Robust Estimation of Ornstein-Uhlenbeck Parameters

Mr. Timon Kramer
University of Wisconsin-Milwaukee
Graduate Student

The standard estimators of the parameter of the Ornstein-Uhlenbeck process are vulnerable to contamination in the data sets. In this thesis more robust estimators for the parameter of the Ornstein-Uhlenbeck process are proposed which use medians instead of means. The scaling for these estimators is more complex and numerical methods must be used. A possible numerical implementation is described. The performance of the standard estimator and the proposed robust estimators are compared on data sets with different levels
of contamination and different kind of errors. This thesis shows that the proposed robust estimators can be considerably better than the standard estimator on contaminated data sets.

Committee Members:
Profs. Daniel Gervini (advisor), Wei Wei, and David Spade

Please note that this event will be held online via. Microsoft Teams. Click here to view the event flyer.