Least squares estimators for discretely observed stochastic processes driven by small fractional noise

S. Nakajima; S. Nakamura; Y. Shimizu

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arXiv · 2201.08462

Least squares estimators for discretely observed stochastic processes driven by small fractional noise

S. Nakajima·S. Nakamura·Y. Shimizu

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Abstract

We study the problem of parameter estimation for discretely observed stochastic differential equations driven by small fractional noise. Under some conditions, we obtain strong consistency and rate of convergence of the least square estimator(LSE) when small dispersion coefficient converges to 0 and sample size converges to infty.

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S. Nakajima, S. Nakamura, Y. Shimizu. 2022-01-20. Least squares estimators for discretely observed stochastic processes driven by small fractional noise. https://arxiv.org/abs/2201.08462

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