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Estimation in Gamma-Ornstein –Uhlenbeck Stochastic Volatility Model

In: Parameter Estimation in Stochastic Volatility Models

Author

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  • Jaya P. N. Bishwal

    (University of North Carolina at Charlotte, Department of Mathematics and Statistics)

Abstract

We generalize the Ornstein–Uhlenbeck process to include non-normal innovations. First we study the asymptotic behavior of the ratio estimator of the drift parameter in Gamma-Ornstein–Uhlenbeck volatility process based on observations of the price process. This model captures the stylized facts as it preserves both jumps in the volatility process. We study the behavior of the moment estimators.

Suggested Citation

  • Jaya P. N. Bishwal, 2022. "Estimation in Gamma-Ornstein –Uhlenbeck Stochastic Volatility Model," Springer Books, in: Parameter Estimation in Stochastic Volatility Models, chapter 0, pages 295-305, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-03861-7_6
    DOI: 10.1007/978-3-031-03861-7_6
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