading volume as the volume variables. When the linear quantile regression model is under investigated, we find that the relation between daily returns and turnover rates exhibit symmetric V-shaped across quantiles. This result indicates that a large return (in either sign) is usually accompanied with a large trading volume. A symmetric inverse V-shaped relation between daily returns and trading volumes is found by linear quantile regression. To study the nonlinear relation between price and volume, the local quantile regression is considered in this thesis. The symmetric V-shaped relation between daily returns and turnover rates is re-confirmed. However, the relations between daily returns and trading volumes are not constant over the range of trading volumes. In details, three regimes of the nonlinear relation between daily returns and trading volumes are found. At the first regime when the trading volume is from 8 to 10, the daily return increases as the trading volume increases. For the second regime with trading volumes from 10 to 13, symmetric V-shaped relation is found. For the third regime with trading volumes from13 to 16, an inverse symmetric V-shaped relation is found for the relation between daily returns and trading volumes. These findings support the necessity of using local quantile regression for studying the price-volume relation.
其他識別: U0005-2207200817433800
Appears in Collections:財務金融學系所



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