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題名 以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
作者 温元駿
貢獻者 徐士勛
温元駿
關鍵詞 台灣股價指數
泡沫效果
Noncausal Cauchy AR(1) with Gaussian component
Taiwan stock price index
Bubble effect
Noncausal Cauchy AR(1) with Gaussian component
日期 2017
上傳時間 24-Jul-2017 12:16:28 (UTC+8)
摘要 過去實證研究多以時間序列模型搭配 GARCH 模型針對台灣股價指數進行分析。然而，Gourieroux and Zakoian(2017) 提出，當一時間序列具有泡沫現象時，noncausal Cauchy AR(1) process 是可能的優選模型。此外，Sarno and Taylor(1999) 的研究認為，台灣股價指數具有泡沫現象，故我們以 noncausal Cauchy AR(1) with Gaussian component 分析台灣股價指數，進而判斷其泡沫效果係來自 noncausal linear process 之 local explosive，並根據 noncausal Cauchy AR(1) 與 Gaussian component 之係數變動，捕捉泡沫效果之形成與來源。
Most of the previous studies focused on analyzing Taiwan Stock Price Index using time series models with GARCH effects. However, Gourieroux and Zakoian (2017) have demonstrated that noncausal Cauchy AR(1) process may be a possible model in which the bubbles are observed. Besides, according to the studies of Sarno and Taylor (1991), some bubbles exactly existed in Taiwan Stock Price Index before 1990. Accordingly, this study aims at investigating the possible bubbles in Taiwan Stock Price Index from 2005 to 2015 by employing noncausal Cauchy AR(1) with Gaussian component method. As a result, we find out he bubbles which modeled by the noncausal linear process are local explosive. And based on the changes of the coefficients from noncausal Cauchy AR(1) and Gaussian component, this study successfully captures the form of bubbles.
參考文獻 Ali, N., A. Nassir, T. Hassan and S. Z. Abidin (2009). Stock Overreaction and Financial Bubbles: Evidence from Malaysia. Journal of Money, Investment and Banking, 11, 90–101.
Blanchard, O. (1979). Speculative Bubbles: Crashes and Rational Expectations. Economics Letters, 3, 387–389.
Blanchard, O. and M. Watson (1982). Bubbles, Rational Expectations and Financial Markets. Crisis in the Economic and Financial Structure, edited by Paul Wachtel, Lexington Books, 295–316
Blattberg, R. C. and N. J. Gonedes (1974). A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices. The Journal of Business, 47:2, 244–280.
Bollerslev, T. (1987). A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return. The Review of Economics and Statistics, 69:3, 542–547.
Broda, S. A. (2012). The Expected Shortfall of Quadratic Portfolios with Heavy-Tailed Risk Factors. Mathematical Finance, 22:4, 710–728.
Carrasco, M., M. Chernov, J. Florens and E. Ghysels (2002). Efficient Estimation of Jump Diffusions and General Dynamic Models with a Continuum of Moment Conditions. Working Paper; Department of Economics: University of Rochester.
Davis, R. and S. Resnick (1985). Limit Theory for Moving Averages of Random Variables with Regularly Varying Tail Probabilities. Annals of Probability, 13, 179–195.
Davis, R. and S. Resnick (1986). Limit Theory for the Sample Covariance and Correlation Functions of Moving Averages. Annals of Statistics, 14, 533–558.
Diba, B. and H. Grossman (1988). Explosive Rational Bubbles in Stock Prices? The American Economic Review, 78, 520–530.
Evans, G. (1991). Pitfalls in Testing for Explosive Bubbles in Asset Prices. The American Economic Review, 81:4, 922–930.
Fama, E. (1963). Mandelbrot and the Stable Paretian Hypothesis. The Journal of Business, 36:4, 420–429.
Fama, E. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38:1, 34–105.
Feuerverger, A. (1990). An Efficiency Result for the Empirical Characteristic Function in Stationary Time-Series Models. The Canadian Journal of Statistics, 18:2, 155–161.
Flood, R. and P. Garber (1980). Market Fundamentals Versus Price Level Bubbles. The First Tests. Journal of Political Economy, 88, 745–770.
Glasserman, P., P.HeidelbergerandP.Shahabuddin(2002). PortfolioValueat Risk with Heavy-Tailed Risk Factors. Mathematical Finance, 12:3,239–269.
Gourieroux, C. and A. Hencic (2015). Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange rate. Econometrics of Risk, 583, 17–40.
