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

Emanuele Taufer, Nikolai Leonenko and Marco Bee

No 907, DISA Working Papers from Department of Computer and Management Sciences, University of Trento, Italy

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. In this paper we propose a characteristic function-based estimation method for non-Gaussian Ornstein-Uhlenbeck-based stochastic volatility models. After deriving explicit expressions of the characteristic functions for various cases of interest we analyze the asymptotic properties of the estimators and evaluate their performance by means of a simulation experiment. Finally, a real-data application shows that the superposition of two Ornstein-Uhlenbeck processes gives a good approximation to the dependence structure of the process.

Keywords: ornstein-uhlenbeck process; lévy process; stochastic volatility; characteristic function estimation (search for similar items in EconPapers)
Pages: 30 pages
Date: 2009-10, Revised 2009-12-02
New Economics Papers: this item is included in nep-ecm and nep-ets
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Journal Article: Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models (2011)
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