Maximum Likelihood Estimation of the Fractional Differencing Parameter in an Arfima Model Using Wavelets
In this paper, we examine the finite-sample properties of the approximate maximum likelihood estimate (MLE) of the fractional differencing parameter d in an ARFIMA(p, d, q) model based on the wavelet coefficients. Ignoring wavelet coefficients of higher order of resolution, the remaining wavelet coefficients approximate a sample of independently and identically distributed normal variates with homogeneous variance within each level. The approximate MLE performs satisfactorily and provides a robust estimate for which the short memory component need not be specified.
Mathematics and Computers in Simulation
TSE, Yiu Kuen; Anh, V. V.; and Tieng, Q. M..
Maximum Likelihood Estimation of the Fractional Differencing Parameter in an Arfima Model Using Wavelets. (2002). Mathematics and Computers in Simulation. 59, 153-161. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/321
This document is currently not available here.