Quantile Estimation of Double Threshold Autoregressive Models with Exogenous Variables and Heteroskedasticity
2011/03/15
研討會日期 : 2011-03-15
時間 : 14:30
主講人 : Professor Cathy Chen
地點 : Conference Room B110
演講者簡介 : Cathy Chen got her Ph.D. in Statistics from National Central University in 1993. She is currently serving as Distinguished Professor of Department of Statistics at Feng Chia University. Her research field is in Bayesian inference, modeling and forecasting of financial time series, market volatility study and value at risk estimation in financial markets, Markov chain Monte Carlo estimation, statistical computing, quantile regression, and statistical methods in epidemiology.
演講摘要 : Comparing to the conditional mean, the conditional quantile provides a more comprehensive picture of a variable in various scenarios. A quantile estimation method of a double threshold auto-regression with exogenous regressors and heteroskedasticity is considered, allowing semi-parametric representation of both asymmetry and volatility clustering. As such, GARCH-type dynamics with nonlinearity are added to a nonlinear time series regression model. An adaptive Bayesian Markov chain Monte Carlo scheme, exploiting the link between the quantile loss function and the skewed-Laplace distribution, is employed for estimation and inference, simultaneously estimating and accounting for nonlinear heteroskedasticity plus unknown threshold limits and delay lags. A simulation study illustrates sampling properties of the method. Two data sets are considered in the empirical applications: modelling daily maximum temperatures in Melbourne, Australia; and exploring dynamic linkages between the markets in the US and Hong Kong.
