Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-25
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wang, Xiaohui& Zhang, Wei-Guo. 2014. Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1013971
Modern Language Association (MLA)
Wang, Xiaohui& Zhang, Wei-Guo. Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation. Abstract and Applied Analysis No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1013971
American Medical Association (AMA)
Wang, Xiaohui& Zhang, Wei-Guo. Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1013971
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1013971