Gourieroux, C. and J. M. Zakoian (2017). Local Explosion Modelling by Noncausal Process. Journal of the Royal Statistical Society: Series B, forthcoming.
Homm, U. and J. Breitung (2012). Testing for Speculative Bubbles in Stock Markets: A Comparison of Alternative Methods. Journal of Financial Econometrics, 10, 198–231.
Hu, B. (2011). Are Asian stock markets characterized by rational speculative bubbles? Lincoln University.
Huisman, R., K. G. Koedijk and R. A. J. Pownall (1998). VaR-x: Fat Tails in Financial Risk Management. Journal of Risk, 1:1, 47–61.
Jiang, G. and J. L. Knight (2002). Estimation of Continuous Time Processes via the Empirical Characteristic Function. Journal of Business & Economic Statistics, 20:2, 198–212.
Knight, J. L. and S. E. Satchell (1996). Estimation of Stationary Stochastic Processes via the Empirical Characteristic Function. Working Paper, Department of Economics, University of Western Ontario.
Knight, J. L. and S. E. Satchell (1997). The Cumulant Generating Function Estimation Method. Econometric Theory, 13:2, 170–184.
Knight, J. L. and J. Yu (2002). The Empirical Characteristic Function in Time Series Estimation. Econometric Theory, 18, 691–721.
Lehkonen, H. (2010). Bubble in China. International Review of Financial Analysis, 19, 113–117.
Mandelbrot, B. (1963). The Variation of Certain Speculative Prices. Journal of Business, 36:4, 394–419.
Mandelbrot, B. and H. M. Taylor (1967). On the Distribution of Stock Price Difference. Operations Research, 15:6, 1057–1062.
McNeil, A. J. and R. Frey (2000). Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: An Extreme Value Approach. Journal of Empirical Finance, 7:3-4, 271–300.
Mokhtar, S. H., A. M. Nassir and T. Hassan (2006). Detecting Rational Speculative Bubbles in the Malaysian Stock Market. International Research Journal of Finance and Economics, 6, 102–115.
Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59:2, 347–370.
Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33, 1065–1076.
Phillips, P., Y. Wu and J. Yu (2011) Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values? International Economic Review, 52, 201–226.
Phillips, P., S. Shi and J. Yu (2012). Testing for Multiple Bubbles. Cowles Foundation Discussion Paper, 1843.
Politis, D. N. (2004). A Heavy-Tailed Distribution for ARCH Residuals with Application to Volatility Prediction. Annals of Economics and Finance, 5, 283–298.
Praetz, P. D. (1972). The Distribution of Share Price Changes. The Journal of Business, 45:1, 49–55.
Sarno, L. and M. P. Taylor (1999). Moral Hazard, Asset Price Bubbles, Capital Flows, and the East Asian Crisis: The First Tests. Journal of International Money and Finance, 18, 637–657.
Yu, J. (1998). The Empirical Characteristic Function in Time-Series Estimation. Ph.D. thesis, University of Western Ontario.
Yu, J. (2004). Empirical Characteristic Function Estimation and Its Applications. Econometric Reviews, 23, 93–123.
Zhang, B. (2008). Duration Dependence Test for Rational Bubbles in Chinese Stock Market. Applied Economics Letters, 15:8, 635–639.
