Least squares estimator for Ornstein–Uhlenbeck processes driven by αα-stable motions

We study the problem of parameter estimation for generalized Ornstein–Uhlenbeck processes driven by αα-stable noises, observed at discrete time instants. Least squares method is used to obtain an asymptotically consistent estimator. The strong consistency and the rate of convergence of the estimator have been studied. The estimator has a higher order of convergence in the general stable, non-Gaussian case than in the classical Gaussian case.