臺灣博碩士論文加值系統

在經歷過亞洲金融風暴及全球金融風暴，亞洲股市的波動性產生了結構性改變是值得探討的議題，故本文主要運用ARCH家族模型探討亞洲股票市場在不同金融風暴與無重大風暴期間之波動特性。本研究以亞洲七個國家為主要研究對象，探討亞洲股票市場是否存在波動叢聚、波動不對稱性及長短期二種不同波動成分。隨後再納入遞延項流動變數，研究亞洲股票市場價量關係，驗證混合分配假說或資訊連續到達假說。根據本文實證結果發現：第一，亞洲股票市場的日報酬波動具有持續性與波動叢聚，且金融風暴對其波動叢聚的情形並無明顯貢獻性。第二，波動性的不對稱效果在無重大風暴時期較顯著，在全球金融風暴時期發生時則不明顯，在亞洲金融風暴期間則視其樣本國受風暴影響有所不同，受風暴影響愈大的國家，其波動的不對稱性愈不明顯。第三，亞洲國家的波動確實存有長短期二種不同的波動成分。最後，亞洲股價指數前期交易量係數皆為正數，顯示亞洲國家的交易量對條件報酬波動均存在正向關係，且在無重大風暴時期其前期交易量係數都達顯著水準，表示前期交易量資料對當期股價指數波動具有影響力，同時說明亞洲市場在無重大金融風暴時期面對資訊衝擊時，並無法立刻達到均衡，而是逐漸在調整下恢復均衡，因此本研究的實證結果支持亞洲股票市場在無重大金融風暴時期符合資訊連續到達假說。

目 錄
第一章 緒 論 6
第一節 研究背景 6
第二節 研究動機 7
第三節 研究目的 8
第四節 章節架構 10
第二章 文獻探討 12
第一節 資產價格波動性的探討 12
第二節 資訊傳遞與資產價格波動關係 15
第三節 股票市場波動性的相關研究 17
第四節 文獻探討小結 18
第三章資料與研究方法 22
第一節 研究樣本 22
第二節 樣本檢定 27
第三節 時間序列分析模型 31
第四章 實證結果 35
第一節 亞洲股價指數波動性 35
第二節 資訊傳遞與股價指數波動 42
第五章 結論與建議 53
第一節　結論 53
第二節　建議 53
參考文獻 55

