Testing Nonlinearity for Double Threshold Autoregressive Conditional Heteroskedastic Models
碩士 === 逢甲大學 === 統計與精算所 === 95 === This paper proposed a simple test of the hypothesis that either the mean or the variance are nonlinear in a heteroskedastic model. We estimated the parameters under Bayesian Markov chain Monte Carlo methods and fit a general double threshold ARX-GARCH model with exo...
Main Authors: | Pei-Ju Tai, 戴珮如 |
---|---|
Other Authors: | Cathy W.S. Chen |
Format: | Others |
Language: | en_US |
Published: |
2007
|
Online Access: | http://ndltd.ncl.edu.tw/handle/65058118530275847397 |
Similar Items
-
On the Autoregressive Conditional Heteroskedasticity Models
by: Stenberg, Erik
Published: (2016) -
Evaluating Three-regime Threshold Generalized Autoregressive Conditionally Heteroskedastic Models
by: Mei-hui Lin, et al.
Published: (2007) -
Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes
by: W. Wang, et al.
Published: (2005-01-01) -
Essays on autoregressive conditional heteroskedasticity
by: Silvennoinen, Annastiina
Published: (2006) -
An Application of Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Modelling on Taiwan's Time-Series Data: Three Essays
by: Chang, Tsangyao
Published: (1995)