A least square-type procedure for parameter estimation in stochastic   differential equations with additive fractional noise
  We study a least square-type estimator for an unknown parameter in the drift coefficient of a stochastic differential equation with additive fractional noise of Hurst parameter H>1/2. The estimator is based on discrete time observations of the stochastic differential equation, and using tools from ergodic theory and stochastic analysis we derive its strong consistency. 
Andreas Neuenkirch, Samy Tindel (IECN, INRIA Lorraine / IECN)
math.PR math.ST stat.TH