Spatio-temporal statistical analysis of the carbon budget of the terrestrial ecosystem

The Net Ecosystem Exchange describes the net carbon dioxide flux between an ecosystem and the atmosphere and is a key quantity in climate change studies and in political negotiations. This paper provides a spatio-temporal statistical framework, which is able to infer the Net Ecosystem Exchange from remotely-sensed carbon dioxide ground concentrations together with data on the Normalized Difference Vegetation Index, the Gross Primary Production and the land cover classification. The model is based on spatial and temporal latent random effects, that act as space–time varying coefficients, which allows for a flexible modeling of the spatio-temporal auto- and cross-correlation structure. The intra- and inter-annual variations of the Net Ecosystem Exchange are evaluated and dynamic maps are provided on a nearly global grid and in intervals of 16 days.     

Compositional Tables Analysis in Coordinates

Compositional tables – a continuous counterpart to the contingency tables – carry relative information about relationships between row and column factors; thus, for their analysis, only ratios between cells of a table are informative. Consequently, the standard Euclidean geometry should be replaced by the Aitchison geometry on the simplex that enables decomposition of the table into its independent and interactive parts. The aim of the paper is to find interpretable coordinate representation for independent and interaction tables (in sense of balances and odds ratios of cells, respectively), where further statistical processing of compositional tables can be performed. Theoretical results are applied to real‐world problems from a health survey and in macroeconomics.     

On the existence of unbiased estimators for the portfolio weights obtained by maximizing the Sharpe ratio

We consider the problem of estimating the portfolio weights obtained by maximizing the Sharpe ratio. Assuming that the underlying asset returns are independent and multivariate normally distributed, Okhrin and Schmid (J. Econom. 134:235–256, 2006) showed that the frequently used sample estimators of these weights do not have a first moment. This paper proves that an unbiased estimator of the Sharpe ratio portfolio weights does not exist at all. Moreover, we show that there is no asymptotically unbiased estimator of these weights within the family of estimators which are bounded by cylinder functions.     

Statistical inference of the efficient frontier for dependent asset returns

In the paper we consider the three characteristics of the efficient frontier. These characteristics are estimated by substituting the unknown parameters by the sample counterparts. Assuming that the asset returns follow a stationary Gaussian process it is shown that the estimated characteristics are asymptotically normally distributed. This result is used to determine the joint asymptotic distribution of the estimated portfolio return and the estimated portfolio variance in the case of the expected utility portfolio and the tangency portfolio, respectively.