本篇研究主要的目的是分別探討台灣、南韓、新加坡、香港、日本、中國與美國共七國股價指數報酬的非線性動態調整行為。使用本身股價指數報酬之落後期為解釋變數，並且應用自我迴歸平滑轉換模型來描述股價指數報酬非線性調整的部分。採用 Teräsvirta（1992）所提出之自我迴歸平滑轉換模型下，實證結果發現：
首先，使用本身股價指數報酬落後期為解釋變數之下，不同國家，各個股價指數之解釋變數之落後期不全相同。再者，所研究的七國股價指數報酬均呈現非線性調整，並且每一個股價指數報酬都適合使用logistic型態之轉換型態說明非線性調整行為。所有股價指數非線性調整非但存在門檻，且都存在雙門檻，並非單純的單門檻調整。在越過各個不同的門檻值之後，股價報酬序列有著不同的動態調整行為。所有國家中，上海綜合指數報酬之轉換速度最快，新加坡海峽時報指數報酬之轉換速度最慢。最後，門檻差距最大的為上海綜合指數報酬，最小的為台灣加權股價指數報酬。

This paper examines the nonlinear dynamics in stock returns which includes Taiwan、 South Korea、Singapore、Honk Kong、Japan、United States of America and China by using Smooth Transition Autoregressive Model (STAR) and using the lag of stock return as the transition variable. 
Under the STAR model made by Teräsvirta (1992), we have several results. First, the lags of stocks return are different in each country. Meanwhile, all countries have two thresholds and three regimes. Moreover, all stock returns can be explained by Quadratic Logistic Smooth Transition Autoregressive Model (QLSTAR). By crossing the thresholds fastest and smoothest, the stock returns will have different nonlinear dynamics behaviors. Furthermore, the faster and smoothness regime change is the Shanghai Composite Index; the slowest is the Straits Times Index. Finally, the Shanghai Composite Index has the largest distance between two thresholds; the TSEC weighted index has the smallest distance between the two thresholds.

目錄
第一章 緒論
第一節 研究動機與目的的..................................................................................1
第二節 研究架構與流程......................................................................................3
第二章 文獻回顧
第一節 使用STAR模型研究股票報酬的相關文獻...........................................5    
第二節 應用非線性方法分析股票報酬相關文獻..............................................7
第三節 應用非線性模型研究其他標的之文獻................................................10
第三章 研究方法與模型建立
第一節 單根檢定................................................................................................12
第二節 線性與非線性檢定................................................................................16
第三節 模型選擇................................................................................................18
第四章 實證分析
第一節 資料來源與處理....................................................................................22
第二節 各國股價與股價報酬基本統計量........................................................23
第三節 單根檢定................................................................................................28
第四節 線性模型................................................................................................30
第五節 非線性檢定與非線性模型選擇............................................................37
第六節 平滑轉換自我迴歸模型........................................................................49
第五章 結論................................................................................................................70
參考文獻......................................................................................................................72



圖次
圖1-1：研究流程圖.........................................................................................................4
圖4-1：台灣加權股價指數走勢圖...............................................................................25
圖4-2：韓國綜合股價指數走勢圖...............................................................................25
圖4-3：新加坡海峽時報指數走勢圖...........................................................................25
圖4-4： 香港恆生指數走勢圖....................................................................................25
圖4-5：日經225指數走勢圖.........................................................................................26
圖4-6：標準普爾500指數走勢圖.................................................................................26
圖4-7：上海綜合股價指數走勢圖...............................................................................26
圖4-8：台灣加權股價指數報酬走勢圖.......................................................................27
圖4-9：韓國綜合股價指數報酬走勢圖.......................................................................27
圖4-10：新加坡海峽時報指數報酬走勢圖.................................................................27
圖4-11：香港恆生指數報酬走勢圖.............................................................................27
圖4-12：日經225指數報酬走勢圖...............................................................................28
圖4-13：標準普爾500指數報酬走勢圖.......................................................................28
圖4-14：上海綜合股價指數走勢圖............................................................................28
圖4-15：台灣加權股價指數報酬轉換函數值時間走勢.............................................52
圖4-16：台灣加權股價指數報酬之logistic轉換函數.................................................52
圖4-17：韓國綜合股價指數報酬轉換函數值時間走勢.............................................54
圖4-18：韓國綜合股價指數報酬之logistic轉換函數.................................................54
圖4-19：新加坡海峽時報指數報酬轉換函數值時間走勢.........................................57
圖4-20：新加坡海峽時報指數報酬之logistic轉換函數.............................................57
圖4-21：香港恆生指數報酬轉換函數值時間走勢.....................................................60
圖4-22：香港恆生指數報酬之logistic轉換函數.........................................................60
圖4-23：日經225指數報酬轉換函數值時間走勢.......................................................62
圖4-24：日經225指數報酬之logistic轉換函數...........................................................62
圖4-25：標準普爾500股價指數報酬轉換函數值時間走勢.......................................65
圖4-26：標準普爾500指數報酬之logistic轉換函數...................................................65
圖4-27：上海綜合股價指數報酬轉換函數值時間走勢.............................................68
圖4-28：上海綜合股價股價指數報酬之logistic轉換函數.........................................68
















