Semi-parametric smoothing estimators for long-memory processes with added noise

Authors

Nuno Crato, ISEG Lisbon School of Economics and Management
Bonnie K. Ray, New Jersey Institute of Technology

Document Type

Article

Publication Date

7-1-2002

Abstract

The development of long-memory stochastic volatility (LMSV) models has increased the interest in the estimation of persistent processes observed with added noise. This paper investigates the performance of semi-parametric methods for estimating the long-memory-parameter in the long-range dependence plus noise case and demonstrates improvements obtained by preliminary smoothing and aggregation of the series. © 2001 Elsevier Science B.V. All rights reserved.

Identifier

0036643512 (Scopus)

Publication Title

Journal of Statistical Planning and Inference

External Full Text Location

https://doi.org/10.1016/S0378-3758(01)00275-0

ISSN

03783758

First Page

283

Last Page

297

Issue

2

Volume

105

Recommended Citation

Crato, Nuno and Ray, Bonnie K., "Semi-parametric smoothing estimators for long-memory processes with added noise" (2002). Faculty Publications. 14656.
https://digitalcommons.njit.edu/fac_pubs/14656