臺灣博碩士論文加值系統

本文有別於以往文獻在探討國際股市間波動外溢效果時，僅止於一階與二階動差的傳導效果，擬將台灣與美國股市間訊息傳遞效果的議題，延伸擴展至偏態的傳遞效果，探討美國對台灣股市之影響及股票市場間之國際傳導，擬使用單變量GARCHS模型(Harvey and Siddique, 1999; León et al., 2005)搭配兩階段的估計方法，探討於1998年1月5日至2006年12月29日，美國與台灣股價指數間之報酬率、波動性與偏態之外溢效果，以提供投資者進行國際投資組合及政府制定未來經濟政策之參考。
研究結果發現美股主要指數對台灣加權股價指數無論以日資料或是週資料估計，皆存在顯著的報酬率與波動外溢效果，此結論與以往文獻相同。而在偏態係數的外溢效果方面，本文僅發現以日資料估計時，史坦普500指數與那斯達克對台股指數存在偏態係數外溢效果，此結果對於具有偏態偏好的投資者或是以報酬率、變異數與偏態係數作投資組合選擇的投資者具有重要的實際意義。

Previous studies of international information transmission effect only focused on the first and second moment spillover effects. This study extends this issue to examine the third moment spillover effect among Taiwan and U.S. stock markets. The univariate GARCHS model (Harvey and Siddique, 1999; León et al., 2005) with two-step estimation procedure is adopted to investigate the mean, variance and skewness spillover effects during the sample period of Jan 5, 1998 to Dec 29, 2006 in order to provide some implications for the international investors and government economic policy.
The empirical results indicate that the U.S. stock markets have significant mean and volatility spillover effects to Taiwan stock markets when estimating with daily and weekly data, which is consistent with previous studies. As for the skewness spillover effect, we find that only S&P 500 and Nasdaq have skewness spillover effect to Taiwan stock market when estimating with daily data. The evidences reported here have important practical meanings to skewness-preferred investors and those who make portfolio selection with mean, variance and skewness.

第一章 緒論…………………………………………………………1
第一節 研究背景與動機……………………………………………1
第二節 研究目的……………………………………………………3
第三節 研究架構……………………………………………………4
第四節 研究流程圖…………………………………………………5
第二章 文獻回顧……………………………………………………6
第一節 國外文獻……………………………………………………6
第二節 國內文獻………………………………………………… 19
第三章 研究方法………………………………………………… 32
第一節 單根檢定………………………………………………… 32
第二節 ARCH效果檢定…………………………………………… 34
第三節 條件變異數不對稱檢定………………………………… 36
第四節 AR-GJR-GARCHS模型………………………………………38
第四章 實證結果分析…………………………………………… 41
第一節 研究對象、研究期間與資料處理……………………… 41
第二節 基本統計量分析………………………………………… 42
第三節 單根檢定………………………………………………… 43
第四節 ARCH效果檢定…………………………………………… 45
第五節 條件變異數不對稱檢定………………………………… 46
第六節 AR-GJR-GARCHS模型之估計結果…………………………47
第五章 結論與研究建議 …………………………………………52
第一節 結論……………………………………………………… 53
第二節 研究建議………………………………………………… 53
參考文獻……………………………………………………………… 54
一、國外文獻……… …………………………………………………55
二、國內文獻… ………………………………………………………60

表目錄
【表2-1-1】國外文獻整理……………………………………………14
【表2-2-1】國內文獻整理……………………………………………26
【表4-2-1】股價日報酬率之基本統計量……………………………42
【表4-3-1】股價原始序列之單根檢定(水準項)……………………45
【表4-3-2】股價日報酬率之單根檢定(差分項)……………………45
【表4-4-1】診斷性分析………………………………………………46
【表4-5-1】條件變異數不對稱檢定…………………………………47
【表4-6-1】AR-GJR-GARCHS模型之估計結果……………………… 48
【表4-6-2】美股各指數對台灣加權股價指數之外溢效果(日資料)50
【表4-6-3】美股各指數對台灣加權股價指數之外溢效果(週資料)51

圖目錄
【圖1.4】論文架構圖…………………………………………5
【圖4-2-1】股價指數走勢圖…………………………………………43
【圖4-2-2】股價報酬率走勢圖………………………………………43

