We study the problem of parametric estimation for continuously observed stochastic differential equation driven by fractional Brownian motion. Under some assumptions on drift and diffusion coefficients, we construct maximum likelihood estimator and establish its the asymptotic normality and moment convergence of the drift parameter when a small dispersion coefficient vanishes.

翻译：我们研究了由分数布朗运动驱动的连续观测随机微分方程的参数估计问题。在漂移系数和扩散系数满足一定假设条件下，我们构建了最大似然估计量，并证明了当小离散系数趋于零时漂移参数的渐近正态性与矩收敛性。