Mean-risk models using two risk measures: A multi-objective approach

This paper proposes a model for portfolio optimisation, in which distributions are characterised and compared on the basis of three statistics: the expected value, the variance and the CVaR at a specified confidence level. The problem is multi-objective and transformed into a single objective problem in which variance is minimised while constraints are imposed on the expected value and CVaR. In the case of discrete random variables, the problem is a quadratic program. The mean-variance (mean-CVaR) efficient solutions that are not dominated with respect to CVaR (variance) are particular efficient solutions of the proposed model. In addition, the model has efficient solutions that are discarded by both mean-variance and mean-CVaR models, although they may improve the return distribution. The model is tested on real data drawn from the FTSE 100 index. An analysis of the return distribution of the chosen portfolios is presented

An attempt to observe economy globalization: the cross correlation distance evolution of the top 19 GDP's

Economy correlations between the 19 richest countries are investigated through their Gross Domestic Product increments. A distance is defined between increment correlation matrix elements and their evolution studied as a function of time and time window size. Unidirectional and Bidirectional Minimal Length Paths are generated and analyzed for different time windows. A sort of critical correlation time window is found indicating a transition for best observations. The mean length path decreases with time, indicating stronger correlations. A new method for estimating a realistic minimal time window to observe correlations and deduce macroeconomy conclusions from such features is thus suggested.Comment: to be published in the Dyses05 proceedings, in Int. J. Mod Phys C 15 pages, 5 figures, 1 tabl

Concept Discovery and Argument Bundles in the Experience Web

In this paper we focus on a particular interesting web user-generated content: people¿s experiences. We extend our previous work on aspect extraction and sentiment analysis and propose a novel approach to create a vocabulary of basic level concepts with the appropriate granularity to characterize a set of products. This concept vocabulary is created by analyzing the usage of the aspects over a set of reviews, and allows us to find those features with a clear positive and negative polarity to create the bundles of arguments. The argument bundles allow us to define a concept-wise satisfaction degree of a user query over a set of bundles using the notion of fuzzy implication, allowing the reuse experiences of other people to the needs a specific user. © Springer International Publishing AG 2016.This research has been partially supported by NASAID (CSIC Intramural 201550E022).Peer Reviewe

Income redistribution in the European Union

We explore the redistributive effects of taxes and benefits in the 27 member states of the European Union (EU) using EUROMOD, the tax-benefit microsimulation model for the EU. As well as describing redistributive effects in aggregate, we assess and compare the effectiveness of eight individual types of policy in reducing income disparities. We derive results for the 27 members of the EU using policies in effect in 2010 and present them for each country separately as well as for the EU as a whole

Scholarly communication in transition: The use of question marks in the titles of scientific articles in medicine, life sciences and physics 1966–2005

The titles of scientific articles have a special significance. We examined nearly 20 million scientific articles and recorded the development of articles with a question mark at the end of their titles over the last 40 years. Our study was confined to the disciplines of physics, life sciences and medicine, where we found a significant increase from 50% to more than 200% in the number of articles with question-mark titles. We looked at the principle functions and structure of the titles of scientific papers, and we assume that marketing aspects are one of the decisive factors behind the growing usage of question-mark titles in scientific articles

Quantified HI Morphology I: Multi-Wavelengths Analysis of the THINGS Galaxies

Galaxy evolution is driven to a large extent by interactions and mergers with other galaxies and the gas in galaxies is extremely sensitive to the interactions. One method to measure such interactions uses the quantified morphology of galaxy images. Well-established parameters are Concentration, Asymmetry, Smoothness, Gini, and M20 of a galaxy image. Thus far, the application of this technique has mostly been restricted to restframe ultra-violet and optical images. However, with the new radio observatories being commissioned (MeerKAT, ASKAP, EVLA, WSRT/APERTIF, and ultimately SKA), a new window on the neutral atomic hydrogen gas (HI) morphology of a large numbers of galaxies will open up. The quantified morphology of gas disks of spirals can be an alternative indicator of the level and frequency of interaction. The HI in galaxies is typically spatially more extended and more sensitive to low-mass or weak interactions. In this paper, we explore six morphological parameters calculated over the extent of the stellar (optical) disk and the extent of the gas disk for a range of wavelengths spanning UV, Optical, Near- and Far-Infrared and 21 cm (HI) of 28 galaxies from The HI Nearby Galaxy Survey (THINGS). Though the THINGS sample is small and contains only a single ongoing interaction, it spans both non-interacting and post-interacting galaxies with a wealth of multi-wavelength data. We find that the choice of area for the computation of the morphological parameters is less of an issue than the wavelength at which they are measured. The signal of interaction is as good in the HI as in any of the other wavelengths in which morphology has been used to trace the interaction rate to date, mostly star-formation dominated ones (near- and far-ultraviolet). The Asymmetry and M20 parameters are the ones which show the most promise as tracers of interaction in 21 cm line observations.Comment: 16 pages, 11 figure, table 1, accepted by MNRAS, appendix not include

Bibliometric Evidence for a Hierarchy of the Sciences

The hypothesis of a Hierarchy of the Sciences, first formulated in the 19(th) century, predicts that, moving from simple and general phenomena (e.g. particle dynamics) to complex and particular (e.g. human behaviour), researchers lose ability to reach theoretical and methodological consensus. This hypothesis places each field of research along a continuum of complexity and "softness", with profound implications for our understanding of scientific knowledge. Today, however, the idea is still unproven and philosophically overlooked, too often confused with simplistic dichotomies that contrast natural and social sciences, or science and the humanities. Empirical tests of the hypothesis have usually compared few fields and this, combined with other limitations, makes their results contradictory and inconclusive. We verified whether discipline characteristics reflect a hierarchy, a dichotomy or neither, by sampling nearly 29,000 papers published contemporaneously in 12 disciplines and measuring a set of parameters hypothesised to reflect theoretical and methodological consensus. The biological sciences had in most cases intermediate values between the physical and the social, with bio-molecular disciplines appearing harder than zoology, botany or ecology. In multivariable analyses, most of these parameters were independent predictors of the hierarchy, even when mathematics and the humanities were included. These results support a "gradualist" view of scientific knowledge, suggesting that the Hierarchy of the Sciences provides the best rational framework to understand disciplines' diversity. A deeper grasp of the relationship between subject matter's complexity and consensus could have profound implications for how we interpret, publish, popularize and administer scientific research