Risikofaktoren und Multifaktormodelle für den Deutschen Aktienmarkt (Risk Factors and Multi-Factor Models for the German Stock Market)

Der deutsche Aktienmarkt sah sich in den letzten 15 Jahren substantiellen Veränderungen gegenüber, welche unter anderem in eine zunehmende Internationalisierung und deutlich erhöhten Streubesitz mündeten. In der vorliegenden Arbeit untersuchen wir, inwieweit dies die aus klassischen Multifaktormodellen bekannten Risikofaktoren beeinflusste. Basierend auf den Renditen derCDAX-Unternehmen von Juli 1996 bis Juni 2011 dokumentieren wir vier wesentliche Ergebnisse. Erstens finden wir eine insignifikant (positive) Marktrisikoprämie, eine signifikant negative Größenprämie (Size Premium), eine signifikant positive Substanzprämie (Value Premium) und eine signifikant positive Momentumprämie (Momentum Premium). Zweitens zeigen sich alle vier Faktoren untereinander nur schwach bzw. negativ korreliert und teilweise mit internationalen Gegenstücken nur schwach korreliert. Drittens zeigt sich, dass Renditen von Aktienportfolios, sortiert nach Marktkapitalisierung und Buch-Marktwert-Verhältnis, durch ein Dreifaktorenmodell nach Fama French (1993) substantiell besser erklärt werden, als durch ein Einfaktormodell in Anlehnung an das klassische Capital Asset Pricing Model. Der zusätzliche Erklärungsbeitrag des Momentumfaktors in Anlehnung an Carhart (1997) ist hingegen marginal. Letztendlich argumentieren wir daher vor dem Hintergrund der bekannten Literatur und unserer Ergebnisse für eine länderspezifische Erweiterung des Capital Asset Pricing Models. -- For the last 15 years, the German stock market has been facing substantial changes that resulted in increasing internationalization and a higher free float. In this paper, we investigate to what extent these changes influenced the well-known risk factors of standard multi-factor models. Based on the returns of all stocks listed in the German composite index CDAX (all domestic companies of the Prime and General Standard of the Frankfurt Stock Exchange) from July 1996 to June 2011, we document four major results: First, we find an insignificant (positive) market risk premium, a significant negative size premium, a significant positive value premium and a significant positive momentum premium. Second, the correlation within all four risk factors is only weakly positive or even negative and with international counterparts only weak. Third, we find that returns of portfolios, sorted by market capitalization and book-to-market equity, are captured substantially better by multi-factor models by Fama/French (1993) or Carhart (1997) than by the one-factor model based on the standard Capital Asset Pricing Model. Finally, after comparing our findings for the last 15 years with the existing literature, we conclude for a country specific extension of the Capital Asset Pricing Model.CAPM,multi-factor models,asset pricing,asset pricing anomalies,anomalies,Fama French,Carhart,risk factors,value,size,momentum,Germany

Factor Zoo (.zip)

The number of factors allegedly driving the cross-section of stock returns has grown steadily over time. We explore how much this “factor zoo” can be compressed, focusing on explaining the available alpha rather than the covariance matrix of factor returns. Our findings indicate that about 15 factors are enough to span the entire factor zoo. This evidence suggests that many factors are redundant but also that merely using a handful of factors, as in common asset pricing models, is insufficient. While the selected factor styles remain persistent, the specific style representatives vary over time, underscoring the importance of continuous factor innovation

PEM Single Cells under Differential Conditions: Full Factorial Parameterization of the ORR and HOR Kinetics and Loss Analysis

The anode and cathode kinetics are parameterized based on differential cell measurements. Systematic parameter variations are evaluated to disentangle the dependencies of the electrochemical impedance spectroscopy (EIS) signatures in H2/H2 mode. We introduce a new CO recovery protocol for both electrodes that enables to accurately characterize the hydrogen oxidation reaction (HOR) kinetics. Then, we demonstrate that a compact Tafel kinetics law captures the oxygen reduction reaction (ORR) kinetics for a full factorial grid of conditions, covering a wide range of relative humidities (rH), temperatures, oxygen partial pressures and current densities. This yields the characteristic activation energy and effective reaction order, and we reconcile models that make different assumptions regarding the rH dependency. Moreover, we analyze O2 transport contributions by steady-state and transient limiting current techniques and heliox measurements. Although the rising uncertainty of loss corrections at high current densities makes it impossible to unambiguously identify an intrinsic potential-dependent change of the Tafel slope, our data support that such effect needs not be considered for steady-state cathodic half-cell potentials above 0.8

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Internally contracted multireference coupled-cluster methods

