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Moment based estimation of supOU processes and a related stochastic volatility model
-
Robert Stelzer
,
Thomas Tosstorff
Veröffentlicht/Copyright:
12. März 2015
Abstract
After a quick review of superpositions of OU (supOU) processes, integrated supOU processes and the supOU stochastic volatility model we estimate these processes by using the generalized method of moments (GMM). We show that the GMM approach yields consistent estimators and that it works very well in practice. Moreover, we discuss the influence of long memory effects.
Keywords: Generalized method of moments; Ornstein–Uhlenbeck type process; Lévy basis; long memory; stochastic volatility; superpositions
The authors are very grateful to the editor and two anonymous referees for very helpful suggestions, and to Christian Pigorsch for influential discussions.
Received: 2013-6-4
Revised: 2015-1-23
Accepted: 2015-2-12
Published Online: 2015-3-12
Published in Print: 2015-4-1
© 2015 by De Gruyter
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Artikel in diesem Heft
- Frontmatter
- Moment based estimation of supOU processes and a related stochastic volatility model
- Quasi-Hadamard differentiability of general risk functionals and its application
- Series expansions for convolutions of Pareto distributions
- A copula-based hierarchical hybrid loss distribution
Schlagwörter für diesen Artikel
Generalized method of moments;
Ornstein–Uhlenbeck type process;
Lévy basis;
long memory;
stochastic volatility;
superpositions
Artikel in diesem Heft
- Frontmatter
- Moment based estimation of supOU processes and a related stochastic volatility model
- Quasi-Hadamard differentiability of general risk functionals and its application
- Series expansions for convolutions of Pareto distributions
- A copula-based hierarchical hybrid loss distribution
