Analysts' dividend forecasts, portfolio selection, and market risk premia

The most relevant practical impediment to an application of the Markowitz portfolio selection approach is the problem of estimating return moments, in particular return expectations. We analyze the consequences of using return estimates implied by analysts' dividend forecasts under the explicit notion of taxes and non-flat term structures of interest rates and achieve quite good performance results. As a by-product, these results cast some doubt upon the adequacy of estimating market risk premia with implied returns, because estimation techniques with good performance results are hardly suited to describe market expectations. --analysts' forecasts,CAPM,implied returns,market risk premium,portfolio optimization,return estimation

Estimation and model selection for dynamic biomedical images

Compartment models are a frequently used tool for imaging data gained with medical and biological imaging techniques. The solutions of the differential equations derived from a compartment model provide nonlinear parametric functions, based on which the behavior of a concentration of interest over time can be described. Often, the number of compartments in a compartment model is unknown. As the model complexity itself, which is, the number of compartments, is certainly an important information, it is desirable to estimate it from the observed data. Additionally, the unknown parameters have to be estimated. Therefore, methods dealing with both the parameter estimation and model selection in compartment models are needed. The methods proposed in this thesis are motivated by two applications from the field of medical and biological imaging. In the first application, the quantitative analysis of Fluorescence recovery after photobleaching (FRAP) data, compartment models are used in order to gain insight into the binding behavior of molecules in living cells. As a first approach, we developed a Bayesian nonlinear mixed-effects model for the analysis of a series of FRAP images. Mixed-effect priors are defined on the parameters of the nonlinear model, which is a novel approach. With the proposed model, we get parameter estimates and additionally gain information about the variability between nuclei, which has not been studied so far. The proposed method was evaluated on half-nucleus FRAP data, also in comparison with different kinds of fixed-effects models. As a second approach, a pixelwise analysis of FRAP data is proposed, where information from the neighboring pixels is included into the nonlinear model for each pixel. This is innovative as the existing models are suitable for the analysis of FRAP data for some regions of interest only. For the second application, the quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast, we use a compartment model which describes the exchange of blood between different, well-mixed compartments. In the analysis of such data, the number of compartments allows conclusions about the heterogeneity of cancerous tissue. Therefore, an estimation and model selection approach based on boosting, with which the number of compartments and the unknown parameters can be estimated at the voxel level, is proposed. In contrast to boosting for additive regression, where smoothing approaches are used, boosting in nonlinear parametric regression as described in this thesis is a novel approach. In an extension of this approach, the spatial structure of an image is taken into account by penalizing the differences in the parameter estimates of neighboring voxels. The evaluation of the method was done in simulation studies, as well as in the application to data from a breast cancer study. The majority of the program code used in the three approaches was newly developed in the programming languages R and C. Based on that code, two R packages were built

German Experiences in Police Building in Afghanistan

政治学 / Political Science and International RelationsSince the Petersberg Conference in 2001 Germany has been involved in the police building in Afghanistan. From 2001 until EUPOL Afghanistan took over responsibility in June 2007 Germany was the Lead /Key Partner Nation for police reform. During this time the German Police Project Office (GPPO) was in place, which switched over to German Police Project Team (GPPT) in June 2007. In addition to EUPOL Afghanistan the GPPT is the current bilateral project organisation where the German police officers are deployed.The purpose of this paper is to point out the German experiences working in the above mentioned structures/organisations for police reform of the Afghan police forces.Prepared for the GRIPS State Building Workshop 2010: Organizing Police Forces in Post-Conflict Peace-Support Operations, January 27-28th, 201

