El Riesgo y las estrategias en la evaluación de los fondos de inversión de renta variable

El objetivo de este trabajo consiste en proponer una medida de performance adecuada para los fondos de inversión de renta variable. Las características específicas de este tipo de carteras inducen a tomar un enfoque basado en la L.M.C., por lo que se escoge como medida de riesgo el riesgo total de la cartera (pσ). Se introducen las estrategias pasivas y activas en el análisis, con lo que se consigue desarrollar una medida de performance que, además de medir la rentabilidad por gestión efectiva, la pondera en función del grado de actividad asumido por la cartera a evaluar.

Estimation of dynamic latent variable models using simulated nonparametric moments

Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.

Experimental investigation of transient natural convection cooling of high prandtl number fluid with variable viscosity

Report for the scientific sojourn at the James Cook University, Australia, between June to December 2007. Free convection in enclosed spaces is found widely in natural and industrial systems. It is a topic of primary interest because in many systems it provides the largest resistance to the heat transfer in comparison with other heat transfer modes. In such systems the convection is driven by a density gradient within the fluid, which, usually, is produced by a temperature difference between the fluid and surrounding walls. In the oil industry, the oil, which has High Prandtl, usually is stored and transported in large tanks at temperatures high enough to keep its viscosity and, thus the pumping requirements, to a reasonable level. A temperature difference between the fluid and the walls of the container may give rise to the unsteady buoyancy force and hence the unsteady natural convection. In the initial period of cooling the natural convection regime dominates over the conduction contribution. As the oil cools down it typically becomes more viscous and this increase of viscosity inhibits the convection. At this point the oil viscosity becomes very large and unloading of the tank becomes very difficult. For this reason it is of primary interest to be able to predict the cooling rate of the oil. The general objective of this work is to develop and validate a simulation tool able to predict the cooling rates of high Prandtl fluid considering the variable viscosity effects.

Patrones de tomate: resistencia variable frente al nematodo Meloidogyne

Los patrones de tomate se han propuesto como una alternativa no química al uso del bromuro de metilo. En este estudio se evaluó la respuesta de resistencia de diez patrones de tomate (comerciales y experimentales) a nematodos del género Meloidogyne mediante un ensayo de campo realizado en un invernadero de plástico cuyo suelo se hallaba infestado por Meloidogyne javanica. Al finalizar la campaña agrícola (marzo a julio), siete de los patrones ensayados mostraron altos niveles de resistencia, uno presentó resistencia intermedia y dos resultaron ser susceptibles al nematodo.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

Genomics of wine yeast: functional analysis of new and variable genes

Projecte de recerca elaborat a partir d’una estada a l’Institut National de la Recherche Agronomique, França, entre 2007 i 2009. Saccharomyces cerevisiae ha estat el llevat utilitzat durant mil.lenis en l'elaboració de vins. Tot i així, es té poc coneixement sobre les pressions de selecció que han actuat en la modelització del genoma dels llevats vínics. S’ha seqüenciat el genoma d'una soca vínica comercial, EC1118, obtenint 31 supercontigs que cobreixen el 97% del genoma de la soca de referència, S288c. S’ha trobat que el genoma de la soca vínica es diferencia bàsicament en la possessió de 3 regions úniques que contenen 34 gens implicats en funcions claus per al procés fermentatiu. A banda, s’han dut a terme estudis de filogènia i synteny (ordre dels gens) que mostren que una d'aquestes tres regions és pròxima a una espècie relacionada amb el gènere Saccharomyces, mentre que les altres dos regions tenen un origen no-Saccharomyces. S’ha identificat mitjançant PCR i seqüenciació a Zygosaccharomyces bailii, una espècie contaminant de les fermentacions víniques, com a espècie donadora d'una de les dues regions. Les hibridacions naturals entre soques de diferents espècies dins del grup Saccharomyces sensu stricto ja han estat descrites. El treball és el primer que presenta hibridacions entre espècies Saccharomyces i no-Saccharomyces (Z. bailii, en aquest cas). També s’assenyala que les noves regions es troben freqüent i diferencialment presents entre els clades de S. cerevisiae, trobant-se de manera gairebé exclusiva en el grup de les soques víniques, suggerint que es tracta d'una adquisició recent de transferència gènica. En general, les dades demostren que el genoma de les soques víniques pateix una constant remodelació mitjançant l'adquisició de gens exògens. Els resultats suggereixen que aquests processos estan afavorits per la proximitat ecològica i estan implicats en l'adaptació molecular de les soques víniques a les condicions d'elevada concentració en sucres, poc nitrogen i elevades concentracions en etanol.

