Econometric Theory

Table of Contents - 2001 - Volume 17, Issue 04  


ON THE LOG PERIODOGRAM REGRESSION ESTIMATOR OF THE MEMORY PARAMETER IN LONG MEMORY STOCHASTIC VOLATILITY MODELS

Rohit S.  Deo a1c1 and Clifford M.  Hurvich a1
a1 New York University

Abstract

We consider semiparametric estimation of the memory parameter in a long memory stochastic volatility model. We study the estimator based on a log periodogram regression as originally proposed by Geweke and Porter-Hudak (1983, Journal of Time Series Analysis 4, 221–238). Expressions for the asymptotic bias and variance of the estimator are obtained, and the asymptotic distribution is shown to be the same as that obtained in recent literature for a Gaussian long memory series. The theoretical result does not require omission of a block of frequencies near the origin. We show that this ability to use the lowest frequencies is particularly desirable in the context of the long memory stochastic volatility model.


Correspondence:
c1 Address correspondence to: Rohit Deo, 8-57 KMEC, 44 West 4th Street, New York, NY 10012, USA; e-mail: rdeo@stern.nyu.edu.

--