On Estimating the Parameters in Conditional Heteroskedasticity Models by Empirical Likelihood Estimation

• Main Authors: Shiang-Yuan Wang, 王香媛
• Other Authors: Tsung-Lin Cheng
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/57836249601181302212

碩士 === 國立彰化師範大學 === 數學系所 === 97 === In most time series models, the data sets that we might be confront with are not statistically independent. While the celebrated empirical likelihood (EL) estimation proposed by owen (1988) has been widely used in a framework of independent data without having to know the distribution of the population, it is also challenging to apply EL estimation to the models with dependent data. After Kitamura (1997), there has been a lot of papers focus on the topic of how to apply EL method to a data set with dependence (short-range dependence or long-range dependence ). In this thesis,we will exploit EL method to estimate the parameters emerging in some important econometrical models including ARCH, GARCH, EGARCH and TGARCH. In addition, we conduct some illustrative simulations to compare EL approach with other methods of estimation (e.g. MLE and OLS). Finally, we analyze the data of the West Texas Intermediate (WTI) Crude Oil Prices by fitting it into the GARCH model.