Risk measures and portfolio estimation

Prof. Thomas Holgersson


Title:  Risk measures and portfolio estimation


Abstract:  Statistical analysis is frequently concerned with the problem of estimating some function of the (inverse) covariance matrix. Common examples include Discriminant functions, Mahalanobis distance and Portfolio weight estimation. Explicit estimators are obtained by minimizing an appropriate risk function. The sampling properties of our estimator is therefore dependent on the particular risk function being used. A number of concerns with different risk functions will be addressed using the global minimum variance portfolio (GMVP) as a particular application.  






Time of Seminar: 
2022-01-20 14:30 to 15:15