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arxiv: 1803.01032 · v1 · pith:DQE5VWB5new · submitted 2018-03-02 · 🧮 math.PR

Drift parameter estimation for nonlinear stochastic differential equations driven by fractional Brownian motion

classification 🧮 math.PR
keywords driftfractionalconsistencyderivedifferentialestimatorleastparameter
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We derive the strong consistency of the least squares estimator for the drift coefficient of a fractional stochastic differential system. The drift coeffcient is one-sided dissipative Lipschitz and the driving noise is additive and fractional with Hurst parameter $H \in (\frac{1}{4}, 1)$. We assume that continuous observation is possible. The main tools are ergodic theorem and Malliavin calculus. As a by-product, we derive a maximum inequality for Skorohod integrals, which plays an important role to obtain the strong consistency of the least squares estimator.

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