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

2022/01/20 by S. Nakajima, Nakajima, S., S. Nakamura +3
Economics, Econometrics and Finance · Mathematics · #FOS: Mathematics #Statistical Methods and Inference #Statistics Theory (math.ST) #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.2201.08462

openalex publication_date 2022/01/20 · openalex created_date 2022/04/03 · openalex updated_date 2026/07/28

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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