Sparse and stable Markowitz portfolios

We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e. portfolios with only few active positions), and allows to account for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naive evenly-weighted portfolio which constitutes, as shown in recent literature, a very tough benchmark.Comment: Better emphasis of main result, new abstract, new examples and figures. New appendix with full details of algorithm. 17 pages, 6 figure

OntoJob: Automated Ontology Learning from Labor Market Data

Due to the rapidly changing labor market and the consequently widening information gap between the labor market and education, there is a need for methods that can tackle, or at least ease, the construction of labor market ontologies. The current study set out to examine the viability of Ontology Learning (OL) methods for the (semi-)automated construction of labor market ontologies and / or taxonomies. The purpose of this paper is to propose an unsupervised framework, OntoJob, that can identify and extract from raw vacancy text instances, attributes, and relations, such as job titles, worker qualities, and the non-Taxonomic 'is-A' relations between those concepts, and convert those to an expressive descriptive logic. Evaluation of the extracted worker qualities from OntoJob, using a small sample of 5621 job postings representing 1048 occupations, showed an overall lexical precision of 0.36 and recall of 0.22. </p

Development and application of an algorithm for detecting <i>Phaeocystis globosa</i> blooms in the Case 2 Southern North Sea waters

While mapping algal blooms from space is now well-established, mapping undesirable algal blooms in eutrophicated coastal waters raises further challenge in detecting individual phytoplankton species. In this paper, an algorithm is developed and tested for detecting Phaeocystis globosa blooms in the Southern North Sea. For this purpose, we first measured the light absorption properties of two phytoplankton groups, P. globosa and diatoms, in laboratory-controlled experiments. The main spectral difference between both groups was observed at 467 nm due to the absorption of the pigment chlorophyll c3 only present in P. globosa, suggesting that the absorption at 467 nm can be used to detect this alga in the field. A Phaeocystis-detection algorithm is proposed to retrieve chlorophyll c3 using either total absorption or water-leaving reflectance field data. Application of this algorithm to absorption and reflectance data from Phaeocystis-dominated natural communities shows positive results. Comparison with pigment concentrations and cell counts suggests that the algorithm can flag the presence of P. globosa and provide quantitative information above a chlorophyll c3 threshold of 0.3 mg m-3 equivalent to a P. globosa cell density of 3 × 106 cells L-1. Finally, the possibility of extrapolating this information to remote sensing reflectance data in these turbid waters is evaluated

Big data in economics: evolution or revolution?

The Big Data Era creates a lot of exciting opportunities for new developments in economics and econometrics. At the same time, however, the analysis of large datasets poses difficult methodological problems that should be addressed appropriately and are the subject of the present chapter

Prediction of Mortality in Very Premature Infants: A Systematic Review of Prediction Models

CONTEXT Being born very preterm is associated with elevated risk for neonatal mortality. The aim of this review is to give an overview of prediction models for mortality in very premature infants, assess their quality, identify important predictor variables, and provide recommendations for development of future models. METHODS Studies were included which reported the predictive performance of a model for mortality in a very preterm or very low birth weight population, and classified as development, validation, or impact studies. For each development study, we recorded the population, variables, aim, predictive performance of the model, and the number of times each model had been validated. Reporting quality criteria and minimum methodological criteria were established and assessed for development studies. RESULTS We identified 41 development studies and 18 validation studies. In addition to gestational age and birth weight, eight variables frequently predicted survival: being of average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status. Twelve studies met our methodological criteria, three of which have been externally validated. Low reporting scores were seen in reporting of performance measures, internal and external validation, and handling of missing data. CONCLUSIONS Multivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants. There are validated prediction models for classification and case-mix adjustment. Additional research is needed in validation and impact studies of existing models, and in prediction of mortality in the clinically important subgroup of infants where age and weight alone give only an equivocal prognosis.Stephanie Medlock, Anita C. J. Ravelli, Pieter Tamminga, Ben W. M. Mol, Ameen Abu-Hann

Healthcare choice: Discourses, perceptions, experiences and practices

Policy discourse shaped by neoliberal ideology, with its emphasis on marketisation and competition, has highlighted the importance of choice in the context of healthcare and health systems globally. Yet, evidence about how so-called consumers perceive and experience healthcare choice is in short supply and limited to specific healthcare systems, primarily in the Global North. This special issue aims to explore how choice is perceived and utilised in the context of different systems of healthcare throughout the world, where choice, at least in policy and organisational terms, has been embedded for some time. The articles are divided into those emphasising: embodiment and the meaning of choice; social processes associated with choice; the uncertainties, risks and trust involved in making choices; and issues of access and inequality associated with enacting choice. These sociological studies reveal complexities not always captured in policy discourse and suggest that the commodification of healthcare is particularly problematic

What do women undergoing in vitro fertilization (IVF) understand about their chance of IVF success?

Funding No external funding was used for this study. S.L. is supported by a NHMRC Investigator Grant (APP1195189). R.W. is supported by a NHMRC Investigator Grant (GNT2009767). B.W.M. is supported by a NHMRC Investigator Grant (GNT1176437) and has received research funding and travel funding from MerckPeer reviewedPublisher PD

Ethnic differences in stillbirth and early neonatal mortality in The Netherlands

Background: Ethnic disparities in perinatal mortality are well known. This study aimed to explore the contribution of demographic, socioeconomic, health behavioural and pre-existent medical risk factors among different ethnic groups on fetal and early neonatal mortality. Methods: We assessed perinatal mortality from 24.0 weeks' gestation onwards in 554 234 singleton pregnancies of nulliparous women in the linked Netherlands Perinatal Registry over the period 2000–2006. Logistic regression modelling was used. Results: Considerable ethnic differences in perinatal mortality exist especially in fetal mortality. Maternal age, socioeconomic status and pre-existent diseases could not explain these ethnic differences. Late booking visit could explain some differences. Compared with the Dutch, African women had an increased fetal mortality risk of OR 1.7 (95% CI 1.4 to 2.1); South Asian women, 1.8 (1.4 to 2.3); other non-Western women, 1.3 (1.1 to 1.6) and Turkish/Moroccan women, 1.3 (1.1 to 1.4). The risk on early neonatal mortality was only increased in other non-Western women, OR 1.3 (1.0 to 1.8). Ethnic differences were even present in the women without risk factors including preterm births. Mortality risk for East Asian and other Western women was lower or comparable with the Dutch. Conclusion: Important ethnic differences in fetal mortality exist, especially among women of African and South Asian origin. Ethnic minorities should be more acquainted with the significance of early start of prenatal care. Tailored prenatal care for women with African and South Asian origin seems necessary. More research on underlying cause of deaths is needed by ethnic group.A C J Ravelli, M Tromp, M Eskes, J C Droog, J A M van der Post, K J Jager, B W Mol, J B Reitsm