A recursive online algorithm for the estimation of time-varying ARCH parameters | Academic Article individual record
abstract

In this paper we propose a recursive online algorithm for estimating the parameters of a time-varying ARCH process. The estimation is done by updating the estimator at time point t - 1 with observations about the time point t to yield an estimator of the parameter at time point t. The sampling properties of this estimator are studied in a non-stationary context - in particular, asymptotic normality and an expression for the bias due to non-stationarity are established. By running two recursive online algorithms in parallel with different step sizes and taking a linear combination of the estimators the rate of convergence can be improved for parameter curves from Hlder classes of order between 1 and 2. 2007 ISI/BS.

publication outlet

Bernoulli

author list (cited authors)
Dahlhaus, R., & Rao, S. S.
publication date
2007
citation count

16