This thesis details the development of quantum chemical methods for the accurate theoretical description of molecular systems with a complicated electronic structure. In simple cases, a single Slater determinant, in which the electrons occupy a number of energetically lowest molecular orbitals, offers a qualitatively correct model. The widely used coupled-cluster method CCSD(T) efficiently includes electron correlation effects starting from this determinant and provides reaction energies in error by only a few kJ/mol. However, the method often fails when several electronic configurations are important, as, for instance, in the course of many chemical reactions or in transition metal compounds. Internally contracted multireference coupled-cluster methods (ic-MRCC methods) cure this deficiency by using a linear combination of determinants as a reference function. Despite their theoretical elegance, the ic-MRCC equations involve thousands of terms and are therefore derived by the computer. Calculations of energy surfaces of BeH2, HF, LiF, H2O, N2 and Be3 unveil the theory's high accuracy compared to other approaches and the quality of various hierarchies of approximations. New theoretical advances include size-extensive techniques for removing linear dependencies in the ic-MRCC equations and a multireference analog of CCSD(T). Applications of the latter method to O3, Ni2O2, benzynes, C6H7NO and Cr2 underscore its potential to become a new standard method in quantum chemistry.Diese Dissertation erläutert die Entwicklung quantenchemischer Methoden zur genauen theoretischen Beschreibung molekularer Systeme mit komplizierter elektronischer Struktur. In einfachen Fällen bietet eine Slaterdeterminante, in der die Elektronen eine Anzahl energetisch niedrigster Orbitale besetzen, ein qualitativ korrektes Modell. Die weitverbreitete Coupled-Cluster-Methode CCSD(T) berücksichtigt effizient Elektronenkorrelationseffekte ausgehend von dieser Determinante und liefert Reaktionsenergien mit Fehlern im Bereich weniger kJ/mol. Die Methode versagt allerdings häufig, wenn mehrere Elektronenkonfigurationen wichtig sind, wie zum Beispiel im Verlauf vieler chemischer Reaktionen oder in Übergangsmetallverbindungen. Intern kontrahierte Multireferenz-Coupled-Cluster-Methoden (ic-MRCC-Methoden) beheben dieses Defizit durch Verwendung einer Linearkombination von Determinanten als Referenzfunktion. Trotz ihrer theoretischen Eleganz beinhalten die ic-MRCC-Gleichungen Tausende von Termen und werden daher mit dem Computer hergeleitet. Berechnungen der Energieflächen von BeH2, HF, LiF, H2O, N2 and Be3 enthüllen die hohe Genauigkeit der Theorie im Vergleich zu anderen Ansätzen und die Qualität diverser Hierarchien von Näherungen. Neue theoretische Fortschritte umfassen größenextensive Techniken zur Beseitigung linearer Abhängigkeiten in den ic-MRCC-Gleichungen und ein Multireferenz-Analogon zu CCSD(T). Anwendungen der letztgenannten Methode auf die Moleküle O3, Ni2O2, Didehydrobenzole, C6H7NO and Cr2 unterstreichen ihr Potenzial, eine neue Standardmethode in der Quantenchemie zu werden

The idiosyncratic momentum anomaly

This paper seeks to uncover the drivers of the idiosyncratic momentum anomaly. We show that: (i) idiosyncratic momentum is a distinct phenomenon that exists next to conventional momentum and is not explained by it; (ii) idiosyncratic momentum is priced in the cross-section of stock returns after controlling for established and recently proposed asset pricing factors, including the ones that explain a host of momentum-related anomalies; (iii) some of the prominent explanations for the momentum premium, such as crash risk, and investor overconfidence and overreaction linked to market states and dynamics cannot explain idiosyncratic momentum profits; (iv) long-term return dynamics of idiosyncratic momentum support the underreaction hypothesis for its existence; (v) idiosyncratic momentum generates robust returns across a range of developed and emerging markets

Surprise in short interest

We extract the news component of short-selling activity by accounting for important cross-sectional, distributional differences in short interest data. The resulting measure of surprise in short interest negatively predicts the cross section of both U.S. and international equity returns. Our results also indicate that this predictability originates from short sellers’ informed trading on mispricing and investors’ underreaction due to their anchoring on past short interest. Finally, consistent with the notion of costly arbitrage, the return predictability is stronger among illiquid, volatile stocks and stocks with high information uncertainty, but importantly, unrelated to short-selling frictions.</p

Full Factorial In Situ Characterization of Ionomer Properties in Differential PEM Fuel Cells

The performance optimization of membrane electrode assemblies of PEM fuel cells requires accurate characterization and modelling of the relevant mechanisms. In this paper, the ionomer conductivities and permeation properties are characterized in situ in a differential cell setup by varying the operating conditions in a full factorial fashion in H2/N2 mode. Voltammetry methods are validated against online gas analysis and then used to record H2 crossover. The membrane and cathode catalyst layer (CCL) resistances are deconvoluted by fitting transmission line models (TLM) to electrochemical impedance spectroscopy (EIS) data. Based on this, we estimate activation energies of 20 kJ mol−1 for the H2 permeation, 7 kJ mol−1 for the membrane resistance and 9 kJ mol−1 for the ionomer resistance in the CCL. Through EIS measurements under load (H2/O2), we also evaluate the change in the ionomer resistances in course of water production. This effect is most pronounced under cold and dry conditions and implies that a subtraction of the protonic loss contributions from polarization curves only based on EIS measurements obtained in H2/N2 mode is not possible