表次
表4-1：股價指數基本統計量.......................................................................................24
表4-2：股價指數報酬基本統計量...............................................................................24
表4-3：單根檢定（1）........... .........................................................................................29
表4-4：單根檢定（2）.....................................................................................................29
表4-5：各國自我迴歸模型之落後期..........................................................................30
表4-6：台灣加權股價指數報酬線性模型估計...........................................................31
表4-7：韓國綜合股價指數報酬線性模型估計...........................................................32
表4-8：新加坡海峽時報指數報酬線性模型估計.......................................................33
表4-9：香港恆生指數報酬線性模型估計...................................................................34
表4-10：日經225指數報酬線性模型估計...................................................................35
表4-11：標準普爾500指數報酬線性模型估計...........................................................36
表4-12：上海綜合股價指數報酬線性模型估計.........................................................37
表4-13：非線性模型選擇.............................................................................................38
表4-14：台灣加權股價指數報酬之非線性檢定.........................................................39
表4-15：韓國綜合股價指數報酬之非線性檢定.........................................................40
表4-16：新加坡海峽時報指數報酬之非線性檢定.....................................................42
表4-17：香港恆生指數報酬之非線性檢定.................................................................43
表4-18：日經225指數報酬之非線性檢定...................................................................45
表4-19：標準普爾500指數報酬之非線性檢定.......................................................... 46
表4-20：上海綜合股價指數報酬之非線性檢定.........................................................48
表4-21：台灣加權股價指數報酬QLSTAR模型估計結果.........................................50
表4-22：韓國綜合股價指數報酬QLSTAR模型估計結果.........................................53
表4-23：新加坡海峽時報指數報酬QLSTAR模型估計結果.....................................55
表4-24：香港恆生指數報酬QLSTAR模型估計結果.................................................58
表4-25：日經225指數報酬QLSTAR模型估計結果...................................................61
表4-26：標準普爾500指數報酬QLSTAR模型估計結果.........................................63
表4-27：上海綜合股價指數指數報酬QLSTAR模型估計結果.................................66
表4-28：台灣、南韓、新加坡、香港估計結果...............................................................69
表4-29：日本、美國、中國估計結果.............................................................................69

參考文獻

一、中文部分

吳慶忠（2005），金融與總體經濟變數對股票報酬之影響－Linear與STARX模型之比較分析，中原大學國際貿易學系碩士論文

吳若瑋（2005），以STAR模型探討歐洲工業國家之實質利率平價說，國立中山大學經濟學研究所碩士論文

許琇庭（2005），台灣利率期限結構之非線性平滑轉換誤差修正模型實證研究，淡江大學財務金融學所碩士論文。

二、英文部分

Ahmed, E., J. B. Rosser Jr. and J. Y. Uppal（1999）.”Evidence of nonlinear speculative bubbles in Pacific-Rim stock markets,“ Quarterly Review of Economics and Finance, 39, 21-36.

Aminian, F. , E. D. Suarez , M. Aminian and D. T. Walz（2006）.” Forecasting Economic Data with Neural Networks” Computational Economics, 88, 71-88.

Bonilla, C . A. , R. Romero-Meza and M. J. Hinich（2006）.” Episodic nonlinearity in Latin American stock market indices,” Applied Economics Letters, 13, 195-204.
 
Campbell, J. Y. and Shiller R. J.（1998）.” Stock prices, earnings, and expected dividends,” Journal of Finance, 43, 661-676.

Clements, M. P , P. H. Franses and N. R. Swanson （2004）. “Forecasting economic and financial time series with non-linear models,” International Journal of Forecasting, 20, 169-183.

Kanas, A.（2001）.” Neural network linear forecasts for stock returns,” International Journal of Finance & Economics, 6, 245-254.