描述 碩士
國立政治大學
經濟學系
104258003
資料來源 http://thesis.lib.nccu.edu.tw/record/#G1042580031
資料類型 thesis
dc.contributor.advisor 徐士勛zh_TW
dc.contributor.author (Authors) 温元駿zh_TW
dc.creator (作者) 温元駿zh_TW
dc.date (日期) 2017en_US
dc.date.accessioned 24-Jul-2017 12:16:28 (UTC+8)-
dc.date.available 24-Jul-2017 12:16:28 (UTC+8)-
dc.date.issued (上傳時間) 24-Jul-2017 12:16:28 (UTC+8)-
dc.identifier (Other Identifiers) G1042580031en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111376-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟學系zh_TW
dc.description (描述) 104258003zh_TW
dc.description.abstract (摘要) 過去實證研究多以時間序列模型搭配 GARCH 模型針對台灣股價指數進行分析。然而，Gourieroux and Zakoian(2017) 提出，當一時間序列具有泡沫現象時，noncausal Cauchy AR(1) process 是可能的優選模型。此外，Sarno and Taylor(1999) 的研究認為，台灣股價指數具有泡沫現象，故我們以 noncausal Cauchy AR(1) with Gaussian component 分析台灣股價指數，進而判斷其泡沫效果係來自 noncausal linear process 之 local explosive，並根據 noncausal Cauchy AR(1) 與 Gaussian component 之係數變動，捕捉泡沫效果之形成與來源。zh_TW
dc.description.abstract (摘要) Most of the previous studies focused on analyzing Taiwan Stock Price Index using time series models with GARCH effects. However, Gourieroux and Zakoian (2017) have demonstrated that noncausal Cauchy AR(1) process may be a possible model in which the bubbles are observed. Besides, according to the studies of Sarno and Taylor (1991), some bubbles exactly existed in Taiwan Stock Price Index before 1990. Accordingly, this study aims at investigating the possible bubbles in Taiwan Stock Price Index from 2005 to 2015 by employing noncausal Cauchy AR(1) with Gaussian component method. As a result, we find out he bubbles which modeled by the noncausal linear process are local explosive. And based on the changes of the coefficients from noncausal Cauchy AR(1) and Gaussian component, this study successfully captures the form of bubbles.en_US
dc.description.tableofcontents 1 緒論 1
2 文獻回顧 3
3 研究模型 6
3.1 穩定分配 (Stable distribution) 6
3.2 橢圓分配 (Elliptical distribution) 7
3.3 Noncausal linear AR(1) process 8
4 估計方法 10
4.1 泡沫效果 (Bubble Effect) 10
4.2 Noncausal Cauchy AR(1) 之係數估計與其漸近性質 10
4.3 NoncausalCauchylinearAR(1)processwithGaussianAR(1)component 13
4.4 實證特徵函數 (empirical characteristic function, ECF) 估計 14
4.4.1 獨立且同分配資料型態 15
4.4.2 時間序列資料型態 15
4.5 資料模擬 16
5 實證分析 19
5.1 資料基本分析與描述 19
5.2 ACF 分析 21
5.3 模型檢定 21
5.4 參數估計 24
5.5 分段估計 25
6 結論 32
A 一般動差估計法(generalizedmethodofmomentestimator, GMM
estimator) 39		zh_TW
dc.format.extent 1019004 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1042580031en_US
dc.subject (關鍵詞) 台灣股價指數zh_TW
dc.subject (關鍵詞) 泡沫效果zh_TW
dc.subject (關鍵詞) Noncausal Cauchy AR(1) with Gaussian componentzh_TW
dc.subject (關鍵詞) Taiwan stock price indexen_US
dc.subject (關鍵詞) Bubble effecten_US
dc.subject (關鍵詞) Noncausal Cauchy AR(1) with Gaussian componenten_US
dc.title (題名) 以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數zh_TW
dc.title (題名) Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Indexen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Ali, N., A. Nassir, T. Hassan and S. Z. Abidin (2009). Stock Overreaction and Financial Bubbles: Evidence from Malaysia. Journal of Money, Investment and Banking, 11, 90–101.
Blanchard, O. (1979). Speculative Bubbles: Crashes and Rational Expectations. Economics Letters, 3, 387–389.
Blanchard, O. and M. Watson (1982). Bubbles, Rational Expectations and Financial Markets. Crisis in the Economic and Financial Structure, edited by Paul Wachtel, Lexington Books, 295–316
Blattberg, R. C. and N. J. Gonedes (1974). A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices. The Journal of Business, 47:2, 244–280.
Bollerslev, T. (1987). A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return. The Review of Economics and Statistics, 69:3, 542–547.
Broda, S. A. (2012). The Expected Shortfall of Quadratic Portfolios with Heavy-Tailed Risk Factors. Mathematical Finance, 22:4, 710–728.
Carrasco, M., M. Chernov, J. Florens and E. Ghysels (2002). Efficient Estimation of Jump Diffusions and General Dynamic Models with a Continuum of Moment Conditions. Working Paper; Department of Economics: University of Rochester.
Davis, R. and S. Resnick (1985). Limit Theory for Moving Averages of Random Variables with Regularly Varying Tail Probabilities. Annals of Probability, 13, 179–195.
Davis, R. and S. Resnick (1986). Limit Theory for the Sample Covariance and Correlation Functions of Moving Averages. Annals of Statistics, 14, 533–558.
