Sufrimiento y pesimismo en Schopenhauer

El presente artículo investiga de qué forma la centralidad del sufrimiento en la filosofía de Schopenhauer sirve para fundamentar su pesimismo. Tres son los argumentos analizados: el lugar del sufrimiento en el mundo, su lugar en la conciencia humana y su lugar frente a la felicidad. A la luz de estos tres argumentos, se destaca que el vínculo indisoluble entre el sufrimiento y la esencia del mundo, la determinación del sufrimiento en la conciencia, tanto en su génesis como en su intensidad, y su anterioridad ontológica frente a la felicidad hacen del pesimismo una categoría necesaria. Finalmente, se señala una posible contribución del pesimismo schopenhaueriano a la crítica social contemporánea, considerando la idea de mundo que el capitalismo tardío promueve.

Women artists of the international avant-garde: the case of "Abstraction-Création" (1931-1936)

Women’s contribution to abstract art in the interwar period is a subject that, to date, has received very little attention. In this article we deal with the untold story of the participation of women artists in Abstraction-Création, the foremost international group dedicated to abstract art in the 1930s. Founded in Paris in 1931, the group took on the work of two previous collectives to become a platform for the dissemination and promotion of abstract art and consisted of around a hundred members. Twelve of these were women, whose writings and works were published in the group’s annual magazine, abstraction creátion art non figuratif (1932-1936), and who participated in a number of the group’s exhibitions. Compared to what had occurred in previous groups, the participation of women, although reduced in number, was comparable to that of the male artists and being members of the group had a generally positive impact on the women’s careers. However, all this came at the expense of relinquishing any gender specificity in their work and the public presentation of it, and demonstrates that the normalization of women’s contributions to the avant-garde could only be brought about alongside a questioning of the more dogmatic views of modernity.

A Diagnostic System Using Broad Categories With Clinicaly Relevant Specifiers: Lessons for ICD-10

A diagnostic system for ICD-11 is proposed which commences with broad reorganization and simplification of the current categories and the use of clinically relevant specifiers. Such changes have implications for the positioning of diagnostic groups and lead to a range of possibilities for improving terminology and the juxtaposition of individual conditions. The development of ICD-11 provides the first opportunity in almost two decades to improve the validity and reliability of the international classification system. Widespread change in broad categories and criteria cannot be justified by research that has emerged since the last revision. It would also be disruptive to clinical practice and might devalue past research work. However, the case for reorganization of the categories is stronger and has recently been made by an eminent international group of researchers (Andrews et al., 2009). A simpler, interlinked diagnostic system is proposed here which is likely to have fewer categories than its predecessor. There are major advantages of such a system for clinical practice and research and it could also produce much needed simplification for primary care (Gask et al., 2008) and the developing world (Wig, 1990; Kohn et al., 2004).

Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

Recovering Social Networks from Individual Attributes

One of the most important challenges of network analysis remains the scarcity of reliable information on existing connection structures. This work explores theoretical and empirical methods of inferring directed networks from nodes attributes and from functions of these attributes that are computed for connected nodes. We discuss the conditions, under which an underlying connection structure can be (probabilistically) recovered, and propose a Bayesian recovery algorithm. In an empirical application, we test the algorithm on the data from the European School Survey Project on Alcohol and Other Drugs.

Endogenous Two-Sided Markets with Repeated Transactions

We consider homogeneous two-sided markets, in which connected buyer-seller pairs bargain and trade repeatedly. In this infinite market game with exogenous matching probabilities and a common discount factor, we prove the existence of equilibria in stationary strategies. The equilibrium payoffs are given implicitly as a solution to a system of linear equations. Then, we endogenize the matching mechanism in a link formation stage that precedes the market game. When agents are sufficiently patient and link costs are low, we provide an algorithm to construct minimally connected networks that are pairwise stable with respect to the expected payoffs in the trading stage. The constructed networks are essentially efficient and consist of components with a constant buyer-seller ratio. The latter ratio increases (decreases) for a buyer (seller) that deletes one of her links in a pairwise stable component.

Efficient Evaluation of Multidimensional Time-Varying Density Forecasts

We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation of the coordinate system. The advantage of the second method is not only its applicability to any continuous distribution but also the evaluation of the forecast accuracy in specific regions of its domain as defined by the user’s interest. We show that the latter property is particularly useful for evaluating a multidimensional generalization of the Value at Risk. In simulations and in an empirical study, we examine the performance of both tests.