Parameter Estimation in Stochastic Differential Equation Driven by Fractional Brownian Motion

Paper presents a methodology for estimating the parameters of stochastic differential equation (SDE) driven by fractional Brownian motion (fBm). The main idea is connected with simulated maximum likelihood. To develop this methodology two important questions: generation the fBm sample paths with different Hurst parameter values and Hurst parameter estimation methods are studied. Effectiveness of methodology is analyzed through Monte Carlo simulations.