一、國外文獻
1. Arditti, F. D. (1967), “Risk and the required return on equity,” Journal of Finance, 22(1), 19-36.
2. Becker, K. G., J. E. Finnerty and A. L. Tucker (1992), “The intraday interdependence structure between U.S. and Japanese equity markets,” Journal of Financial Research, 15, 27-37.
3. Beedles, W. L. and M. A. Simkowitz (1980), “Morphology of asset asymmetry,” Journal of Business Research, 8,457-468.
4. Bollerslev, T. (1990), “Modeling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH approach,” Review of Economics and Statistics, 72, 498-505.
5. Bollerslev, T. and J. M. Wooldridge (1992), “Quasi-maximum likelihood estimation and inference in dynamic models with time varying covariances,” Econometric Review, 11, 143-172.
6. Booth, G. G., T. Martikainen and Y. Tse (1997), “Price and volatility spillovers in Scandinavian stock markets,” Journal of Banking & Finance, 21, 811-823.
7. Campbell, J. Y. (1987), “Stock returns and the term structure,” Journal of Financial Economics, 18, 373-399.
8. Campbell, J. Y. and L. Hentschel (1992), “No news is good news: an asymmetric model of changing volatility in stock returns,” Journal of Financial Economics, 31, 281-318.
9. Cecchetti, S. G., R. E. Cumby and S. Figlewski (1988), “Estimation of the optimal futures hedge,” Review of Economics and Statisitcs, 70, 623-630.
10. Chen, H., B. J. Lobo and W. K. Wong (2006), “Links between the Indian, U.S. and Chinese Stock Markets,” Working paper of department of Economics, National University of Singapore.
11. Cheung, Y. L. and S. C. Mak (1992), “The international transmission of stock market fluctuation between the developed markets and the Asian-Pacific markets,” Applied Financial Economics, 2, 43-47.
12. Chou, R. J., L. Li and C. S. Wu (1998), “Modeling Taiwan stock market and international linkages,” NTU International Conference on Finance.
13. Chowdhury, A. R. (1994), “Stock market interdependencies: evidence from the Asian NIEs,” Journal of Macroeconomics, 16, 629-651.
14. Chunhachinda, P., K. Dandapani, S. Hamid and A. J. Prakash (1997), “Portfolio selection and skewness: evidence from international stock markets,” Journal of Banking and Finance, 21, 143-167.
15. Colm, K. and A. J. Patton (2000), “Multivariate GARCH modeling of exchange volatility transmission in the European monetary system,” Financial Review, 41, 29-48.
16. Corrado, C. and T. Su (1996), “Skewness and Kurtosis in S&P 500 index returns implied by option prices,” Journal of Financial Research, 19, 175-192.
17. Darbar, S. M. and P. Deb (1997), “Co-movements in international equity markets,” Journal of Financial Research, 3, 305-322
18. DeFusco, R. A., G. V. Karels and K. Muralidhar (1996), “Skewness persistence in US common stock returns: results from bootstrapping tests,” Journal of Business Banking & Accounting, 23, 1183-1195.
19. Dickey, D.A. and W. A. Fuller (1981), “Likelihood ratio statistic for autoregressive time series with a unit root,” Econometrica, 49, 143-159.
20. Ederington, L. H. (1979), “The hedging performance of the new futures markets,” Journal of Finance, 34, 157-170.
21. Engle, R. F. (1982), “Autoregressive conditional heteroscedasticity with estimates of the variance of UK inflation,” Econometrica, 50, 987-1008.
