Open Access
2014 Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation
Xiaohui Wang, Weiguo Zhang
Abstr. Appl. Anal. 2014(SI35): 1-10 (2014). DOI: 10.1155/2014/462982

Abstract

Ordinary least squares estimators of variogram parameters in long-memory stochastic volatility are studied in this paper. We use the discrete observations for practical purposes under the assumption that the Hurst parameter H ( 1 / 2,1 ) is known. Based on the ordinary least squares method, we obtain both the explicit estimators for drift and diffusion by minimizing the distance function between the variogram and the data periodogram. Furthermore, the resulting estimators are shown to be consistent and to have the asymptotic normality. Numerical examples are also presented to illustrate the performance of our method.

Citation

Download Citation

Xiaohui Wang. Weiguo Zhang. "Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation." Abstr. Appl. Anal. 2014 (SI35) 1 - 10, 2014. https://doi.org/10.1155/2014/462982

Information

Published: 2014
First available in Project Euclid: 6 October 2014

zbMATH: 07022427
MathSciNet: MR3191043
Digital Object Identifier: 10.1155/2014/462982

Rights: Copyright © 2014 Hindawi

Vol.2014 • No. SI35 • 2014
Back to Top