Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/27668
標題: 英、美、日股票市場波動性之分析
Volatility of U.K., U.S. and Japan Stock Markets
作者: 陳姿惠
Chen, Tzu-Hui
關鍵字: EGARCH model
EGARCH模型
Cointegration
VECM
共整合
向量誤差修正模型
出版社: 應用經濟學系所
引用: 參考文獻 一、國內文獻 [1] 劉健欣(1999)。台灣股市與美國股市關連性之實證研究。淡江大學管理科學研究所碩士論文。 [2] 邱建良等(2000),「國際股票市場共整合與動態關聯性之實證研究」,企銀季刊,23(4),155-177 頁。 [3] 蔡明修(2001),「亞洲股市互動關係與波動影響因素之探討」,國立台灣科 技大學企業管理系碩士論文 [4] 蘇慶富(2004),「國際股票市場波動性與共整合之探討」,國立交通大學 統計學研究所碩士論文 [5] 楊奕農(2005)。時間序列分析。臺北市:雙葉書廊。 [6] 張簡士煌(2005),「台灣股市與國際股市關聯性之研究」,朝陽科技大學企業管理系碩士論文 [7] 李育菁(2005),「台北市房地產投資風險波動性研究-GARCH模型之應用」 ,國立中山大學財務管理學系研究所碩士論文 [8] 謝俊宏(2006),「台灣股市波動性長時間之探討」,國立中興大學財務金融 系碩士論文 [9] 吳其定(2007),「滬、港、台、美四地股市指數與區域經濟成長關聯性及共整合之研究─以中、港CEPA 實施前後期為例」,國立中央大學財務金融研究所碩士論文 [10] 鍾孟桓(2008),「國際油輪運費市場資訊不對稱性與槓桿效果分析」,國立成功大學交通管理研究所碩士論文 [11] 張世芳(2010),「自然旅遊需求預測-以日月潭國家風景區為例」,國立中興大學應用經濟學系碩士論文 二、國外文獻 [1] Akaike, H. (1974), A new look at the statistical model identification, IEEE Transactions on Automatic Control, AC-19, pp 716-723. [2] Akgiray ,V (1989),「Conditional Heteroscedasticity in the Series of Stock Return Evidence and Forecasts.」,Journal of Business, 62, 55-80 [3] Bollerslev, T. (1986), “Generalized Autoregressive Condition Heteroskedasticity,” Journal of Econometrics 31, pp 307-327. [4] 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, Vol. 74, No. 366, pp 427-431. [5] Engle, R. F. (1982), “Autoregressive Conditional heteroscedasticity with Estimates of the Variance of United Kingdom Inflation,” Econometrica, Vol. 50, No. 4, pp 987-1007. [6] Engle, R. F. and Granger, C. W. J. (1987), “Cointegration and Error Correction: Representation, Estimation, and Testing,” Econometrica, Vol. 55, No. 2, pp 251-276 [7] Liljeblom, Eva and Marianne Stenius(1997),「Macroeconomic volatility and stock market volatility: empirical evidence on Finnish data.」,Applied Financial Economic, Vol.7,pp.419-426 [8] Nelson, D. B. (1991), “Conditional Heteroskedasticity in Asset Returns : A new Approach,” Econometrica 59, pp 347-370. [9] Nelson ,D B(1989),「Modelling Stock Market Volatility Changes.」,ASA 1989 Proceedings of the Business and Economics Statistics Section, pp.93-98 [10] Reena Aggarwal, Carla Inclan, and Ricardo Leal (1999), “Volatility in Emerging Stock Markets”, Journal of Financial and Quantitative Analysis, Vol.34, No.1, pp.33-55. [11] Schwert, G. W. (1989), “Why does stock market volatility change over time? ”, Journal of Finance, Vol.44, pp.1115-53. [12] Schwert, G. W. (1989), “Margin requirements and stock volatility”,Journal of Finance Services Research, pp.153-64. [13] Pan, M. S. et al (2002), “Volatility and Trading Demands in Stock Index Futures,” Journal of Futures Markets, Vol. 23, No. 4, pp 399-414. [14] Tsay, R. S. (1987), “Conditional Heteroscedastic Time Series Models,” Journal of the American Statictical Association, Vol. 82, No. 398, pp 590-604. [15] Tsay, R. S. (2002), Analysis of Financial Time Series, Wiley.
摘要: 本研究針對英、美、日三國股票市場分析其波動性與相關性。資料使用2009年到2010年的日資料,以倫敦時報 Ftse 100 指數 (London - Ftse 100 Index)、紐約道瓊工業平均指數(New York - The Dow Jones Industrial Average)與東京日經道瓊平均指數。波動性方面,利用ARMA-EGARCH(1,1)模型,更能有效的捕捉市場波動的不對稱性。相關性方面,運用共整合和向量誤差修正模型(VECM),並探討其存在時之共整合模型及其相關性。 由實證結果可發現:(1) 三個國家股市報酬皆存在著波動不對稱與槓桿效果的情形。(2) 根據Johansen最大概似共整合檢定結果得知,三個國家股市於長期間存在均衡共移之關係。(3) 各國的EGARCH模型中,可知計算出來該國的波動性,能解釋的只有該國的變異數與誤差項;在VECM模型卻可以提供除了該國自身的落後期數影響外,還有其他兩國的落後期數也考量進來模型中,這是EGARCH模型所沒解釋到的部分,VECM模型更清楚解釋影響該國的股價指數波動,使本研究更了解英國、美國、日本三國的股價報酬波動性的完整。
This study use Britain, America and Japan to analyze the stock markets' volatility and correlation. Daily data of the Times of London Ftse 100 Index (London - Ftse 100 Index), New York, the Dow Jones Industrial Average Index (New York - The Dow Jones Industrial Average) and the Tokyo Nikkei Dow Jones average were adopted from 2009 to 2010 and used the ARMA-EGARCH (1,1) model to capture more effectively market volatility asymmetry. Cointegration and vector error correction model (VECM) were used to explore the presence of co-integration model and its relevance. The empirical results can be found: (1) there are fluctuations in the stock market returns and the leverage effect asymmetry of the situation in all of the three countries. (2) According to the Johansen maximum likelihood cointegration test results, there is a long period of stock market equilibrium at a total shift of the relationship among the three countries.(3) Countries EGARCH model, we can see the calculated volatility, can explain only the variance of the error term; in the VECM model, it can provide in addition to the impact of their own behind the number of installments, there are other countries considerations also come in behind the phases of the model, which is not explained to the EGARCH model part, VECM model to explain more clearly the impact of the country''s stock index volatility, making the study more about the UK, U.S., Japan three of the volatility of stock returns integrity.
URI: http://hdl.handle.net/11455/27668
其他識別: U0005-2906201110134800
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2906201110134800
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