跳到主要內容

臺灣博碩士論文加值系統

(3.239.4.127) 您好!臺灣時間:2022/08/20 08:14
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:韋尊仁
研究生(外文):Tsun-Jen Wei
論文名稱:以GARCH及EGARCH模型探討交易活動對股價波動之影響﹕以摩根成份股為例
論文名稱(外文):The impacts of trading activity on returns volatility: the case of components of MSCI
指導教授:林楚雄林楚雄引用關係
指導教授(外文):Chu-Siung Lin
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:財務管理所
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:2002
畢業學年度:90
語文別:中文
論文頁數:58
中文關鍵詞:關鍵字:交易活動代理變數GARCHEGARCH波動性隔夜效應
外文關鍵詞:keyword:traded activelyGARCH(11)EGARCH(11)volatilityONIt (over night index )
相關次數:
  • 被引用被引用:5
  • 點閱點閱:604
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
摘要

本文以GARCH模型來探討91檔摩根成份股的交易活動對其股價波動持續性的影響,本文是以交易量作為交易活動的代理變數並採用GARCH(1,1) 或 EGARCH(1,1)來研究股價報酬率的波動性是否減弱。其次,本文考慮隔夜效應對股價波動的差異性影響。由於GARCH(1,1) 或 EGARCH(1,1) 模型對金融商品的時間序列有較一般傳統統計計量模型更好的描述性,因此本文以GARCH(1,1) 或 EGARCH(1,1) 模型來探討股票價格、成交量的波動關聯性,實證結果顯示股票價格與交易量的變動過程符合GARCH(1,1) 或 EGARCH(1,1) 模型,且隔夜效應 比其他的交易活動較能解釋價格的波動。
Abstract
This paper uses GARCH model to investigate the question of excessive implies persistence of volatility. Ninety one traded actively Taiwan stocks of SIMEX MSCI are considered and as already established in the literature, when volume traded is inserted in the GARCH(1,1) or EGARCH(1,1) model for returns, the estimated persistence is decreased since volume is affected also by within-the-day price movements. It is concluded that the difference between the opening price and the closing price of the previous day accounts also for most of the persistence in the autoregressive conditional hetero-skedasticity. The GARCH(1,1) or EGARCH(1,1) model is found to be more appropriate than traditional statistical models because it is capable of mimicking observed statistical characteristics of many time series of financial assets. The result of this study indicated that the change process of price and volume are best described by a GARCH(1,1) or EGARCH(1,1) model. Evidence is also exhibited that ONIt (over night index ) can help to explain the price volatility better than volume or other proxies.
目 錄

中文摘要i
英文摘要ii
誌謝iii
目錄iv
表目錄v
圖目錄v
第一章、緒論1
第一節 前言1
第二節 研究動機與目的4
第三節 研究架構與流程圖8
第二章、文獻回顧10
第一節 價量關係研究之文獻10
第二節 ARCH 模型的理論12
第三節 GARCH 模型的理論15
第四節 GARCH 與EGARCH模型的實證文獻17
第五節 交易活動加入模型的實證文獻19
第三章 資料分析與研究模型20
第一節 資料分析20
第二節、GARCH(1,1)與E GARCH(1,1)為最佳模型21
第三節 研究模型22
第四章 實證研究30
第一節 GARCH模型的實證結果30
第二節加入代理變數的GARCH模型的實證結果31
第三節 EGARCH模型的實證結33
第四節 加入代理變數的EGARCH模型的實證結果35
第五章、結論37
參考文獻40

表 目 錄
表1 MSCI 台股成份股及權值比重一覽表45
表2 GARCH模型及加入代理變數的α1+β1的統計值47
表3 EGARCH模型及加入代理變數的α1+β1的統計值51
表4 EGARCH 模型加入交易活動的代理變數55

