Gaussian Estimation of One-Factor Mean Reversion Processes

Abstract EN

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.