A Behavioral Portfolio Analysis of Retirement Portfolios in Germany

To most individuals saving for retirement is the number one financial goal. However, it reveals a complex task and induces serious behavioral problems which cannot be explained by traditional economic theory. This paper investigates the role of behavioral asset selection on retirement portfolios in Germany. Simulated behavioral portfolios show (i) an impact of emotions since pessimism (optimism) induces the most conservative (aggressive) portfolio, (ii) concentrated portfolios with a large position in only one secure asset and a small position in a risky portfolio, and (iii) a large difference to mean-variance portfolios in terms of level of diversification. I conclude that behavioral portfolio theory has remarkably power in understanding, describing and selecting retirement portfolios in Germany. The results have several implication for financial planning, e.g. for an ``auto-pilot'' solution to encourage people to more retirement saving.behavioral portfolio choice, decision making under risk, retirement portfolios

Published stock recommendations as investor sentiment in the near-term stock market

This paper investigates the role of published stock recommendations in print and online media as investor sentiment in the near-term German stock market. In line with extant literature on other sentiment measures, vector autoregressions reveal that past stock returns drive today's sentiment, but not the other way around, and that sentiment is a powerful predictor of itself. In particular, sentiment based on printed analyst recommendations follows reversals, that is, when analysts face a stock market downturn, they see a buying opportunity and become optimistic.analyst forecasts, investor sentiment, media content, VAR analysis

Essays on Behavioral Portfolio Management: Theory and Application

Gegenstand der Arbeit ist das Portfoliowahlproblem aus verhaltenswissenschaftlicher Sicht, bei dem Risiko als Ausfallwahrscheinlichkeit verstanden wird. Unter Berücksichtigung verhaltenswissenschaftlicher Elemente, u.a. mentale Kontenbildung und Emotionen, werden sowohl empirische als auch modelltheoretische Fragestellungen untersucht. Methodisch lässt sich die Arbeit in den Bereich der stochastischen linearen Optimierung einordnen.The aim of this dissertation is the behavioral portfolio selection problem in which risk is measured as the probability of shortfall. Using behavioral elements, such as mental accounting, and emotions and cognition, this dissertation investigates empirical issues related to behavioral asset allocation and theoretical issues related to stochastic linear programming

Accountability and Transparency of Entrepreneurial Journalism: Unresolved ethical issues in crowdfunded journalism projects

Crowdfunding is a new business model in which journalists rely—and depend—on (micro-) payments by a large number of supporters to finance their reporting. In this form of entrepreneurial journalism the roles of publisher, fundraiser and journalist often overlap. This raises questions about conflicts of interest, accountability and transparency. The article presents the results of selected case studies in four different European countries—Germany (Krautreporter), Italy (Occhidellaguerra), the United Kingdom (Contributoria) and the Netherlands (De Correspondent)—as well as one US example (Kickstarter). The study used a two-step methodological approach: first a content analysis of the websites and the Twitter accounts with regard to practices of media accountability, transparency and user participation was undertaken. The aim was to investigate how far ethical challenges in crowdfunded entrepreneurial journalism are accounted for. Second, we present findings from semi-structured interviews with journalists from each crowdfunding. The study provides evidence about the ethical issues in this area, particularly in relation to production transparency and responsiveness. The study also shows that in some cases of crowdfunding (platforms), accountability is outsourced and implemented only through the audience participation

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine

Stable U(IV) Complexes Form at High-Affinity Mineral Surface Sites

Uranium (U) poses a significant contamination hazard to soils, sediments, and groundwater due to its extensive use for energy production. Despite advances in modeling the risks of this toxic and radioactive element, lack of information about the mechanisms controlling U transport hinders further improvements, particularly in reducing environments where UIV predominates. Here we establish that mineral surfaces can stabilize the majority of U as adsorbed UIV species following reduction of UVI. Using X-ray absorption spectroscopy and electron imaging analysis, we find that at low surface loading, UIV forms inner-sphere complexes with two metal oxides, TiO2 (rutile) and Fe3O4 (magnetite) (at <1.3 U nm–2 and <0.037 U nm–2, respectively). The uraninite (UO2) form of UIV predominates only at higher surface loading. UIV–TiO2 complexes remain stable for at least 12 months, and UIV–Fe3O4 complexes remain stable for at least 4 months, under anoxic conditions. Adsorbed UIV results from UVI reduction by FeII or by the reduced electron shuttle AH2QDS, suggesting that both abiotic and biotic reduction pathways can produce stable UIV–mineral complexes in the subsurface. The observed control of high-affinity mineral surface sites on UIV speciation helps explain the presence of nonuraninite UIV in sediments and has important implications for U transport modeling

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing for personalized oncology

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Long-read single-cell RNA sequencing (scRNA-seq), capturing full-length transcripts, lacked the depth to provide this information so far. Here, we increased the PacBio sequencing depth to 12,000 reads per cell, leveraging multiple strategies, including artifact removal and transcript concatenation, and applied the technology to samples from three human ovarian cancer patients. Our approach captured 152,000 isoforms, of which over 52,000 were novel, detected cell type- and cell-specific isoform usage, and revealed differential isoform expression in tumor and mesothelial cells. Furthermore, we identified gene fusions, including a novel scDNA sequencing-validated IGF2BP2::TESPA1 fusion, which was misclassified as high TESPA1 expression in matched short-read data, and called somatic and germline mutations, confirming targeted NGS cancer gene panel results. With multiple new opportunities, especially for cancer biology, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine

CEACAM1-4L promotes anchorage-independent growth in melanoma

Widespread metastasis is the leading course of death in many types of cancer, including malignant melanoma. The process of metastasis can be divided into a number of complex cell biological events, collectively termed the invasion-metastasis cascade. Previous reports have characterized the capability of anchorage-independent growth of cancer cells in vitro as a key characteristic of highly aggressive tumor cells, particularly with respect to metastatic potential. Biological heterogeneity as well as drastic alterations in cell adhesion of disseminated cancer cells support escape mechanisms for metastases to overcome conventional therapies. Here we show that exclusively the carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) splice variant CEACAM1-4L supports an anchorage-independent signature in malignant melanoma. These results highlight important variant-specific modulatory functions of CEACAM1 for metastatic spread in patients suffering malignant melanoma

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Abstract Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine