Rapid Optimal Lag Order Detection and Parameter Estimation of Standard Long Memory Time Series

Objective of this paper is to highlight the rapid assessment (in a few minutes) of fractionally differenced standard long memory time series in terms of parameter estimation and optimal lag order assessment. Initially, theoretical aspects of standard fractionally differenced processes with long memory and related state space modelling will be discussed. An efficient mechanism based on theory to estimate parameters and detect optimal lag order in minimizing processing speed and turnaround time is introduced subsequently. The methodology is extended using an available result in literature to present rapid results of an optimal fractionally differenced standard long memory model. Finally, the technique is applied to a couple of real data applications illustrating it’s feasibility and importance.