Abstract #300254

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JSM 2002 Abstract #300254
Activity Number: 268
Type: Invited
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: Business & Economics Statistics Section*
Abstract - #300254
Title: On Estimation and Prediction for Long Memory Stochastic Volatility Models
Author(s): Rohit Deo*+ and Cliff Hurvich
Affiliation(s): New York University and Stern School of Business, New York University
Address: 44 West 4th Street, New York, New York, 10012-1106,
Keywords:
Abstract:

We consider GMM and QML estimation of long memory stochastic volatility models. We show that moment conditions currently used in the literature for GMM estimation have a slower rate of convergence than root n for the long memory SV model, while the QML estimator still preserves the root n rate. We provide a new set of moment conditions, which are able to preserve the root n rate for GMM estimation. We then consider issues pertaining to prediction of squared returns based not only on past squared returns but also on general powers of past absolute returns.

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