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題名 股市價量關係之實證研究-以美國、俄羅斯、巴西為例 作者 邱繼瑱 貢獻者 林其昂
邱繼瑱關鍵詞 向量自我迴歸模型
因果關係檢定
價量關係日期 2011 上傳時間 1-Nov-2012 14:00:49 (UTC+8) 摘要 本研究選取發達成熟市場的美國以及金磚四國其中一份子的俄羅斯及巴西分別檢視股價報酬率與成交量之間的動態價量關係(Dynamic Price-Volume Relationships)，本研究採行Granger (1969)因果關係檢定、近似無關迴歸模型檢定的研究方法，進行兩大部份分析，第一、三國各自進行股價報酬率與成交量之間是否在不同資料型態設計中有相異的價量因果關係。第二、引進以美國次貸風暴發生時間點視為結構變動點，進行次貸風暴發生前後各國股市價量領先落後情形是否發生異動。本研究選以美國、巴西、俄羅斯，各自所代表的股價指數分別是，美國代表指數分別是標準普爾500指數(Standard and Poor’s 500 Index)、那斯達克綜合指數(Nasdaq Composite Index)、道瓊綜合平均指數(Dow Jones Composite Average Index)、巴西為巴西指數(Bovespa Index)、俄羅斯代表為俄羅斯交易系統指數(RTS Index)。 本研究有別於先前文獻具體研究價值之處，本研究發現美國股票市場的價量關係因應著每個不同股價指數的屬性有所呈現出不同的價量關係樣貌，並且透過資料型態設計的不同、結構變動點的納入與以國家為出發的角度，洞察出美國、巴西、俄羅斯的價量關係會根據經濟體成熟度、產業結構、金融市場開放程度等因素，探究出可能出現不同價量關係的狀況。 其實證結果指出，就美國三大指數而言，以採納的所有資料型態綜觀歸納出，美國三大指數具有量先價行的因果關係，且以S&P500、Nasdaq指數以及空頭資料型態的Dow Jones指數呈現出價先量行的關係存在。次貸風暴的發生，美國三大指數具有價先量行的因果關係。 巴西Bovespa指數在每日空頭、每週多頭資料型態具有價先量行的結果，而當次貸發生前後皆不具任何的因果關係。 俄羅斯RTS指數除了在空頭資料型態部分，其餘皆呈現價先量行的結果，而在多頭資料型態部份，呈現量先價行的結果。而當次貸發生後，皆喪失任何因果關係。 參考文獻 國內文獻 丰珂 (2010)。上海股市價量關係的實證研究。經濟師，第5期，頁84-85。 吳清豐 (2006)。東亞各國家地區股市價量關係之研究。博士論文，雲林科技大學，雲林縣。 林惠玲、陳正倉(2004)。統計學-方法與應用(三版) (上)(下)。台北市:雙葉書廊。 姚蕙芸與梁志民 (2005)。空頭與多頭走勢期間台股股價與相關因素因果關係探討－以2000及2003年為例。企業管理學報，第66期，頁1-39。 施志明(2008)。次級房貸事件對美、德、中、英四國股市及總體經濟變數的影響。碩士論文，國立成功大學，台南市。 高士軒(2008)。價量關係：量是否為價格發現的先行指標。碩士論文，逢甲大學，台中市。 陳仕偉與陳俊偉(2006)。臺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，第2卷第1期，頁21-51。 陳旭昇(2009)。時間序列分析-總體經濟與財務金融之應用(修訂初版)。台北市:東華書局。 游啟民(2009)。價量關係的微結構:台灣五十成份股為例。碩士論文，淡江大學，新北市。 黃台心(2009)。計量經濟學(二版)。台北市:新陸書局。 鄭婉秀、邱哲修、陳玉瓏與洪偉哲(2004)。亞洲股市價量關係之不對稱效果。 華岡經濟論叢，第4卷第1期，頁26-48。 聶建中與姚蕙芸(2001)。空頭走勢期間台灣股票市場成交量與股價之關聯性研究。第十屆會計理論與實務研討會，台北市東吳大學。 顏治華(2008)。美國股市價量關係-非線性平滑轉換誤差修正模型實證研究。碩士論文，淡江大學，新北市。 國外文獻 Agents of change (2010, July 24-30). The Economist, 396(8692),61 Blume, L., Easley, D. and O`Hara, M. (1994). Market Statistics and Technical Analysis: The Role of Volume. The Journal of Finance, 49(1), 153-181. Breusch, T. S. and Pagan, A. R. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), 239-253. Brooks, C. (2008). Introductory econometrics for finance: Cambridge Univ Pr. Cetin, C. (2002). Information content of volume: An investigation of Tokyo commodity futures markets. Pacific-Basin Finance Journal, 10(2), 201-215. Chen, G.-m., Firth, M. and Rui, O. M. (2001). The Dynamic Relation Between Stock Returns, Trading Volume, and Volatility. Financial Review, 36(3), 153-174. Chen, S.-H. and Liao, C.-C. (2005). Agent-based computational modeling of the stock price-volume relation. Information Sciences, 170(1), 75-100 Chen, S.-H. and Yeh, C.-H. (2002). On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis. Journal of Economic Behavior & Organization, 49(2), 217-239. Chuang, C.-C., Kuan, C.-M. and Lin, H.-Y. (2009). Causality in quantiles and dynamic stock return-volume relations. Journal of Banking & Finance, 33(7), 1351-1360. Copeland, T. E. (1976). A Model of Asset Trading Under the Assumption of Sequential Information Arrival. The Journal of Finance, 31(4), 1149-1168. DeLong, J. B., Shleifer, A., Summers, L. H. and Waldmann, R. J. (1990). Positive Feedback Investment Strategies and Destabilizing Rational Speculation. The Journal of Finance, 45(2),379-395. Deo, M., Srinivasan, K. and Devanadhen, K. (2008). The Empirical Relationship between Stock Returns, Trading Volume and Volatility: Evidence from Select Asia-Pacific Stock Market. European Journal of