圖 目 錄
表4-1 圖1.3.1研究架構與流程圖9
參考文獻1. 王甡(1995) ,「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,7:1,125-160。2. 王元章(1999) ,「交易量,股價波動性外溢─台灣股市之實證研究」,3. 余尚武(1990),「股價指數期貨之價格發現與領先效果之研究-Nikei 225指數之實證」,證券市場發展季刊,第九卷第三期,29-62.4. 余尚武(1997),「股價指數期貨之價格發現與領先效果之研究」,行政院國家科學委員會專題研究計劃成果報告,(NSC 86-2416-H011-008)5. 余尚武與呂秋香(2000),「股價指數期貨之時間攸關異常效應」,中華管理評論,3:4 51-626. 林華德與王甡(1995),「台灣股市成交量對股價波動的影響1986-1994□GARCH 修正模型的用」,企銀季刊,19:2,40-58。7. 林建甫與張焯然(1994),「ARCH族模式的估計檢定與台灣股票市場的實證」,手稿。8. 林建甫與張焯然(1997),「GARCH模型條件變異數結構變動的檢定」,經濟論文,25:2,201-225.9. 林楚雄、劉維琪與吳欽杉(1997),「台灣股票市場報酬率的期望值與條件波動之關係」,交大管科學報,17:3,103-124.10. 林楚雄、劉維琪與吳欽杉(1999),「台灣股票店頭市場股價報酬率波動行為的研究」,企業管理學報,44,165-192.11. 郭詳兆與李憲杰(1995),「一般化自我迴歸條件異質性變異模型參數之檢定、估計與檢定─以台灣加權指數為例」,成功大學學報,30,53-7112. 陳正佑(2000)「台股指數期貨的價量關係」,國立中山大學,博士論文13. 黃柏農(1995),「多國性股價報酬率的統計特性及星期效果研究及預測─自我相關條件異質性模型的應用」,中國財務學報,2:2,44-76.14. 劉曦敏與葛豐瑞(1996),「台灣股價指數報酬率之線性及非線性變動」,經濟研究,34:1,73-109。15. Baillie, R.T. and DeGennaro, R.P.(1990), “Stock Returns and Volatility”, Journal of Financial and Quantitative Analysis, 25:2 203-21416. Black, F.(1976), “Studies of Stock, Price Volatility Changes,” Proceedings of the American Statistical Association: Business and Economic Statistics Section, 177-181. 17. Bollerslev, T. (1986), "Generalized autoregressive conditional heteroscedasticity," Journal of Econometrics, 31, 307-27. 18. Bollerslev, T. (1987a), "A Conditional Heteroskedastic Time Series Model for Speculative Prices and Rates of Return”, Review of Economics and Statistics, 69, 542-547.19. Bollerslev, T. (1987b), "On the Correlation Structure the Generalized Autoregressive Conditional Heteroskedastic Process”, Journal of Time Series Analysis 9:2, 21-131.20. Bollerslev, T., R. Chou, and K. Kroner (1992), “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence,” Journal of Econometrics 52, 5-59.21. Bollerslev, T., and J.M. Wooldridge (1992), “Quasi-Maximum Likelihood Estimation of Dynamic Models with Time Varying Covariances,” Econometric Reviews 11, 143-172.22. Braun, P. A, D.B. Nelson, and A. M. Sunier (1995), “Good News, Bad News, Volatility, and Betas”, Journal of Finance 50:5, 1575-1603. 23. Campbell, J. and L. Hentschell (1992),”No News is Good News: An Asymmetric Models of Changing Volatility in Stock Returns. ”, Journal of Financial Economics, 31,281-31824. Clark, P.K. (1976), “A Subordinated Stochastic Process Model with Finite Variance for Speculative Price” , Econometrica, Vol.41, No.4, 135-15925. Copeland, T. E., “A Model of Asset Trading Under the Assumption of sequential Information Arrival,” Journal of Finance 31, 1976 1149-1168.26. Christie, A.(1982), “The Stochastic Behavior of Common Stock Variance: Value, Leverage and Interest Rate Effects,” Journal of Financial Economics 10, 407-432.27. Crouch, R. L. 1970b, “The Volume of Transaction and Prices Changes on the New York Stock Exchange”, Financial Analyst Journal, 26, 104-10928. Engle, R. F.(1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation,” Econometrica 50, 987-1008. 29. Engle, R. F, D. Lilien, and R. Robins (1987), “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model,” Econometrica 55, 391-407.30. Engle, R. F, and C. Mustafa(1992), “Implied ARCH Models from Option Prices,” Journal of Econometrics 52, 289-311. 