A COMPARISON OF ESTIMATION METHODS IN NON-STATIONARY ARFIMA PROCESSES

摘要

This paper reports an extensive Monte Carlo simulation study based on six estimators for the long memory fractional parameter when the time series is non-stationary, i.e., ARFIMA(p, d, q) process for d > 0.5. Parametric and semiparametric methods are compared. In addition, the effect of the parameter estimation is investigated for small and large sample sizes and non-Gaussian error innovations. The methodology is applied to a well known data set, the so-called UK short interest rates.