Diba, B. and H. Grossman (1988). Explosive Rational Bubbles in Stock Prices? The American Economic Review, 78, 520–530.
Evans, G. (1991). Pitfalls in Testing for Explosive Bubbles in Asset Prices. The American Economic Review, 81:4, 922–930.
Fama, E. (1963). Mandelbrot and the Stable Paretian Hypothesis. The Journal of Business, 36:4, 420–429.
Fama, E. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38:1, 34–105.
Feuerverger, A. (1990). An Efficiency Result for the Empirical Characteristic Function in Stationary Time-Series Models. The Canadian Journal of Statistics, 18:2, 155–161.
Flood, R. and P. Garber (1980). Market Fundamentals Versus Price Level Bubbles. The First Tests. Journal of Political Economy, 88, 745–770.
Glasserman, P., P.HeidelbergerandP.Shahabuddin(2002). PortfolioValueat Risk with Heavy-Tailed Risk Factors. Mathematical Finance, 12:3,239–269.
Gourieroux, C. and A. Hencic (2015). Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange rate. Econometrics of Risk, 583, 17–40.
Gourieroux, C. and J. M. Zakoian (2017). Local Explosion Modelling by Noncausal Process. Journal of the Royal Statistical Society: Series B, forthcoming.
Homm, U. and J. Breitung (2012). Testing for Speculative Bubbles in Stock Markets: A Comparison of Alternative Methods. Journal of Financial Econometrics, 10, 198–231.
Hu, B. (2011). Are Asian stock markets characterized by rational speculative bubbles? Lincoln University.
Huisman, R., K. G. Koedijk and R. A. J. Pownall (1998). VaR-x: Fat Tails in Financial Risk Management. Journal of Risk, 1:1, 47–61.
Jiang, G. and J. L. Knight (2002). Estimation of Continuous Time Processes via the Empirical Characteristic Function. Journal of Business & Economic Statistics, 20:2, 198–212.
Knight, J. L. and S. E. Satchell (1996). Estimation of Stationary Stochastic Processes via the Empirical Characteristic Function. Working Paper, Department of Economics, University of Western Ontario.
Knight, J. L. and S. E. Satchell (1997). The Cumulant Generating Function Estimation Method. Econometric Theory, 13:2, 170–184.
Knight, J. L. and J. Yu (2002). The Empirical Characteristic Function in Time Series Estimation. Econometric Theory, 18, 691–721.
Lehkonen, H. (2010). Bubble in China. International Review of Financial Analysis, 19, 113–117.
Mandelbrot, B. (1963). The Variation of Certain Speculative Prices. Journal of Business, 36:4, 394–419.
Mandelbrot, B. and H. M. Taylor (1967). On the Distribution of Stock Price Difference. Operations Research, 15:6, 1057–1062.
McNeil, A. J. and R. Frey (2000). Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: An Extreme Value Approach. Journal of Empirical Finance, 7:3-4, 271–300.
Mokhtar, S. H., A. M. Nassir and T. Hassan (2006). Detecting Rational Speculative Bubbles in the Malaysian Stock Market. International Research Journal of Finance and Economics, 6, 102–115.
Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59:2, 347–370.
Parzen, E. (1962). On estimation of a probability density function and mode. Annals of Mathematical Statistics, 33, 1065–1076.
Phillips, P., Y. Wu and J. Yu (2011) Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values? International Economic Review, 52, 201–226.
Phillips, P., S. Shi and J. Yu (2012). Testing for Multiple Bubbles. Cowles Foundation Discussion Paper, 1843.
Politis, D. N. (2004). A Heavy-Tailed Distribution for ARCH Residuals with Application to Volatility Prediction. Annals of Economics and Finance, 5, 283–298.
Praetz, P. D. (1972). The Distribution of Share Price Changes. The Journal of Business, 45:1, 49–55.
Sarno, L. and M. P. Taylor (1999). Moral Hazard, Asset Price Bubbles, Capital Flows, and the East Asian Crisis: The First Tests. Journal of International Money and Finance, 18, 637–657.
Yu, J. (1998). The Empirical Characteristic Function in Time-Series Estimation. Ph.D. thesis, University of Western Ontario.
Yu, J. (2004). Empirical Characteristic Function Estimation and Its Applications. Econometric Reviews, 23, 93–123.
Zhang, B. (2008). Duration Dependence Test for Rational Bubbles in Chinese Stock Market. Applied Economics Letters, 15:8, 635–639.		zh_TW