Kanas, A.（2003） .“ Non-linear Forecasts of Stock Returns,” Journal of Forecasting, 22, 299-315.

Arshanapalli, B . , J. Doukas and L. H. P. Lang（1995）. ” Pre and post-October 1987 stock market linkages between U.S. and Asian markets,” Pacific-Basin Finance Journal, 3, 57-73.

Baharumshah, A. Z. and V. Khim-Sen Liew（2006）. ” Forecasting Performance of Exponential Smooth Transition Autoregressive Exchange Rate Models,” Open Economies Review, 17, 235-251.

Balke, N. S. and T. B. Fomby（1997）. ” Threshold cointegration,” International Economic Review, 38, 627-645.


Banaian, K. and M. C. Lo,（2006）.” Indexing Speculative Pressure on an Exchange Rate Regime: A Case Study of Macedonia,” Studies in Nonlinear Dynamics and Econometrics, 10.

Basci, E. and M. Caner（2005）.” Are Real Exchange Rates Nonlinear or Nonstationary? Evidence from a New Threshold Unit Root Test,” Studies in Nonlinear Dynamics and Econometrics , 9.

Bradley,M. D. and D. W. Jansen（2004）.” Forecasting with a nonlinear dynamic model of stock returns and industrial production,” International Journal of Forecasting, 20, 321-343.

Chung, S. K. （2006）.” The out-of-sample forecasts of nonlinear long-memory models of the real exchange rate,” International Journal of Finance & Economics, 11, 355-370.

Chyi, Yih-Luan（1997）.” Nonlinear dynamics and daily stock returns on the Taiwan Stock Exchange,” Applied Financial Economic, 7, 619-634.

Constantinou, E . , R. Georgiades ,  A. Kazandjian and G. P. Kouretas（2006）.” Regime switching and artificial neural network forecasting of the Cyprus Stock Exchange daily returns,” International Journal of Finance & Economics, 11, 373-383.

Cowan, A. R. and A. M. A. Sergeant（2001）.” Interacting biases, non-normal return distributions and the performance of tests for long-horizon event studies,” Journal of Banking & Finance, 25, 741-765.

Eitrheim, O. and Teräsvirta, T.（1996）.“ Testing the adequacy of smooth transition autoregressive models,” Journal of Econometrics, 74, 59-75.

Enders, W. and C. W. J. Granger（1998）.” Unit-root tests and asymmetric adjustment with an example using the term,” Journal of Business & Economic Statistics, 16, 304-311.

Enders, W. and P. L. Siklos（2001）.“ Cointegration and threshold adjustment,” Journal of Business & Economic Statistics, 19, 166-176.

Erlat, H.（2004）.“ Unit roots of nonlinear stationarity in Turkish real exchange rates,“Applied Economics Letters, 11, 645-650.

Gabriel Perez-Quiros, and A. Timmermann（2000）.” Firm Size and Cyclical Variations in Stock Returns,” The Journal of Finance, 55, 1229-1262.

Granger, C. W. J., & Teräsvirta, T. (1993).“ Modelling nonlinear economic relationships,” Oxford : Oxford University Press.

Guidolin, M. and A. Timmermann（2006）.” An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns,” Journal of Applied Econometrics, 21, 1-22.

Guidolin, M. and A. Timmermann（2003）.” Recursive modeling of nonlinear dynamics in UK stock returns,” The Manchester School, 71, 381-395.

Heimonen, K.（2006）.” Nonlinear adjustment in PPP--evidence from threshold cointegration,” Empirical Economics, 31, 479-495.

Holmes, M. J.（2004）.” Is There Non-linear Real Exchange Rate Adjustment for the Asian Economies?,” ASEAN Economic Bulletin, 21, 198-212.

Kanas , A. and A. Yannopoulos（2001）.” Comparing linear and nonlinear forecasts for stock returns,” International Review of Economics & Finance, 10, 383-398.

Kanas , A. and A. Yannopoulos（2003）.” Non-linear Forecasts of Stock Returns,” Journal of Forecasting, 22, 299-315.

Kryzanowski, L. , Galler, M. and Wright, D. W. （1993）.” Using artificial neural networks to pick stocks,” Financial Analysts Journal, 49, 21-27.

Lanne, M. （2006）.“ Nonlinear dynamics of interest rate and inflation,” Journal of Applied Econometrics, 21, 1157-1168.

Lee, H. J.（2004）.“Essays on long-horizon stock return prediction regression,” University of Washington Graduate School.