Economics, Finance and Administrative Sciences, 12. Dickey, D. A. and Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(366), 427-431. Dickey, D. A. and Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057-1072. Enders, W. (2004). Applied Econometric Time Series, 2nd Edition: John Wiley&Sons, Inc. Epps, T. W. (1975). Security Price Changes and Transaction Volumes: Theory and Evidence. The American Economic Review, 65(4), 586-597. EViews 6 User’s Guide I (2007). Eviews 6. Quantitative Micro Software, LLC, Irvine, CA. USA EViews 6 User’s Guide II (2007). Eviews 6. Quantitative Micro Software, LLC, Irvine, CA. USA. Gallant, A. R., Rossi, P. E. and Tauchen, G. (1992). Stock Prices and Volume. The Review of Financial Studies, 5(2), 199-242. Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464. Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. Granger, C. W. J. and Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111-120. Hiemstra, C. and Jones, J. D. (1994). Testing for Linear and Nonlinear Granger Causality in the Stock Price- Volume Relation. The Journal of Finance, 49(5), 1639-1664. Jennings, R. H., Starks, L. T. and Fellingham, J. C. (1981). An Equilibrium Model of Asset Trading with Sequential Information Arrival. The Journal of Finance, 36(1), 143-161. Karpoff, J. M. (1987). The Relation Between Price Changes and Trading Volume: A Survey. The Journal of Financial and Quantitative Analysis, 22(1), 109-126. Lakonishok, J. and Smidt, S. (1989). Past price changes and current trading volume. [Article]. Journal of Portfolio Management, 15(4), 18-24. Lee, B.-S. and Rui, O. M. (2002). The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence. Journal of Banking & Finance, 26(1), 51-78. Mossin, J. (1973). Theory of financial markets: Prentice-Hall,Inc. Mubarik, F. and Javid, A. (2009). Relationship between Stock Return, Trading Volume and Volatility: Evidence from Pakistani Stock Market. Asia Pacific Journal of Finance and Banking Research, 3(3). Osborne, M. F. M. (1959). Brownian Motion in the Stock Market. Operations Research, 7(2), 145-173. Rashid, A. (2007). Stock prices and trading volume: An assessment for linear and nonlinear Granger causality. Journal of Asian Economics, 18(4), 595-612. Saatcioglu, K. and Starks, L. T. (1998). The stock price-volume relationship in emerging stock markets: the case of Latin America. International Journal of Forecasting, 14(2), 215-225. Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48. Srinivasan, K., Devanadhen, K. and Malabika, D. (2010). Price Changes, Trading Volume and Time-Varying Conditional Volatility: Evidence from Asia Pacific Stock Market. [Article]. International Review of Applied Financial Issues & Economics, 2(2), 379-390. Tesfatsion, L. and Judd, K. L. (2006). Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics. Staff General Research Papers. Wald, A. (1943). Tests of Statistical Hypotheses Concerning Several Parameters When the Number of Observations is Large. Transactions of the American Mathematical Society, 54(3), 426-482. White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817-838. Ying, C. C. (1966). Stock Market Prices and Volumes of Sales. Econometrica, 34(3), 676-685. Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368. 描述 碩士
國立政治大學
財政研究所
97255007
