隨著國際間的政治與總體經濟環境相互依存性逐漸地增強，亞洲部分國家的金融市場採漸進式的改革政策，使金融市場邁向自由化與國際化，然而國際金融市場的整合，也引起學界探討國際股市關聯程度的相關議題。然Granger and （1993）曾提及多數的經濟變數具有非線性的性質，Chelley-Steeley（2004）以平滑轉換模型探討新興國家股票市場及已開發國家股票市場間的區域性與全球性的整合現象。平滑轉換模型中考量了參數以漸近式變動的可能性，輔以計量方法予以檢定，並於研究之樣本期間內，估計模型參數是否具有漸進式的改變。
本文引用Chelley-Steeley（2004）的平滑轉換模型，進行東亞三國與美日德間股市非線性關係之研究，且探討股市整合的現象，並以線性模型、非線性原始模型與非線性延伸模型進行比較，實證結果發現，非線性延伸模型相較於線性及非線性原始模型之配適度具有較佳的表現。

With gradually increasing interdependence of international political and economic environments, part of Asian countries' financial markets reform adopted progressive policies towards liberalization and internationalization. Therefore, the integration of international financial markets has attracted a bunch of scholars to investigate related topics of international stock market. Granger and (1993) documented that most of the economic variables have nonlinear characters. Chelley-Steeley (2004) uses smooth transition regression model to explore the financial market integration of regional and global markets among emerging and developed countries. Smooth transition regression model considered the possibility of nonlinear changes in regression parameters.
This paper applies the smooth transition regression model to reinvestigate Chelley-Steeley’s (2004) study of nonlinear relationship of stock markets among some East Asian countries and the United States, Japan and Germany. The main difference of our model and Chelley-Steeley’ model is that we relax his constant market index correlation between two countries by allowing the autoregressive process on market index correlation. Empirical evidences of linear model, original non-linear model and our non-linear extension model show that our non-linear extension model outperformedthe other two models in terms of goodness of fit.

第壹章 緒論 1
第一節 研究動機與目的 1
第二節 研究架構 2
第貳章 文獻回顧 3
第一節 非線性模相關文獻之探討 3
第二節 國際股市關聯性相關文獻之探討 5
第參章 模型介紹與實證研究方法 7
第一節 模型介紹 7
一、 平滑轉換迴歸模型 7
二、 原始模型 11
三、 延伸模型 12
第二節 實證研究方法 15
一、 單根檢定 16
二、 STR模型之建構 17
三、 診斷性分析 22
四、 模型選擇之準則 24
五、 非線性模型殘差之DF-GLS單根檢定 25
第肆章 實證分析與結果 26
第一節 實證資料來源與處理 26
一、 資料來源與樣本期間 26
二、 資料處理 26
第二節 實證結果分析 27
一、 單根檢定 27
二、 非線性模型之估計與檢定 27
三、 模型之參數估計 31
四、 線性模型之診斷性分析 56
五、 非線性模型之診斷性分析 57
六、 配適模型之選擇 63
七、 非線性延伸模型殘差之DF-GLS單根檢定 64
第伍章 結論 66
參考文獻 69

王鶴松 (2005)，「金融危機與金融改革」，第一版，優彩股份有限公司，頁318-340。
林翰基 (2005)，「霸菱金融風暴之省思」，國際金融參考資料，第三十七輯，119-134。
楊奕農 (2005)，「時間序列分析-經濟與財務上之應用」，第一版，雙葉書廊有限公司，台北。
楊淑娟 (2003)，「SARS損害有多少?」，天下雜誌，第275期。
蔡增家 (2005)，「南韓轉型：政黨輪替與政經體制的轉變遷(1993-2003)」，第一版，巨流圖書公司，頁107-128。
劉雨芬摘譯 (2005)，「禽流感疫情對亞洲經濟可能造成之影響」，國際金融參考資料，第五十一輯，126-132。
賴建宇 (2007)，「美國次級房貸風暴 吹垮全球信評 ?」，天下雜誌，第378期。
廖俊男 (2007)，「近期泰國實施資本管制措施及其對金融市場之影響」，國際金融參考資料，第五十三輯，43-54。
「日本經濟復甦腳步緩慢」，經濟日報，第16版，民國84年4月9日。
「波灣戰爭二度爆發，全球經濟恐受衝擊」，經濟日報，第1版，民國92年3月21日。