Life-Cycle Effects on Household Expenditures: A Latent-Variable Approach

Using data from the Spanish household budget survey, we investigate life- cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Lyfe-cycle effects on household expenditures: A latent-variable approach

Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Variable Kernel estimates: On the impossibility of tuning the parameters

For the standard kernel density estimate, it is known that one can tune the bandwidth such that the expected L1 error is within a constant factor of the optimal L1 error (obtained when one is allowed to choose the bandwidth with knowledge of the density). In this paper, we pose the same problem for variable bandwidth kernel estimates where the bandwidths are allowed to depend upon the location. We show in particular that for positive kernels on the real line, for any data-based bandwidth, there exists a densityfor which the ratio of expected L1 error over optimal L1 error tends to infinity. Thus, the problem of tuning the variable bandwidth in an optimal manner is ``too hard''. Moreover, from the class of counterexamples exhibited in the paper, it appears thatplacing conditions on the densities (monotonicity, convexity, smoothness) does not help.

Testing financing constraints on firm investment using variable capital

We consider a dynamic multifactor model of investment with financing imperfections,adjustment costs and fixed and variable capital. We use the model to derive a test offinancing constraints based on a reduced form variable capital equation. Simulation resultsshow that this test correctly identifies financially constrained firms even when the estimationof firms investment opportunities is very noisy. In addition, the test is well specified inthe presence of both concave and convex adjustment costs of fixed capital. We confirmempirically the validity of this test on a sample of small Italian manufacturing companies.

Optical counterpart of galactic plane variable radio sources

We present I-band deep CCD exposures of the fields of galactic plane radio variables. An optical counterpart, based on positional coincidence, has been found for 15 of the 27 observed program objects. The Johnson I magnitude of the sources identified is in the range 18-21.

Radio detections towards unidentified variable EGRET sources

A considerable fraction of the -ray sources discovered with the Energetic Gamma-Ray Experiment Telescope (EGRET) remain unidentified. The EGRET sources that have been properly identified are either pulsars or variable sources at both radio and gamma-ray wavelengths. Most of the variable sources are strong radio blazars. However, some low galactic-latitude EGRET sources, with highly variable -ray emission, lack any evident counterpart according to the radio data available until now. Aims. The primary goal of this paper is to identify and characterise the potential radio counterparts of four highly variable -ray sources in the galactic plane through mapping the radio surroundings of the EGRET confidence contours and determining the variable radio sources in the field whenever possible. Methods. We have carried out a radio exploration of the fields of the selected EGRET sources using the Giant Metrewave Radio Telescope (GMRT) interferometer at 21 cm wavelength, with pointings being separated by months. Results. We detected a total of 151 radio sources. Among them, we identified a few radio sources whose flux density has apparently changed on timescales of months. Despite the limitations of our search, their possible variability makes these objects a top-priority target for multiwavelength studies of the potential counterparts of highly variable, unidentified gamma-ray sources.

Super-resolution of remotely sensed images with variable-pixel linear reconstruction

This paper describes the development and applications of a super-resolution method, known as Super-Resolution Variable-Pixel Linear Reconstruction. The algorithm works combining different lower resolution images in order to obtain, as a result, a higher resolution image. We show that it can make significant spatial resolution improvements to satellite images of the Earth¿s surface allowing recognition of objects with size approaching the limiting spatial resolution of the lower resolution images. The algorithm is based on the Variable-Pixel Linear Reconstruction algorithm developed by Fruchter and Hook, a well-known method in astronomy but never used for Earth remote sensing purposes. The algorithm preserves photometry, can weight input images according to the statistical significance of each pixel, and removes the effect of geometric distortion on both image shape and photometry. In this paper, we describe its development for remote sensing purposes, show the usefulness of the algorithm working with images as different to the astronomical images as the remote sensing ones, and show applications to: 1) a set of simulated multispectral images obtained from a real Quickbird image; and 2) a set of multispectral real Landsat Enhanced Thematic Mapper Plus (ETM+) images. These examples show that the algorithm provides a substantial improvement in limiting spatial resolution for both simulated and real data sets without significantly altering the multispectral content of the input low-resolution images, without amplifying the noise, and with very few artifacts.