Asia-Pacific Financial Markets

, Volume 12, Issue 2, pp 109–141 | Cite as

Inference Methods for Discretely Observed Continuous-Time Stochastic Volatility Models: A Commented Overview



In this paper an overview of inference methods for continuous-time stochastic volatility models observed at discrete times is presented. It includes estimation methods for both parametric and nonparametric models that are completely or partially observed in a variety of situations where the data might be nonlinear functions of the components of the model and/or contaminated with observation noise. In each case, the main reported methods are presented, making emphasis on underlying ideas, theoretical properties of the estimators (bias, consistency, efficient, etc.), and the viability of their implementation to solve actual problems in finance.


stochastic volatility models diffusion processes inference methods 


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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Departamento de Matemática InterdisiplinariaInstituto de Cibernética, Matemética y FísicaLa Habana 4Cuba
  2. 2.Department of Prediction and ControlThe Institute of Statistical MathematicsTokyoJapan

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