參考文獻
1.Antoniou, A., P. Holmes and R. Priestley (1998), “The effects of stock index futures trading on stock index volatility: An analysis of the asymmetric response of volatility to news.” Journal of Futures Markets, 18, pp. 151-156.
2.Avramov, D., T. Chordia and A. Goyal (2004), “The impact of trades on daily volatility,” Working paper, University of Maryland, College Park, Maryland.
3.Black, F. (1976), “Studies of stock price volatility changes,” Proceedings of American Statistical Association, Business and Economics and Statistics Section, pp. 177-181.
4.Baker, M. and Wurgler, J., (2000). “The equity share in new issues and aggregate stock returns, ” Journal of Finance 55, 2219-2257.
5.Bohl, M. and H. Henke (2003), “Trading volume and stock market volatility: The Polish case,” International Review of Financial Analysis, 12, pp. 513-525.
6.Bollerslev, T. (1986), “Generalized autoregressive conditional heteroskedasticity,” Journal of Econometrics, 31, pp. 307-327.
7.Campbell, John Y., (1987). Stock returns and the term structure, Journal of Financial Economics, 18, pp. 373-399.
8.Campbell, J. and L. Hentschel (1992), “No news is good news: An asymmetric model of changing volatility in stock returns.” Journal of Financial Economics, 31, pp. 281-318.
9.Chordia, T., R. Roll and A. Subrahmanyan (2001), “Market liquidity and trading activity,” Journal of Finance, 56, pp. 501-530.
10.Christie, A. A. (1982), “The stochastic behavior of common stock variance-value, leverage and interest rate effects,” Journal of Financial Economics, 10, pp. 407-484.
11.Clark, P. K. (1973), “A subordinated stochastic process model with finite model with finite variance for speculative prices,” Econometrica, 41, pp. 135-155.
12.Chow Gregory c. (1960) ,”Tests of equality between sets of coefficients in two linear regressions,”.Econometica,28(3),pp.591-605.
13.Dickey, D. and W. A. Fuller (1981), “Likelihood ratio statistics for autoregressive time series with a unit root,” Econometrica, 49, pp. 1057-1072.
14.Ding, Z. and W. J. Granger (1996), “Modeling volatility persistence of speculative returns: A new approach,” Journal of Econometric, 73, pp. 185-215.
15.Engle, R. F. and G. Lee (1993), “A permanent and transitory component model of stock return volatility,” University of San Diego Discussion Paper, 92-44R.
16.Epps, T. W. and M. L. Epps (1976), “The stochastic dependence of security price changes and transaction volumes: Implication for the mixture distributions hypothesis,” Econometrica, 44, pp. 305-321.
17.Fama, E., (1965), “The behavior of stock market prices,” The Journal of Business, 38, pp. 34-105.
18.Fama, Eugene F. and French, Kenneth R. (1988). Dividend yields and expected stock returns, Journal of Financial Economics, 22, pp. 3-25.
19.Fama, E. F. and K. R. French (1998), “Value versus growth: The international evidence,” Journal of Finance, American Finance Association, 53, pp. 1975-1999.
20.Fornari, F and A. Mele （1997）, “Sign and volatility switching ARCH models: Theory and applications to international stock markets,” Journal of Applied Econometrics, 12, pp. 49-65.
21.French, K. R., G. W. Schwert and R. F. Stambaugh (1987), “Expected stock returns and volatility,” Journal of Financial Economics, 19, pp. 3-29.
22.Gallagher, L. (1999), “A multi-country analysis of the temporary and permanent of stock prices,” Applied Financial Economics, 9, pp. 129-142.
23.Gallant, A. R., P. E. Rossini and G. Tauchen (1992), “Stock prices and volume,” Review of financial Studies, 21, pp. 173-196.
24.Glosten, L. R., R. Jagannathan and D. E. Runkle (1993), “On the relation between expected value and the volatility of the nominal excess returns on stocks,” Journal of Finance, 48, pp. 1779-1801.
25.Hodrick, Robert J. (1992). Dividend yields and expected stock returns: Alternative procedures for inference and measurement. Review of Financial Studies, 5, pp.357-386.
26.Hadsell, L. (2006), “A TARCH examination of the return volatility- volume relationship in electricity futures,” Applied Financial Economics, 16, pp. 893-901.
27.Harris, L. (1986), “Cross-security tests of the mixture of distribution hypothesis,” Journal of Financial and Quantitative Analysis, 22, pp. 127-141.
28. . (1987), “Transaction data tests of the mixture of distributions hypothesis,” Journal of Financial and Quantitative Analysis, 22, pp. 127-141.
29.Harvey, L. (1989), Forecasting, Structural Time Series Models and Kalman Fiher, Cambridge University Press, Cambridge.
30.Jegadeesh, N. (1991), “Seasonality in stock price mean reversion: evidence from the U.S and the U.K,” Journal of Finance, 45, pp. 1427-1444.
31.Kirby, C. (1997). Measuring the predictable variation in stock and bond returns, Review of Financial Studies, 10, pp579-630.
32.Kothari, S.P. and Shanken, J. (1997). Book-to-market, dividend yield, and expected market returns: a time series analysis, Journal of Financial Economics, 44, pp.169-203.
33.Kalotychou, E. and S. K. Staikouras (2006), “Volatility and trading activity in Short Sterling futures,” Applied Economics, 38, pp. 997-1005.
34.Kandel, E. and N. D. Pearson (1995), “Differential interpretation of public signals and trade in speculative markets,” Journal of Political Economy, 103, pp. 831-872.
35.Lamoureux, C. G. and W. D. Lastrapes (1990a), “Persistence in variance, structural change, and the GARCH model,” Journal of Business and Economics Statistics, 8, pp. 225-234.
36. . (1990b), “Heteroscedasticity in stock returns data: Volume versus GARCH effects,” Journal of Finance, 45 pp. 221-229.
37.Nelson, D. B. (1990a), “Conditional heteroskedasticity in asset returns: A new approach,” Journal of Econometrica, 59, pp.347-370.
38.Pagan, A. R. and G. W. Schwert (1990), “Alternative models for conditional stock volatility,” Journal of Economics Literature, 41, pp.478-539.
39.Richardson, M. and T. Smith (1994), “A direct test of the mixture of distributions hypothesis: measuring the daily flow of information,” Journal of Financial and Quantitative Analysis, 29, pp.101-116.
40.Schwert, G. W. (1989), “Why does market volatility change over time,” Journal of Finance, 5, pp. 1115-1153.
41. . (1990), “Stock market volatility,” The Review of Financial Studies, 3, pp. 77-102.
42.Tsay, R.S. and Tiao, G. C. (1984), “Consistent estimates of autoregressive parameters and extended sample autocorrelation function for stationary and nonstationary ARMA models ,” Journal of the American Statistical Association, 79, pp.84-96.
43.Wood, R. A., McInish, T. H. and Ord, J. K. (1985), “An investigation of Transactions data for NYSE stock,” Journal of Finance, 60, pp. 723-739.
44.Zakoian, J. M. (1994), “Threshold heteroskedastic models,” Journal of Economic Dynamics and Control, 18, pp. 931-955.
45.莊忠柱、胡文正(民94)，「具有狀態轉換過程下的台灣股價指數與股價指數期貨市場的報酬與波動性動態關係」，Journal of Financial Studies Vol.13 No.1 April 2005.