Limit theory for autoregressive‐parameter estimates in an infinite‐variance random walk

We consider the asymptotic behaviour of least‐squares and M ‐estimates of the autoregressive parameter when the process is an infinite‐variance random walk. It is shown that certain M ‐estimates converge faster than least‐squares estimates and that they are also asymptotically normal.