「泰國政變對經濟有負面影響，可能引發股市全面拋售賣壓」，經濟日報，第10版，民國80年2月25日。
「泰國政變干擾，“2日內可反應完畢”，亞股普遍開低震盪，但跌幅不大 顯示衝擊仍在有限範圍內，但後續仍需密切觀察」，聯合晚報，第14版，民國95年9月20日。
「國際經濟金融日誌」，中央銀行季刊，第二十三卷第三期，211-213。
「意料中的意外 長紅伴隨開戰」，聯合晚報，第11版，民國80年1月17日。
Bacon, D. W. and Watts, D. G. (1971), Estimating the Transition between Two Intersecting Straight Lines, Biometrika, 58, pp. 525-534.
Chelley-Steeley, P. (2004), Equity Market Integration in the Asia-Pacific Region: A Smooth Transition Analysis, International Review of Financial Analysis, 13, pp. 621-632.
Chelley-Steeley, P. L. (2005), Modeling Equity Market Integration Using Smooth Transition Analysis: A Study of Eastern European Stock Markets, Journal of International Money and Finance, 24, pp. 818-831.
Cheung, Y. L. and Mak, S. C. (1992), The International Transmission of Stock Market Fluctuation between the Developed Markets and the Asian-Pacific Markets, Applied Financial Economics, 2(1), pp. 43-47.
Dijk, D. V., Terasvirta, T., and Franses, P. H. (2002), Smooth Transition Autoregressive Models － A survey of Recent Developments, Econometric Reviews, 21(1), 1-47.
Eitrheim, Ø. and , T. (1996), Testing the Adequacy of Smooth Transition Autoregressive Model, Journal of Econometrics, 74, pp. 59-75.
Elliott, G., Rothenberg, T. J. and Stock, J. H. (1996), “Efficient Tests for an Autoregressive Unit Root, Econometrica, 64(4), pp. 813-836.
Engle, R. F. and Granger, C. W. J. Granger, (1987), Co-integration and Error Correction: Representation, Estimation, and Testing, Econometrica, 55(2), pp. 251-276.
Eun, C. S. and Shim, S. (1989), International Transmission of Stock Market Movements, Journal of Financial and Quantitative Analysis, 24(2), pp. 241-256.
Franses, P. H. and van Kijk, D. (2000), Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, Cambridge.
Ghosh, A., R. Saidi and K. H. Johnson (1999), Who Moves The Asia-Pacific Stock Markets-US or Japan? Empirical Evidence Based on The Theory of Cointegration, The Financial Review, 34, pp. 159-170.
Goetzmann, W., and Jorion, P. (1999), Re-emerging Markets, Journal of Financial and Quantitative Analysis, 34, pp. 1-32.
Goldfeld, S. M. and Quandt, R. (1972), Nonlinear Methods in Econometrics, North Holland, Amsterdam.
Granger, C. and Newbold, P. (1974), Spurious Regressions in Econometrics, Journal of Econometrics, 2(2), pp. 111-120.
Granger, C. W. J. and , T. (1993), Modelling Nonlinear Economic Relationships, Oxford University Press, Oxford.
Greenaway, D., Leybourne, S., and Sapsford, D. (1997), Modeling Growth (and Liberalisation) Using Smooth Transitions Analysis, Economic Inquiry, 35, pp. 798-814.
Grubel, H. (1968), Internationally Diversified Portfolios: Welfare Gains and Capital Flows, American Economic Review, 58, pp. 1299-1314.
