Sankhya: The Indian Journal of Statistics
A Note on Uniform Convergence of an ARCH$(\infty)$ Estimator
Suhasini Subba Rao, Texas A&M University, USA
SUMMARY. We consider parameter estimation for a class of ARCH$(\infty)$ models, which do not necessarily have a parametric form. The estimation is based on a normalized least squares approach, where the normalization is the weighted sum of past observations. The number of parameters estimated depends on the sample size and increases as the sample size grows. Using maximal inequalities for martingales and mixingales we derive a uniform rate of convergence for the parameter estimator. We show that the rate of convergence depends both on the number of parameters estimated and the rate that the ARCH$(\infty)$ parameters tend to zero.
AMS (2000) subject classification. Primary 62M09; secondary 91B84, 37B10.
Key words and phrases. ARCH, maximal inequalities, nonlinear process, near epoch dependence,weighted least squares.