Multilevel models are widely used in education and social science research. However, the effects of omitting levels of the hierarchy on the variance decomposition and the clustering effects have not been well documented. This paper discusses how omitting one level in three-level models affects...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

Cluster analysis by k-means algorithm by R programming applied for the geological data analysis is the scope of the presented paper. The research object is the Mariana Trench, a hadal trench located in west Pacific Ocean. The study evaluates the similarity of the geological data by the analysis...

We examine the impact of performance groups on the estimation of therelative importance of ¯rm, industry and other e®ects on corporate performance.Performance groups comprise ¯rms from the same industry with asimilar performance over a longer period of time. We present a statisticalmethod...

Die klassische, von Markowitz entwickelte, Portfoliotheorie basiert auf spezifischen Risikomaßen, der Renditevarianz bzw. der Renditestandardabweichung. Diese Risikomaße messen primär die Volatilität der Renditeentwicklung...

Applied researchers often test for the difference of the variance of two investment strategies;in particular, when the investment strategies under consideration aim to implementthe global minimum variance portfolio. A popular tool to this end is the F-test for theequality of variances....

It is well known that mean-variance portfolio selection is a time-inconsistent optimalcontrol problem in the sense that it does not satisfy Bellman’s optimalityprinciple and therefore the usual dynamic programming approach fails. We developa time-consistent formulation of this problem, which...

We derive an explicit formula of the Watts’ poverty index, in terms of parametersof bivariate lognormal distributions of price indices and nominal livingstandards. This result enables us to: analyse the contributions of the distributionsof prices and nominal living standards in poverty;...

This study explores the information content of HML and SMB by linking the Fama-French factors toshocks in the state variables which predict future investment opportunities. It shows that the HMLfactor contains information about shocks to default spread. Moreover, the Fama-French modelexplains...