100資料來源 http://thesis.lib.nccu.edu.tw/record/#G0097255007 資料類型 thesis dc.contributor.advisor 林其昂 zh_TW dc.contributor.author (Authors) 邱繼瑱 zh_TW dc.creator (作者) 邱繼瑱 zh_TW dc.date (日期) 2011 en_US dc.date.accessioned 1-Nov-2012 14:00:49 (UTC+8) - dc.date.available 1-Nov-2012 14:00:49 (UTC+8) - dc.date.issued (上傳時間) 1-Nov-2012 14:00:49 (UTC+8) - dc.identifier (Other Identifiers) G0097255007 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/55156 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 財政研究所 zh_TW dc.description (描述) 97255007 zh_TW dc.description (描述) 100 zh_TW dc.description.abstract (摘要) 本研究選取發達成熟市場的美國以及金磚四國其中一份子的俄羅斯及巴西分別檢視股價報酬率與成交量之間的動態價量關係(Dynamic Price-Volume Relationships)，本研究採行Granger (1969)因果關係檢定、近似無關迴歸模型檢定的研究方法，進行兩大部份分析，第一、三國各自進行股價報酬率與成交量之間是否在不同資料型態設計中有相異的價量因果關係。第二、引進以美國次貸風暴發生時間點視為結構變動點，進行次貸風暴發生前後各國股市價量領先落後情形是否發生異動。本研究選以美國、巴西、俄羅斯，各自所代表的股價指數分別是，美國代表指數分別是標準普爾500指數(Standard and Poor’s 500 Index)、那斯達克綜合指數(Nasdaq Composite Index)、道瓊綜合平均指數(Dow Jones Composite Average Index)、巴西為巴西指數(Bovespa Index)、俄羅斯代表為俄羅斯交易系統指數(RTS Index)。 本研究有別於先前文獻具體研究價值之處，本研究發現美國股票市場的價量關係因應著每個不同股價指數的屬性有所呈現出不同的價量關係樣貌，並且透過資料型態設計的不同、結構變動點的納入與以國家為出發的角度，洞察出美國、巴西、俄羅斯的價量關係會根據經濟體成熟度、產業結構、金融市場開放程度等因素，探究出可能出現不同價量關係的狀況。 其實證結果指出，就美國三大指數而言，以採納的所有資料型態綜觀歸納出，美國三大指數具有量先價行的因果關係，且以S&P500、Nasdaq指數以及空頭資料型態的Dow Jones指數呈現出價先量行的關係存在。次貸風暴的發生，美國三大指數具有價先量行的因果關係。 巴西Bovespa指數在每日空頭、每週多頭資料型態具有價先量行的結果，而當次貸發生前後皆不具任何的因果關係。 俄羅斯RTS指數除了在空頭資料型態部分，其餘皆呈現價先量行的結果，而在多頭資料型態部份，呈現量先價行的結果。而當次貸發生後，皆喪失任何因果關係。 zh_TW dc.description.tableofcontents 表目錄 IV 圖目錄 V 第一章、緒論 1 第一節、研究動機與目的 1 第二節、研究流程 8 第二章、文獻探討 9 第一節、理論文獻 9 第二節、實證文獻 16 第三章、研究方法 27 第一節、資料辨認 27 第二節、跨期相關 29 第四章、實證結果與分析 34 第一節、資料簡介與處理 34 第二節、各國股市(多空頭)價量關係 37 第三節、次貸風暴前後之價量關係 57 第五章、結論 62 參考文獻 64 附錄 69 zh_TW dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0097255007 en_US dc.subject (關鍵詞) 向量自我迴歸模型 zh_TW dc.subject (關鍵詞) 因果關係檢定 zh_TW dc.subject (關鍵詞) 價量關係 zh_TW dc.title (題名) 股市價量關係之實證研究-以美國、俄羅斯、巴西為例 zh_TW dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 國內文獻 丰珂 (2010)。上海股市價量關係的實證研究。經濟師，第5期，頁84-85。 吳清豐 (2006)。東亞各國家地區股市價量關係之研究。博士論文，雲林科技大學，雲林縣。 林惠玲、陳正倉(2004)。統計學-方法與應用(三版) (上)(下)。台北市:雙葉書廊。 姚蕙芸與梁志民 (2005)。空頭與多頭走勢期間台股股價與相關因素因果關係探討－以2000及2003年為例。企業管理學報，第66期，頁1-39。 施志明(2008)。次級房貸事件對美、德、中、英四國股市及總體經濟變數的影響。碩士論文，國立成功大學，台南市。 高士軒(2008)。價量關係：量是否為價格發現的先行指標。碩士論文，逢甲大學，台中市。 陳仕偉與陳俊偉(2006)。臺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，第2卷第1期，頁21-51。 陳旭昇(2009)。時間序列分析-總體經濟與財務金融之應用(修訂初版)。台北市:東華書局。 游啟民(2009)。價量關係的微結構:台灣五十成份股為例。碩士論文，淡江大學，新北市。 黃台心(2009)。計量經濟學(二版)。台北市:新陸書局。 鄭婉秀、邱哲修、陳玉瓏與洪偉哲(2004)。亞洲股市價量關係之不對稱效果。 華岡經濟論叢，第4卷第1期，頁26-48。 聶建中與姚蕙芸(2001)。空頭走勢期間台灣股票市場成交量與股價之關聯性研究。第十屆會計理論與實務研討會，台北市東吳大學。 顏治華(2008)。美國股市價量關係-非線性平滑轉換誤差修正模型實證研究。碩士論文，淡江大學，新北市。 國外文獻 Agents of change (2010, July 24-30). The Economist, 396(8692),61 Blume, L., Easley, D. and O`Hara, M. (1994). Market Statistics and Technical Analysis: The Role of Volume. The Journal of Finance, 49(1), 153-181. Breusch, T. S. and Pagan, A. R. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), 239-253. Brooks, C. (2008). Introductory econometrics for finance: Cambridge Univ Pr. Cetin, C. (2002). Information content of volume: An investigation of Tokyo commodity futures markets. Pacific-Basin Finance Journal, 10(2), 201-215. Chen, G.-m., Firth, M. and Rui, O. M. (2001). The Dynamic Relation Between Stock Returns, Trading Volume, and Volatility. Financial Review, 36(3), 153-174. Chen, S.-H. and Liao, C.-C. (2005). Agent-based computational modeling of the stock price-volume relation. Information Sciences, 170(1), 75-100 Chen, S.-H. and Yeh, C.