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Maximum likelihood estimation of mean reverting processes The Ornstein-Uhlenbeck mean reverting (OUMR) model is a Gaussian model well suited for maximum likelihood (ML) methods Alternative methods include least squares (LS) regression of discrete autoregressive versions of the OUMR model and methods of moments (MM)
Lecture 6 More General Stochastic Processes Lecture 6 More General Stochastic Processes The Ornstein-Uhlenbeck process is a di usion process that was rst introduced to help model the velocity of a particle undergoing Brownian motion
Ornstein-Uhlenbeck - Imperial College London The basic model for processes of this type is given by the (linear) stochastic differential equation dV = V dt + dW; whose solution is called the Ornstein-Uhlenbeck (velocity) process with re-laxation time 1= and diffusion coefficient D := 1 2= 2
The Ornstein-Uhlenbeck process - inla. r-inla-download. org The Ornstein-Uhlenbeck process is the continuous-time analogue to the discrete AR(1) model (for positive lag-one correlation only), but they are parameterised slightly different