Vice versus virtue investing around the world

This paper assumes the role of advocatus diaboli by testing whether an investment in sin stocks can financially outperform an investment in socially responsible stocks. We create a set of global, regional, and domestic portfolios consisting of a large number of stocks belonging to what could be labeled as a sextet of sin: adult entertainment, alcohol, gambling, nuclear power, tobacco, and weapons. We assess the performance of sin stocks against well-known benchmarks, and rerun the identical assessment for socially responsible stocks. We find no compelling evidence that sin stocks, or socially responsible stocks outperform or underperform, and establish this result in several ways. Consistent with this finding, a hedge portfolio long in sin stocks and short in socially responsible stocks does not outperform the market, either. However, sin stocks are substantially tilted towards value, bear less market risk with an average beta below one, and are prone to momentum relative to socially responsible stocks.     

Measuring the affective quality of life of university students: The validation of an instrument

The purpose of this study is to develop an instrument for measuring the quality of life of university students, and to report its validity and reliability. The study used a representative sample of undergraduate and graduate students in the faculty of education at a major Canadian university. The construct validity of the scales was assessed by Piazza's technique for the analysis of attitude items. The findings supported conceptualizing the quality of life of university students in four dimensions including Positive Affect, Interaction with Students, Interaction with Professors, and Negative Affect. The alpha reliabilities of these scales ranged from 0.75 to 0.93. Some potential applications of this instrument for understanding educational attainment, as well as for the evaluation of university departments and faculties, are mentioned.     

The invisible body of queer youth: identity and health in the margins of lesbian and trans communities

How does complexity in gender and sexual identity construction and partnering practices generate unique vulnerabilities for queer-identified youth? We present two case studies from an ongoing ethnographic study of LGBTQ youth development: "Samantha," a queer-identified woman partnered with a transgender man, and "Reid," a queer-identified transgender man who has declined medical gender transitioning and who partners with lesbians and gay men. We consider the implications of these youths' locations on the margins of both lesbian and transgender communities and the challenges in providing health care and support services for queer-identified youth.     

Supply Chain Conflict Due to Store Brands: The Value of Wholesale Price Commitment in a Retail Supply Chain*

Store brands are of increasing importance in retail supply chains, often causing channel conflict, as the retailer's product directly competes with the manufacturer's national brand. Extant research on the resulting channel interactions either assumes the national brand manufacturer can credibly commit to maintaining a wholesale price or that he lacks such ability. However, these two scenarios imply very different supply chain interactions, as only a national brand manufacturer with commitment ability can strategically adjust a national brand wholesale price to prevent a store brand introduction by the retailer. We specifically analyze the impact of this assumption on the manufacturer, the retailer, and the customers. We determine when long‐term contracts that provide the manufacturer with such commitment ability can improve supply chain profitability.     

Time series models associated with Mittag-Leffler type distributions and its properties

ABSTRACT

We have provided a fractional generalization of the Poisson renewal processes by replacing the first time derivative in the relaxation equation of the survival probability by a fractional derivative of order α(0 < α ? 1). A generalized Laplacian model associated with the Mittag-Leffler distribution is examined. We also discuss some properties of this new model and its relevance to time series. Distribution of gliding sums, regression behaviors, and sample path properties are studied. Finally we introduce the q-Mittag-Leffler process associated with the q-Mittag-Leffler distribution.     

Segmentation,alignment and statistical analysis of biosignals with application to disease classification

We present a novel methodology for a comprehensive statistical analysis of approximately periodic biosignal data. There are two main challenges in such analysis: (1) the automatic extraction (segmentation) of cycles from long, cyclostationary biosignals and (2) the subsequent statistical analysis, which in many cases involves the separation of temporal and amplitude variabilities. The proposed framework provides a principled approach for statistical analysis of such signals, which in turn allows for an efficient cycle segmentation algorithm. This is achieved using a convenient representation of functions called the square-root velocity function (SRVF). The segmented cycles, represented by SRVFs, are temporally aligned using the notion of the Karcher mean, which in turn allows for more efficient statistical summaries of signals. We show the strengths of this method through various disease classification experiments. In the case of myocardial infarction detection and localization, we show that our method compares favorably to methods described in the current literature.     

Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods

ABSTRACT

The optimal learner for prediction modeling varies depending on the underlying data-generating distribution. Super Learner (SL) is a generic ensemble learning algorithm that uses cross-validation to select among a ‘library’ of candidate prediction models. While SL has been widely studied in a number of settings, it has not been thoroughly evaluated in large electronic healthcare databases that are common in pharmacoepidemiology and comparative effectiveness research. In this study, we applied and evaluated the performance of SL in its ability to predict the propensity score (PS), the conditional probability of treatment assignment given baseline covariates, using three electronic healthcare databases. We considered a library of algorithms that consisted of both nonparametric and parametric models. We also proposed a novel strategy for prediction modeling that combines SL with the high-dimensional propensity score (hdPS) variable selection algorithm. Predictive performance was assessed using three metrics: the negative log-likelihood, area under the curve (AUC), and time complexity. Results showed that the best individual algorithm, in terms of predictive performance, varied across datasets. The SL was able to adapt to the given dataset and optimize predictive performance relative to any individual learner. Combining the SL with the hdPS was the most consistent prediction method and may be promising for PS estimation and prediction modeling in electronic healthcare databases.     

Führungsstile – Evaluation einer Nebenaufgabe im Development Center

To asses six different leadership styles we employed a questionnaire during the development center in a manufacturing firm. Analysing the questionnaire indicates its reliability, scalability, economy, usefulness and fairness. An explorative factor analysis supports the factorial validity. A content analysis provides evidence that the transformational leadership style is perceived as the most positive and the authoritarian leadership style as the most negative one. Furthermore, we found transformational leadership style positively correlated with an aggregated measure for the competence extraversion.