-H. (2002). On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis. Journal of Economic Behavior & Organization, 49(2), 217-239. Chuang, C.-C., Kuan, C.-M. and Lin, H.-Y. (2009). Causality in quantiles and dynamic stock return-volume relations. Journal of Banking & Finance, 33(7), 1351-1360. Copeland, T. E. (1976). A Model of Asset Trading Under the Assumption of Sequential Information Arrival. The Journal of Finance, 31(4), 1149-1168. DeLong, J. B., Shleifer, A., Summers, L. H. and Waldmann, R. J. (1990). Positive Feedback Investment Strategies and Destabilizing Rational Speculation. The Journal of Finance, 45(2),379-395. Deo, M., Srinivasan, K. and Devanadhen, K. (2008). The Empirical Relationship between Stock Returns, Trading Volume and Volatility: Evidence from Select Asia-Pacific Stock Market. European Journal of Economics, Finance and Administrative Sciences, 12. Dickey, D. A. and Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(366), 427-431. Dickey, D. A. and Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057-1072. Enders, W. (2004). Applied Econometric Time Series, 2nd Edition: John Wiley&Sons, Inc. Epps, T. W. (1975). Security Price Changes and Transaction Volumes: Theory and Evidence. The American Economic Review, 65(4), 586-597. EViews 6 User’s Guide I (2007). Eviews 6. Quantitative Micro Software, LLC, Irvine, CA. USA EViews 6 User’s Guide II (2007). Eviews 6. Quantitative Micro Software, LLC, Irvine, CA. USA. Gallant, A. R., Rossi, P. E. and Tauchen, G. (1992). Stock Prices and Volume. The Review of Financial Studies, 5(2), 199-242. Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464. Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. Granger, C. W. J. and Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111-120. Hiemstra, C. and Jones, J. D. (1994). Testing for Linear and Nonlinear Granger Causality in the Stock Price- Volume Relation. The Journal of Finance, 49(5), 1639-1664. Jennings, R. H., Starks, L. T. and Fellingham, J. C. (1981). An Equilibrium Model of Asset Trading with Sequential Information Arrival. The Journal of Finance, 36(1), 143-161. Karpoff, J. M. (1987). The Relation Between Price Changes and Trading Volume: A Survey. The Journal of Financial and Quantitative Analysis, 22(1), 109-126. Lakonishok, J. and Smidt, S. (1989). Past price changes and current trading volume. [Article]. Journal of Portfolio Management, 15(4), 18-24. Lee, B.-S. and Rui, O. M. (2002). The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence. Journal of Banking & Finance, 26(1), 51-78. Mossin, J. (1973). Theory of financial markets: Prentice-Hall,Inc. Mubarik, F. and Javid, A. (2009). Relationship between Stock Return, Trading Volume and Volatility: Evidence from Pakistani Stock Market. Asia Pacific Journal of Finance and Banking Research, 3(3). Osborne, M. F. M. (1959). Brownian Motion in the Stock Market. Operations Research, 7(2), 145-173. Rashid, A. (2007). Stock prices and trading volume: An assessment for linear and nonlinear Granger causality. Journal of Asian Economics, 18(4), 595-612. Saatcioglu, K. and Starks, L. T. (1998). The stock price-volume relationship in emerging stock markets: the case of Latin America. International Journal of Forecasting, 14(2), 215-225. Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48. Srinivasan, K., Devanadhen, K. and Malabika, D. (2010). 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