31. Engle, R. F, and V. Ng(1993), “Measuring and Testing the Impact of News on Volatility,” Journal of Finance 45, 1749-1777. 32. Engle, R. F, and T. Bollerslev(1986), “Modeling the Persistence of Conditional Variance,” Econometric Review 5, 1-50. 33. Engle, R. F, D. Lilien, and R. Robins (1987), “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model,” Econometrica 55, 391-407.34. Engle, R. F, V. Ng, and M. Rothschild (1990), “Asset Pricing with a Factor ARCH Covariance Structure:Empirical Estimates for Treasury Bills,” Journal of Econometrics 45, 213-38. 35. Epps, T. W. and M. L. Epps, 1976, “The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implication for the Mixture-of-Distribution Hypothesis”, Econometrica, 44, 305-321 36. Fornari, F. and A. Mele (1995), “Sign- and Volatility-Switching ARCH Models:Theory and Applications to International Stock Markets,” University of Paris X, Working Paper, No. 251. 37. French, R. K., G. W. Schwert, and R. F. Stambaugh(1987), “Expected Stock Returns and Volatility,” Journal of Financial Economics 19, 3-29. 38. Giamiero M. Gallo and Barbara Pacini(2000) “The effects of trading activity on market volatility”, The European Journal of Finance 6. 163-175.39. Granger, C. W, J., and O. Morgenstem, 1963, “Spectral analysis of New York Stock Market Prices”, Kyklos, 16, 1-2740. Hentschel, L. (1995), “All in the Family Nesting Symmetric and Asymmetric GARCH Models,” Journal of Financial Economics 39, 71-104. 41. Higgins, M. L. and A. K. Bera (1992), “A Class of Nonlinear ARCH Models,” International Economic Review 33:1, 137-158. 42. Lamoureux, C. G. and W. D. Lastrapes, (1990), "Heteroscedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, 45, 221-19.43. Nelson, D. (1990), “ARCH Models as Diffusion Approximations,” Journal of Econometrics 45, 7-38. 44. Nelson, D. (1991), “Conditional Heteroskedasticity in Asset Returns:A New Approach,” Econometrica 59, 347-70. 45. Nelson, D.and D. Foster (1994), “Asymptotic Filtering Theory for Univariate ARCH Models,” Econometrica 62, 1-41. 46. Osborne, M. F. M., (1959), “Brownian Motion in the Stock Market”, Operations Research, 17, 145-173.47. Rabemananjara, R. and J. M. Zakolin(1993), “Threshold ARCH Models and Asymmetries in Volatility,” Journal of Applied Econometrics 8, 31-49. 48. Schwert, G. W. (1989), “Why Does Stock Market Volatility Change Over Time ? ” Journal of Finance 44, 1115-1153. 49. Schwert, G. W. (1990), “Stock Volatility and the Crash of 87,” Review of Financial Studies 3, 77-102.50. Ying, C. C., (1966), “Stock Market Prices and Volumes of Sales”, Econometrica, 34, 676-686 51. Najand, M and Yung, K.(1991), “ A GARCH Examination of the relationship between volume and price variability in futures markets”, Journal of Futures Markets, 11:5.465-478.52. Najand, M and Yung, K.(1994), “ Conditional Heteroskedasticity and The Weekend Effect in S&P 500 Index Future”, Journal of Business Finance & Accounting 21:4 603-612.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