22. Engle, R. F. and B. S. Yoo (1987), “Forecasting and testing in co-integrated Systems,” Journal of Econometrics, 35, 143-159.
23. Engle, R. F. and V. K. Ng (1993), “Measuring and testing the impact of news on. volatility,” Journal of Finance, 48, 1749-1778.
24. Eun, C. S. and S. Shim (1989), “International transmission of stock market movements,” Journal of Financial and Quantitative Analysis, 24(2), 241-256.
25. Fama, E. F. and K. R., French (1996), “Multifactor explanations of asset pricing anomalies,” Journal of Finance, 51, 55-84.
26. Fisher, K. P. and A. P. Palasvirta (1990), “High road to a global marketplace: the international transmission of stock market fluctuations,” Financial Review, 25(3), 371-394.
27. Friend, I. and R. Westerfield (1980), “Co-skewness and capital asset pricing,” Journal of Finance, 35, 897-919.
28. Gilbert, S., S. K. Jones and G. H. Morris (2006), “The impact of skewness in the hedging decision,” Journal of Futures Markets, 26(5), 503-520.
29. Glosten, L. R., R. Jagannathan and D. E. Runkle, (1993), “On the relation between expected value and the volatility of the nominal excess return on stocks,” Journal of Finance, 48, 1779-1801.
30. Hamao, Y. R., R. W. Masulis and V. K. Ng (1990), “Correlation in price changes and volatility across international stock markets,” Review of Financial Studies, 3, 281-307.
31. Hansen, B. E. (1994), “Autoregressive conditional density estimation,” International Economic Review, 35, 705-730.
32. Harvey, C. R. (1989), “Time-varying conditional covariances in tests of asset pricing models,” Journal of Financial Economics, 24, 289-317.
33. Harvey, C. R. and A. Siddique (1999), “Autoregressive conditional skewness,” Journal of Financial and Quantitative Analysis, 34(4), 465-487.
34. Hashmi, A. R. and A. S. Tay (2007), “Global regional sources of risk in equity markets: evidence from factor models with time-varying conditional skewness,” Journal of International Money and Finance, 26, 403-453.
35. Hentschel, L. (1995), “All in the Family: nesting symmetric and asymmetric GARCH models,” Journal of Financial Economics, 39, 71-104.
36. Howard, C. T. and L. J. D’Antonio (1984), “A risk-return measure of hedging effectiveness,” Journal of Financial and Quantitative Analysis, 19, 101-112.
37. Hsin, C. W., J. Kuo and C. F. Lee (1994), “A new measure to compare the hedging effectiveness of foreign currency futures versus options,” Journal of Futures Markets, 14, 685-707.
38. Ibbotson, R. G. (1975), “Price performance of common stock new issues,” Journal of Financial Economics, 2(3), 235-272.
39. In, F., S. Kim, J. H. Yoon and C. Viney (2001), “Dynamic interdependence and volatility transmission of Asian stock markets: evidence from the Asian crisis,” International Review of Financial Analysis, 10, 87-96.
40. Jarrow, R. and A. Rudd (1982), “Approximate option valuation for arbitrary stochastic processes,” Journal of Financial Economics, 10, 347-369.
41. Jarque, C. M. and A. K. Bera (1987), “A test for normality of observations and regression residuals,” International Statistical Review, 55, 163-172.
42. Jeong, J. G. (1999), “Cross-border transmission of stock price volatility: evidence from the overlapping trading hours,” Global Finance Journal, 10, 53-70.
43. Kanas, A. (1998), “Volatility spillovers across equity market: European evidence,” Applied Financial Economics, 8, 245-256.
44. Kearney, C. (2000), “The determination and international transmission of stock market volatility,” Global Finance Journal, 31-52.
45. Kim, H. L., O. Joseph and G. Yantao (2005), “Cross-market dynamics in property stock markets: some international evidence, Journal of Property Investment and Fiancne, 23(1), 55-75.
