Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.

Moduli of flat conformal structures of hyperbolic type

"Vegeu el resum a l'inici del document del fitxer adjunt."

Quantifying rates of landscape evolution and tectonic processes by thermochronology and numerical modeling of crustal heat transport using PECUBE

PECUBE is a three-dimensional thermal-kinematic code capable of solving the heat production-diffusion-advection equation under a temporally varying surface boundary condition. It was initially developed to assess the effects of time-varying surface topography (relief) on low-temperature thermochronological datasets. Thermochronometric ages are predicted by tracking the time-temperature histories of rock-particles ending up at the surface and by combining these with various age-prediction models. In the decade since its inception, the PECUBE code has been under continuous development as its use became wider and addressed different tectonic-geomorphic problems. This paper describes several major recent improvements in the code, including its integration with an inverse-modeling package based on the Neighborhood Algorithm, the incorporation of fault-controlled kinematics, several different ways to address topographic and drainage change through time, the ability to predict subsurface (tunnel or borehole) data, prediction of detrital thermochronology data and a method to compare these with observations, and the coupling with landscape-evolution (or surface-process) models. Each new development is described together with one or several applications, so that the reader and potential user can clearly assess and make use of the capabilities of PECUBE. We end with describing some developments that are currently underway or should take place in the foreseeable future. (C) 2012 Elsevier B.V. All rights reserved.

(Optimal) Spatial Aggregation in the Determinants of Industrial Location

Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

Modeling AIDS vaccines: the cellular level

This paper discuses current strategies for the development of AIDS vaccines wich allow immunzation to disturb the natural course of HIV at different detailed stages of its life cycle. Mathematical models describing the main biological phenomena (i.e. virus and vaccine induced T4 cell growth; virus and vaccine induced activation latently infected T4 cells; incremental changes immune response as infection progress; antibody dependent enhancement and neutralization of infection) and allowing for different vaccination strategies serve as a backgroud for computer simulations. The mathematical models reproduce updated information on the behavior of immune cells, antibody concentrations and free viruses. The results point to some controversial outcomes of an AIDS vaccine such as an early increase in virus concentration among vaccinated when compared to nonvaccinated individuals.

Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

Estudi per la implantació d'un ERP en una empresa d'aplicació de pintura industrial i decorativa

La implantació d'un sistema ERP no és senzilla, requereix grans esforços i una bona administració a més de considerar molts altres aspectes per arribar a tenir èxit. Per aquest motiu, la presa de requeriments en aquest tipus de projectes esdevé pedra angular. A Estudi per la implantació d'un ERP en una empresa d'aplicació de pintura industrial i decorativa es realitza un estudi detallat de l'organització de l'empresa amb la finalitat de trobar els requeriments d'aquesta, seguidament es realitza un estudi de tres sistemes ERP per acabar trobant la solució que millor encaixa en les necessitats de l'empresa.

Casolà o industrial?: estudi organolèptic i microbiològic de la vida útil del pernil cuit

Treball de recerca realitzat per un alumne d'ensenyament secundari i guardonat amb un Premi CIRIT per fomentar l'esperit científic del Jovent l'any 2009. Aquest treball tracta sobre el temps de garantia o de vida útil d’un producte alimentari i està basat en esbrinar quin és el millor mètode o envàs per conservar el pernil cuit llescat durant la seva vida útil, per tal que es mantinguin les propietats organolèptiques i microbiològiques inicials de l’aliment durant el màxim de temps possible. Per comparar envasos he utilitzat els industrials (envàs al buit i envàs en atmosfera) i els envasos que podem trobar quan comprem un producte llescat en el mostrador d’una botiga o supermercat. Per a fer l’estudi doncs s’ha utilitzat el pernil cuit, conegut com a pernil dolç, un dels productes més consumits per la societat actual. El pernil ha estat tractat en tres situacions diferents: llescat en una màquina de carnisseria i envasat en mètodes de conservació domèstics, llescat en màquines industrials i envasat en diferents envasos (al buit i en atmosfera modificada) utilitzats per les grans empreses i llescat en màquines industrials i envasat al buit sotmès a un tractament amb altes pressions. Després d’aquests processos s’ha realitzat un estudi de vida útil, és a dir, s’ha analitzat el producte al laboratori, amb l’objectiu de trobar quin és el millor envàs per a la conservació del pernil cuit.

Relationship between technological progress, capital elasticity and emissions of industrial pollutants for the production sectors in Catalonia

As is known, the Kyoto Protocol proposes to reinforce national policies for emission reduction and, furthermore, to cooperate with other contracting parties. In this context, it would be necessary to assess these emissions, both in general and specifically, by pollutants and/or among productive sectors. The object of this paper is precisely to estimate the polluting emissions of industrial origin in Catalonia in the year 2001, in a multivariate context which explicitly allows a distinction to be made between the polluter and/or the productive sector causing this emission. Six pollutants considered, four directly related to greenhouse effect. A multi-level model, with two levels, pollutants and productive sectors, was specified. Both technological progress and elasticity of capital were introduced as random effects. Hence, it has been permitted that these coefficients vary according to one or other level. The most important finding in this paper is that elasticity of capital has been estimated as very non-elastic, with a range which varies between 0.162 (the paper industry) and 0.556 (commerce). In fact, and generally speaking, the greater capital the sector has, the less elasticity of capital has been estimated. Key words: Kyoto protocol, multilevel model, technological progress

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Industrial district effects and innovation in the Tuscan shipbuilding industry

The aim of the present work is to investigate innovative processes within a geographical cluster, and thus contribute to the debate on the effects of industrial clusters on innovation capacity. In particular, we would like to ascertain whether the advantages of industrial districts in promoting innovation, as already revealed by literature (diffusion of knowledge, social capital and trust, efficient networking), are also keys to success in the Tuscan shipbuilding industry of pleasure and sporting boats. First, we verify the existence of clusters of shipbuilding in Tuscany, using a specific methodology. Next, in the identified clusters, we analyse three innovative networks financed in a policy to support innovation, and examine whether the typical features of a cluster for promoting innovation are at work, using a questionnaire administered to 71 actors. Finally, we develop a performance analysis of the cluster firms and ascertain whether their different behaviours also lead to different performances. The analysis results show that our case records effects of industrial clustering on innovation capacity, such as the important role given to trust and social capital, the significant worth put in interfirm relations and in each partner’s specific competencies, or even the distinctive performance of firms belonging to a cluster.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.