Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation
Xiaohui Wang and
Weiguo Zhang
Abstract and Applied Analysis, 2014, vol. 2014, 1-10
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 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.
Date: 2014
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/AAA/2014/462982.pdf (application/pdf)
http://downloads.hindawi.com/journals/AAA/2014/462982.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:462982
DOI: 10.1155/2014/462982
Access Statistics for this article
More articles in Abstract and Applied Analysis from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().