Hansen, B. E. (2001), The New Econometrics of Structural Change: Dating Breaks in U.S. :abor Productivity, Journal of Economic Perspectives, 15(4), pp.117-128.
Holmes, M. J. and Maghrebi, N. (2004), Asian Real Interest Rates, Nonlinear Dynamics, and International Parity, International Review of Economics and Finance, 13, pp.387-405.
Kanas, A. (1998), Volatility Spillovers Across Equity Markets: European Evidence, Applied Financial Economics, 8(3), pp. 245-256.
Kasa, K. (1992), Common Stochastic Trends in International Stock Markets, Journal of Monetary Economics, 29, pp. 95-124.
Leybourne, S. J., Newbould, P., and Vougas, D. (1998), Unit Roots and Smooth Transitions, Journal of Time Series Analysis, 19, pp. 83-97.
Leybourne, S. J., and Mizen, P. (1999), Understanding the Disinflations in Australia, Canada and New Zealand: Evidence from Smooth Transition Analysis, Journal of International Money and Finance, 18, pp.799-816.
Luukkonen, R., Saikkonen, P. and , T. (1988a), Testing Linearity Against Smooth Transition Autoregressive Models, Biometrika, 75, pp. 491-499.
Maddala, D. S. (1977), Econometrics, McGraw-Hill, New York.
Mishkin, F. S. and Eakins, S. G. (2000), Financial Markets and Institutions, Massachusetts: Addison-Wesley Publishing Company.
, N. and Osborn, D. R. (2000), Business Cycle Nonlinearities in UK Consumption and Production, Journal of Applied Econometrics, 15, pp. 27-43.
Panton, D., Lessin, V. and Joy, O. (1976), Comovements of International Equity Markets: A Taxonomic approach, Journal of financial and Quantitative Analysis, 11, pp. 415-432.
Quandt, R. E. (1958), The Estimation of Parameters of a Linear Regression System Obeying Two Separate Regimes, Journal of the American Statistical Association, 53, pp. 873-880.
Ripley, D. (1973), Systematic Elements in the Linkage of National Stock Market Indices, Review of Economics and Statistics, 55, pp. 356-361.
Sarantis, N. (1999), Modelling Nonlinearities in Effective Exchange Rates, Journal of International Money and Finance, 18, pp.27-45.
Sarantis, N. (2001), Nonlinearities, Cyclical Behaviour and Predictability in Stock Markets: International Evidence, International Journal of Forecasting, 17, pp.459-482.
, T. (1994), Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models, Journal of the American Statistical Association, 89, pp. 208-218.
, T. (1998), Modeling Economic Relationships with Smooth Transition Regressions, in A, Ullah and D. E. Giles (eds.), Handbook of Applied Economic Statistics, Dekker, New York, pp. 507-552.
, T. (2004), Smooth Transition Regression Modeling, in H. and M. (eds), Applied Time Series Econometrics, Cambridge University Press, Cambridge.
, T. and Anderson, H. M. (1992), Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models, Journal of Applied Econometrics, 7, pp. 119-136.
Tiao, G. C., and Tsay, R. S. (1994), Some Advances in Non-linear and Adaptive Modelling in Time-Series, Journal of Forecasting, 13, pp. 109-131.
Tong, H. (1978), On a Threshold Model, in C.H Chen (eds), Pattern Recognition and Signal Processing, Amsterdam: Sijthoff and Noordhoff, pp. 101-141.
Tong, H. (1990), Non-Linear Time Series. A Dynamical System Approach, Oxford University Press, Oxford.
Tong, H. and Lim K. S. (1980), Threshold Autoregressions, Limit Cycles, and Data, Journal of the Royal Statistical Society, pp. 245-292.
van Dijk, D. and Franses, P. H. (1999), Modeling Multiple Regimes in the Business Cycle, Macroeconomic Dynamics, 3, pp. 311-340.