Parameter Estimation in Nonlinear AR-GARCH Models
نویسندگان
چکیده
منابع مشابه
Parameter estimation in nonlinear AR - GARCH models
This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a general nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. We do not require the rescaled errors to be ind...
متن کاملStability of nonlinear AR–GARCH models
This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Conditions under which the model is stable in the sense that its Markov chain repre...
متن کاملConstrained Nonlinear Programming for Volatility Estimation with GARCH Models
This paper proposes a constrained nonlinear programming view of generalized autoregressive conditional heteroskedasticity (GARCH) volatility estimation models in financial econometrics. These models are usually presented to the reader as unconstrained optimization models with recursive terms in the literature, whereas they actually fall into the domain of nonconvex nonlinear programming. Our re...
متن کاملM -estimation in Garch Models
This paper derives asymptotic normality of a class of M-estimators in the generalized autoregressive conditional heteroskedastic ~GARCH! model+ The class of estimators includes least absolute deviation and Huber’s estimator in addition to the well-known quasi maximum likelihood estimator+ For some estimators, the asymptotic normality results are obtained only under the existence of fractional u...
متن کاملRobust Minimum Distance Estimation for Nonlinear Semi-Strong GARCH Models
We develop a class of Minimum Distance Estimators for semi-strong Nonlinear ARMAX-Nonlinear GARCH processes. The estimators are asymptotically normal for possibly very heavy-tailed data due to underlying shocks and/or model parameter values. In particular we only impose trivial moment conditions on the GARCH errors, covering non-stationary GARCH. The MDE class is couched within a Method of Mome...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2008
ISSN: 1556-5068
DOI: 10.2139/ssrn.1148175