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Weighted least-squares estimation for the subcritical Heston process

Part of: Inference from stochastic processes Stochastic processes

Published online by Cambridge University Press:  26 July 2018

M. du Roy de Chaumaray
M. du Roy de Chaumaray*
Affiliation:
Institut de Mathématiques de Bordeaux
*
* Current address: ENSAI, Campus de Ker Lann, Rue Blaise Pascal, BP 37203, 35172 Bruz Cedex, France. Email address: [email protected]
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Abstract

We simultaneously estimate the four parameters of a subcritical Heston process. We do not restrict ourselves to the case where the stochastic volatility process never reaches zero. In order to avoid the use of unmanageable stopping times and a natural but intractable estimator, we use a weighted least-squares estimator. We establish strong consistency and asymptotic normality for this estimator. Numerical simulations are also provided, illustrating the favorable performance of our estimation procedure.

Keywords

Squared radial Ornstein–Uhlenbeck processHeston processparameter estimationweighted least-squares estimateconsistencyasymptotic normality

MSC classification

Primary: 62M05: Markov processes
Secondary: 60G20: Generalized stochastic processes 60G44: Martingales with continuous parameter
Type
Research Papers
Information
Journal of Applied Probability , Volume 55 , Issue 2 , June 2018 , pp. 543 - 558
Copyright
Copyright © Applied Probability Trust 2018 

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