Liew,K. S. , A. Z. Baharumshah and K.P. Lim（2006）.” Nonlinear adjustment of real exchange rates towards purchasing power parity and the Asian Financial Crisis,” International Journal of Business and Society, 6, 122-140.

Martens, M. , P. Kofman and T. C. F. Vorst（1998）.“ A threshold error correction model for intraday futures and index returns,” Jouornal Applied Economics, 13, 245-263.

McMillan, D. G .（2002）.” Non-linear Predictability of UK Stock Market Returns,” Oxford Bulletin of Economics and Statistics,65, 557-579.

McMillan, D. G .（2001）.” Nonlinear predictability of stock market returns : Evidence from nonparametric and threshold models, “ International Review of Economics & Finance,10, 353-368.

McMillan, D. G .（2005）.” Non-linear dynamics in international stock market returns,” Review of Financial Economics, 14, 81-91.

McMillan, D. G .（2005）.” Smooth-transition error-correction in exchange rates,” North American Journal of Economics and Finance, 16, 217-232.

McMillan, D. G .（2004）.” Non-linear Error Correction Evidence for UK Interest Rates,” The Manchester School, 72, 626-640.

Milas, C. and  G . Legrenzi （2006）.” Non-linear Real Exchange Rate Effects in the UK Labour Market,” Studies in Nonlinear Dynamics and Econometrics,10, 1-33.

Nam, K. , C. S. Pyun and S. L. Avard（2001）.” Asymmetric reverting behavior of short-horizon stock returns : An evidence of stock market overreaction,” Journal of Banking & Finance, 25, 807-824.

Narayan, P. K .（2005）.” Are the Australian and New Zealand stock prices nonlinear with a unit root, “ Applied Economics, 37, 2161-2166.

Nenortaite, J. and R. Simutis（2006）.” Development and Evaluation of Decision-Making Model for Stock Markets,” Journal of Global Optimization, 36, 1-19.

Obstfeld, M. and A. M. Taylor（1997）.” Nonlinear Aspects of Goods-Market Arbitrage and Adjustment: Heckscher's Commodity Points Revisited,” Journal of the Japanese and International Economics, 11, 441-479.

Pandey , V. , T. Kohers and G .Kohers.（1998）” Deterministic nonlinearity in the stock returns of major European equity markets and the United States,” The Financial Review, 33, 45-64.

Pedro. J. F de Lima（1998）.” Nonlinearities and Nonstationarities in Stock Returns,” Journal of Business & Economic Statistics, 16, 227-236.

Qi,M.（1997）.” Nonlinear predictability of stock returns using financial and economic variables,” Journal of Business & Economic Statistics, 17, 419-429.

Racine, J（2001）. “On the nonlinear predictability of stock returns using financial and economic variables,” Journal of Business & Economic Statistics, 19, 380-382.

Rapach, D. E. and M. E. Wohar（2006）.” The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior,” International Journal of Forecasting, 22, 341-361.

Scheinkman, J. A .and L . Blake（1989）.” Nonlinear Dynamics and Stock Returns,” The Journal of Business, 62, 311-337.

Sierimo, C. Tuula and D. Soc. Sc.（2002）” Testing the efficient market hypothesis of the Helsinki Stock Exchange,” University of Colorado.
 
Sollis, R. and M. E. Wohar（2006）.” The real exchange rate-real interest rate relation: evidence from tests for symmetric and asymmetric thresh old cointegration,” International journal of finance and economics, 11, 139-153.

Taylor , N.（2004）.” A New Econometric Model of Index Arbitrage,” European Financial Management, 13, 159-199.

Teräsvirta, T. and H. M. Anderson（1992）.“Characterising nonlinearities in business cycles using smooth transition autoregressive models,” Journal of Applied Econometrics, 7, 119–136.
.
Teräsvirta, T. （1994）.”Specification, estimation, and evaluation of smooth transition autoregressive models,” Journal of the American Statistical Association, 89, 208-218.

Treepongkaruna, S. and S. Gray（2006）.” Are there nonlinearities in short-term interest rates?,” Accounting and Finance, 46, 149-167.

Tsoukalas, D. , M. Darayseh and E. Waples（2003）.” Nonlinear dynamics in multinational financial data,” Managerial Finance, 29, 76-83.

Urrutia, J. L. , J. Vu , P. Gronewoller and M. Hoque（2002）.” Nonlinearity and low deterministic chaotic behavior in insurance portfolio stock returns,” Journal of Risk and Insurance, 69, 537-554.