Programme:

Tuesday:

11:00 Ivan Žežula, On matrix mean testing in quadratic subspaces model.

Wednesday:

10:30 Stepan Mazur,Tangency portfolio weights under a skew-normal model in small and large dimensions. 

Abstract: In this talk, we investigate the distributional properties of the estimated tangency portfolio (TP) weights assuming that the asset returns follow a matrix variate closed skew-normal distribution. We establish a stochastic representation of the linear combination of the estimated TP weights that fully characterizes its distribution. Using the stochastic representation we derive the mean and variance of the estimated weights of TP which are of key importance in portfolio analysis. Furthermore, we provide the asymptotic distribution of the linear combination of the estimated TP weights under the high-dimensional asymptotic regime, i.e., the dimension of the portfolio p and the sample size n tend to infinity such that p/n→c∈(0,1). A good performance of the theoretical findings is documented in the simulation study. 

17:00 Malwina Mrowińska, Monika Mokrzycka, Comparison of autoregressive covariance matrix estimators.

Thursday:

10:00 Mateusz John, Estimation and testing of covariance matrices belonging to quadratic subspaces. 

20:00 Katarzyna Filipiak, Simo Puntanen, Simple answers to complex questions related to BLUEs and BLUPs.

Friday:

10:00 Katarzyna Filipiak, Estimation of compound symmetry structure under t distribution.

11:00 Daniel Klein, Fisher information matrix under matrix variate elliptical distribution.