Characteristic function estimation of Ornstein–Uhlenbeck-based stochastic volatility models

Taufer, Emanuele, Leonenko, Nikolai N. ORCID: https://orcid.org/0000-0003-1932-4091 and Bee, Marco 2011. Characteristic function estimation of Ornstein–Uhlenbeck-based stochastic volatility models. Computational Statistics & Data Analysis 55 (8) , pp. 2525-2539. 10.1016/j.csda.2011.02.016

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Abstract

Continuous-time stochastic volatility models are becoming increasingly popular in finance because of their flexibility in accommodating most stylized facts of financial time series. However, their estimation is difficult because the likelihood function does not have a closed-form expression. A characteristic function-based estimation method for non-Gaussian Ornstein–Uhlenbeck-based stochastic volatility models is proposed. Explicit expressions of the characteristic functions for various cases of interest are derived. The asymptotic properties of the estimators are analyzed and their small-sample performance is evaluated by means of a simulation experiment. Finally, two real-data applications show that the superposition of two Ornstein–Uhlenbeck processes gives a good approximation to the dependence structure of the process.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	Ornstein–Uhlenbeck process; Lévy process; Stochastic volatility; Characteristic function estimation
Publisher:	Elsevier
ISSN:	0167-9473
Last Modified:	18 Oct 2022 13:27
URI:	https://orca.cardiff.ac.uk/id/eprint/13894

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