46. Ko, K.S. and S. B. Lee (1991), “A comparative analysis of the daily behavior of stock returns: Japan, the US, and the Asian NICs,” Journal of Business Finance, 18, 219-234.
47. Koutmos, G. and G. Booth (1995), “Asymmetric volatility transmission in international stock markets,” Journal of International Money and Finance, 14, 747-762.
48. Koutmos, G. (1996), “Modeling the dynamic interdependence of major European stock markets,” Journal of Business Finance and Accounting, 23, 975-988.
49. Kraus, A. and R. H. Litzenberger (1976), “Skewness preference and the valuation of risk assets,” Journal of Finance, 31(4), 1085-1100.
50. Kwiatkowski, D., P. C. B. Phillips, P. Schmidt and Y. Shin (1992), “Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we the economic time series have a unit root?” Journal of Econometrics, 54(1-3), 159-178.
51. Lau, H. S., J. Wingender and A. Lau (1989), “On estimating skewness in stock returns,” Management Science, 35, 1133-1142.
52. León, A., G. Rubio and G. Serna (2005), “Autoregressive conditional volatility, skewness and kurtosis,” Quarterly Review of Economics and Finance, 45, 599-618.
53. Lin, W. L., R. F. Engle and T. Ito (1994), “Do bulls and bears move across borders? International transmission of stock returns and volatility,” Review of Financial Studies, 7, 507-538.
54. Lintner, J. (1965), “The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets,” Review of Economics and Statistics, 47, 13-37.
55. Liu, Y. A, M. S. Pan and J. C. P. Shieh (1998), “International transmission of stock price movements: evidence from the U.S. and five Asian-Pacific markets,” Journal of Economics and Finance, 22, 59-69.
56. Markowitz, H. (1952), “Portfolio selection,” Journal of Finance, 8, 77-91.
57. Muralidhar, K. (1993), “The bootstrap approach for testing skewness persistence,” Management Science, 39, 487-491.
58. Nelson, D. B. (1991), “Conditional heteroskedasticity in asset return: a new approach,” Econometrica, 59, 347-370.
59. Newey, W. and K. West (1987), “A simple positive-definite heteroskedasticity and autocorrelation consistent covariance matrix,” Econometrica, 55, 703-708.
60. Perron, P. (1990), “Testing for a unit root in a time series with a changing mean,” Journal of Business and Economic Statistics, 8, 153-162.
61. Phillips, P. C. B. and P. Perron (1988), “Testing for unit in time series regression,” Biometrika, 75, 335-346.
62. Prakash, A. J., C. H. Chang and T. E. Pactwa (2003), “Selecting a portfolio with skewness; recent evidence from US, European, and Latin American equity markets,” Journal of Banking and Finance, 27, 1375-1390.
63. Prakash, A. J., M. de Boyrie and R. Moncarz (2001), “Applicability of CAPM in Latin American capital markets. In: Paper presented at the Annual International Trade and Finance Conference, Montpelier, France.
64. Pratt, J. W. (1964), “Risk aversion in the small and in the large,” Econometrica, 32(1/2), 122-136.
65. Schwert, G. W. (1989), “Tests for a unit roots in time series regression,” Biometrika, 75, 335-346.
66. Sharpe, W. F. (1964), “Capital asset prices: a theory of market equilibrium under condition of risk,” Journal of Finance, 19, 425-442.
67. Simkowitz, M. A. and W. L. Beedles (1978), “Diversification in a three-moment world,” Journal of Financial and Quantitative Analysis, 13, 927-941.
68. Singleton, J. C. and J. Wingender (1986), “Skewness persistence in common stock returns,” Journal of Financial and Quantitative Analysis, 13, 335-341.
69. Su, Y. C. (1994), “The dynamic spillovers between Taiwan and international capital markets,” Chinese Finance Association Annual Conference, 427-442.
70. Sun, Q. and Y. Yan (2003), “Skewness persistence with optimal portfolio selection,” Journal of Banking and Finance, 27, 111-1121.
