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Statistical Inference for Stochastic Processes

, Volume 21, Issue 3, pp 553–567 | Cite as

Moderate deviations for parameters estimation in a geometrically ergodic Heston process

  • Marie du Roy de Chaumaray
Article
  • 77 Downloads

Abstract

We establish a moderate deviation principle for the maximum likelihood estimator of the four parameters of a geometrically ergodic Heston process. We also obtain moderate deviations for the maximum likelihood estimator of the couple of dimensional and drift parameters of a generalized squared radial Ornstein–Uhlenbeck process. We restrict ourselves to the most tractable case where the dimensional parameter satisfies \(a>2\) and the drift coefficient is such that \(b<0\). In contrast to the previous literature, parameters are estimated simultaneously.

Keywords

Parameter estimation Maximum likelihood estimator Moderate deviation principle Heston process 

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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Institut de Mathématiques de Bordeaux UMR 5251Université de BordeauxTalence CedexFrance

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