Einsatz inflationsindexierter Anleihen im Asset-Liability-Management

Es wird dargelegt, dass das im Rahmen des Asset-Liability-Managements häufig gewählte Immunisierungsverfahren des Durationsmatch unter Verwendung der traditionellen Yieldbeta-Methode nur dann sachgerecht eingesetzt werden kann, wenn das betrachtete Unternehmen keinen sicheren realen und damit der Inflationsunsicherheit unterliegenden nominalen Zahlungsverpflichtungen gegenübersteht. Vor diesem Hintergrund wird die Yield-beta-Methode erweitert, um das Verfahren auch auf sichere reale Zahlungsverpflichtungen anwenden zu können, die häufig bei Versicherungen anzutreffen sind. Für die Umsetzung benötigt man zusätzlich Anlageinstrumente, die sichere reale Einzahlungsüberschüsse verbriefen. Für den vorliegenden Beitrag werden inflationsindexierte Anleihen gewählt, die jüngst auch von der Bundesrepublik Deutschland emittiert wurden. Verschiedene Typen inflationsindexierter Anleihen werden vorgestellt, und ihr Einsatz im Asset-Liability-Management wird dargelegt. --Asset-Liability-Management,inflationsindexierte Anleihen,Durationsmatch,BPV-Match,Yield-beta-Methode

Bayesian mixed-effect models for the analysis of a series of FRAP images

The binding behavior of molecules in nuclei of living cells can be studied through the analysis of images from fluorescence recovery after photobleaching experiments. However, there is still a lack of methodology for the statistical evaluation of FRAP data, especially for the joint analysis of multiple dynamic images. We propose a hierarchical Bayesian nonlinear model with mixed-effect priors based on local compartment models in order to obtain joint parameter estimates for all nuclei as well as to account for the heterogeneity of the nuclei population. We apply our method to a series of FRAP experiments of DNA methyltransferase 1 tagged to green fluorescent protein expressed in a somatic mouse cell line and compare the results to the application of three different fixed-effects models to the same series of FRAP experiments. With the proposed model, we get estimates of the off-rates of the interactions of the molecules under study together with credible intervals, and additionally gain information about the variability between nuclei. The proposed model is superior to and more robust than the tested fixed-effects models. Therefore, it can be used for the joint analysis of data from FRAP experiments on various similar nuclei

Bayesian mixed-effect models for the analysis of a series of FRAP images

The binding behavior of molecules in nuclei of living cells can be studied through the analysis of images from fluorescence recovery after photobleaching experiments. However, there is still a lack of methodology for the statistical evaluation of FRAP data, especially for the joint analysis of multiple dynamic images. We propose a hierarchical Bayesian nonlinear model with mixed-effect priors based on local compartment models in order to obtain joint parameter estimates for all nuclei as well as to account for the heterogeneity of the nuclei population. We apply our method to a series of FRAP experiments of DNA methyltransferase 1 tagged to green fluorescent protein expressed in a somatic mouse cell line and compare the results to the application of three different fixed-effects models to the same series of FRAP experiments. With the proposed model, we get estimates of the off-rates of the interactions of the molecules under study together with credible intervals, and additionally gain information about the variability between nuclei. The proposed model is superior to and more robust than the tested fixed-effects models. Therefore, it can be used for the joint analysis of data from FRAP experiments on various similar nuclei

Tyrosine 263 in Cyanobacterial Phytochrome Cph1 Optimizes Photochemistry at the prelumi-R→lumi-R Step

We report a low-temperature fluorescence spectroscopy study of the PAS-GAF-PHY sensory module of Cph1 phytochrome, its Y263F mutant (both with known 3D structures) as well as Y263H and Y263S to connect their photochemical parameters with intramolecular interactions. None of the holoproteins showed photochemical activity at low temperature, and the activation barriers for the Pr→lumi-R photoreaction (2.5-3.1 kJ mol(-1)) and fluorescence quantum yields (0.29-0.42) were similar. The effect of the mutations on Pr→Pfr photoconversion efficiency (ΦPr→Pfr) was observed primarily at the prelumi-R S0 bifurcation point corresponding to the conical intersection of the energy surfaces at which the molecule relaxes to form lumi-R or Pr, lowering ΦPr→Pfr from 0.13 in the wild type to 0.05-0.07 in the mutants. We suggest that the Ea activation barrier in the Pr* S1 excited state might correspond to the D-ring (C19) carbonyl - H290 hydrogen bond or possibly to the hindrance caused by the C13(1) /C17(1) methyl groups of the C and D rings. The critical role of the tyrosine hydroxyl group can be at the prelumi-R bifurcation point to optimize the yield of the photoprocess and energy storage in the form of lumi-R for subsequent rearrangement processes culminating in Pfr formation