A least square-type procedure for parameter estimation in stochastic differential equations with additive fractional noise

Andreas Neuenkirch () and Samy Tindel ()

Statistical Inference for Stochastic Processes, 2014, vol. 17, issue 1, 99-120

Abstract: We study a least square-type estimator for an unknown parameter in the drift coefficient of a stochastic differential equation with additive fractional noise of Hurst parameter $$H>1/2$$ H > 1 / 2 . The estimator is based on discrete time observations of the stochastic differential equation, and using tools from ergodic theory and stochastic analysis we derive its strong consistency. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Fractional Brownian motion; Parameter estimation; Least square procedure; Ergodicity; 62M09; 62F12 (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s11203-013-9084-z

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