政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/35100

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/35100

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政大典藏 > College of Commerce > Department of International Business > Theses > Item 140.119/35100

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/35100

Title:	布蘭特原油期貨的波動率－以馬可夫移轉模型分析 Regime-switched volatility of Brent crude oil futures using Markov-switching ARCH model
Authors:	邱天禹 Chiu, Tien-Yu
Contributors:	謝淑貞 Shieh, Shwu-Jane 邱天禹 Chiu, Tien-Yu
Keywords:	馬可夫轉換波動率布蘭特原油 Markov-switching ARCH SWARCH volatility Brent crude oil
Date:	2005
Issue Date:	2009-09-18 14:09:54 (UTC+8)
Abstract:	本篇論文使用SWARCH模型探討布蘭特原油期貨市場的波動性。SWARCH模型將條件變異設定為可隨時間變動而改變，甚至移轉到不同的區間上。實證結果顯示SWARCH (3,3)模型具有最佳配適度與最準確的預測能力。樣本在不同區間下的平滑機率的估計值有助於補捉資料特性，而且當樣本落在高波動率區間上時會對應著重大事件的發生，如1990年波斯灣戰爭、1997年亞洲金融風暴與2001年的911恐怖攻擊。 This paper investigates the volatility of the Brent crude oil futures markets using Markov-switching ARCH (SWARCH) model. The SWARCH model allows the conditional disturbances to change as time passes and even to switch in different regimes. The empirical evidence shows that the SWARCH (3,3) model performs the best goodness of fit and the best forecast performance between different fitting models. The estimation of smoothing probabilities of data under different regimes facilitates to capture the characteristics of data, and the high-volatility regime is associated with the extraordinary events, such as the 1990’s Persian Gulf War, the 1997’s Asia Financial Crisis, and the 2001’s 911 terrorist attack.
Reference:	Bollerslev T. Generalized autogressive conditional heteroskedasticity. Journal of Econometrics, 1986. Cai J. A Markov Model of Switching-Regime ARCH. Journal of Business and Economic Statistics, 1994. Cologni A., Manera M. The asymmetric effects of oil shocks on output growth: A Markov-switching analysis for the G-7 countries. Working paper, 2006. Dickey D.A., Fuller W.A. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 1979. Diebold, F. X. Modelling the persistence of conditional variance: A comment. Econometric Review, 1986. Enders W. Applied econometric time series, second edition. University of Alabama. Engle R.F. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 1982. Hamilton J. D., Susmel R. Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics, 1994. Hamilton J. D. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 1989. Jiang S.L., Wang C.F., Wu X.L. Investigating on volatility OF Chinese stock market by regime-switching ARCH model. Journal of systems engineering, 2004. Kumar, Manmohan. Forecasting Accuracy of Crude Oil Futures Prices. IMF Working paper, 2006. Lamoureux C. G., Lastrapes W. D. Persistence in variance, structural change and the GARCH model. Journal of Business and Economic Statistics, 1990. Pagano P., Pisani M. Risk-adjusted forecasts of oil prices. Bank of Italy Economic Research Paper,2006. Phillips P.C.B., Perron P. Testing for a unit root in time series regression. Biometrika,1988. Tsay R.S. Analysis of financial time series, financial econometrics. University of Chicago. Yang Z. Estimation of Markov Regime-Switching Model. Working paper, 2004.
Description:	碩士國立政治大學國際經營與貿易研究所 93351006 94
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0093351006
Data Type:	thesis
Appears in Collections:	[Department of International Business] Theses

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