Improved nonparametric estimation of the drift in diffusion processes
Evgeny Pchelintsev, Svyatoslav Perelevskiy, Irina Makarova
TL;DR
This paper introduces a robust adaptive nonparametric method for estimating the drift coefficient in diffusion processes, utilizing improved weighted least squares and establishing sharp oracle inequalities for the risk.
Contribution
It presents a novel adaptive model selection procedure with improved weighted least squares estimates for drift estimation in diffusion processes.
Findings
Derived sharp oracle inequalities for the robust risk.
Developed an adaptive estimation procedure with improved accuracy.
Abstract
In this paper, we consider the robust adaptive non parametric estimation problem for the drift coefficient in diffusion processes. An adaptive model selection procedure, based on the improved weighted least square estimates, is proposed. Sharp oracle inequalities for the robust risk have been obtained.
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Taxonomy
TopicsStatistical Methods and Inference · Advanced Control Systems Optimization · Stochastic processes and financial applications