71. Susmel, R. and R. F. Engel (1994), “Hourly volatility spillovers between international equity markets,” Journal of International Money and Finance, 13, 3-25.
72. Theodossiou, P. and U. Lee (1993), “Mean and volatility spillovers across major national stock market: further empirical evidence,” Journal of Financial Research, 16, 337-350.
73. Theodossiou, P. (1998), “Financial data and skewed generalized t distribution,” Management Science, 44, 1650-1661.
74. Tobin, J. (1958), “Liquidity preference as behavior towards risk,” Review of Economic Studies, 25(6/7), 65-86.
75. Wu, G. (1998), “The determination of asymmetric volatility,” Unpublished, Manuscript, Stanford University.
76. Wang, K. L., C. Fawson, C. B. Barrett and J. B. McDonald (2001), “A flexible parametric GARCH model with an application to exchange rates,” Journal of Applied Econometrics, 16(4), 521-536.
77. Wang, K. L. and C. Fawson (2001), “Modeling Asian stock returns with a more general parametric GARCH specification,” Journal of Financial Studies, 9(3), 21-52.
78. Wang, P. and P. Wang (2001), “Equilibrium adjustment, basis risk and risk transmission in spot and forward foreign exchange markets,” Applied Financial Economics, 11, 127-136.

二、國內文獻
1. 王凱立、林嘉慧(2003)，條件高階動差於財務金融市場之應用，財務金融學刊，11(2)，頁1-41.
2. 王毓敏、徐守德(1998)，「亞洲股市間報酬與波動性外溢效果之研究」，人文及社會科學研究彙刊(TSSCI)，國科會，第8卷，第3期，450-460。
3. 朱孟芳(2006)，大陸B股開放前後大中華地區股市波動外溢效果之研究，大葉大學國際企業管理所碩士論文。
4. 江智德(1997)，國際資本市場互動關係之研究-GARCH模型之應用，國立台灣大學商學研究所碩士論文。
5. 林于文(1999)，股價、匯價、利率傳遞效果之分析-多變量VAR-EGARCH的應用，逢甲大學經濟學研究所碩士論文。
6. 林青青(1999)，國際股市之漲跌對台灣及東南亞各國股市之影響，國立台灣大學財務金融研究
7. 徐守德(1995)，「亞洲股市間共整合關係之實證研究」，證券市場發展季刊，第七卷，第四期，33-57。
8. 陳君達(2000)，價格變動與國際股市波動相關性之研究，淡江大學財務金融學系碩士論文。
9. 黃瓊葦(2000)，亞太各國股市關連性與波動性探討，國立台北大學企業管理學系碩士論文。
10. 黃馨慧(2002)，台灣、日本、新加坡、韓國與美國股市關聯性之研究-VEC-TGARCH模型之應用，佛光人文社會學院經濟學研究所碩士論文。
11. 葉銀華(1991)，國際股票市場股價指數共移型態與關聯性之研究，台灣經濟金融月刊，第二十七期，第十卷，11-20。
12. 廖珮真(1993)，美日港新台五國股市報酬率多元時間序列關聯性之研究，國立台灣大學商學研究所碩士論文。
13. 蔡玠施(1995)，亞洲股市間動態波及效果的實證研究－GARCH模型的應用，國立台灣大學財務金融學系碩士論文。
14. 楊育軒(2003)，「台、美、日三國股價資訊傳遞之研究」，國立台北大學企業管理 學系研究所碩士論文。
15. 賴怡洵(2000)，「美、日、港、台股價資訊傳遞多元GARCH模式之研究」，證券櫃檯月刊，第五十二期，1-17。
16. 楊筆琇(1998)，台灣電子股指數與美國股價指數互動關係之實證研究，國立成功大學企業管理研究所碩士論文。
17. 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。
18. 謝朝光(2001)，台灣與亞太股市間關聯性與動態相關係數之研究，國立台北大學企業管理學系碩士論文。