Reconsidering Moments-Based Estimators for ARCH Processes

2014 ◽  
Author(s):  
Todd Prono
Keyword(s):  
2002 ◽  
Vol 23 (3) ◽  
pp. 341-375 ◽  
Author(s):  
NORA MULER ◽  
VICTOR J. YOHAI

2013 ◽  
Vol 14 (1) ◽  
pp. 143-170 ◽  
Author(s):  
Gilles Zumbach ◽  
Luis Fernández

Author(s):  
Sebastian Kühnert

Conditional heteroskedastic financial time series are commonly modelled by (G)ARCH processes. ARCH(1) and GARCH were recently established in C[0,1] and L^2[0,1]. This article provides sufficient conditions for the existence of strictly stationary solutions, weak dependence and finite moments of (G)ARCH processes for any order in C[0,1] and L^p[0,1]. It deduces explicit asymptotic upper bounds of estimation errors for the shift term, the complete (G)ARCH operators and the projections of ARCH operators on finite-dimensional subspaces. The operator estimaton is based on Yule-Walker equations, and estimating the GARCH operators also involves a result estimating operators in invertible linear processes being valid beyond the scope of (G)ARCH. Moreover, our results regarding (G)ARCH can be transferred to functional AR(MA).


2012 ◽  
Vol 9 (3) ◽  
pp. 144-156 ◽  
Author(s):  
Gilles Zumbach

2008 ◽  
Vol 146 (2) ◽  
pp. 275-292 ◽  
Author(s):  
Heejoon Han ◽  
Joon Y. Park
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document