Gaussian estimation of one-factor mean reversion processes

Abstract

We propose a new alternative method to estimate the parameters in one-factor mean reversion processes based on the maximum likelihood technique. This approach makes use of Euler-Maruyama scheme to approximate the continuous-time model and build a new process discretized. The closed formulas for the estimators are obtained. Using simulated data series, we compare the results obtained with the results published by other authors. © 2013 Freddy H. Marín Sánchez and J. Sebastian Palacio.