Impacto de la venta de acciones en la salud financiera y el riesgo en los grupos financieros

Esta investigación tiene como objetivo general el análisis del impacto de la venta de acciones sobre la salud financiera y el riesgo en el grupo Aval. La necesidad por este estudio nace del interés por conocer los costos y beneficios que tienen las empresas a la hora de emitir acciones, siendo ésta última una práctica común en las últimas décadas. Algunas de las motivaciones relevantes para emitir acciones, son la financiación de nuevos proyectos de la empresa, el status que le pueda dar a la misma, una manera de hacer frente a la deuda, etc. Es importante conocer las implicaciones que tienen sobre la empresa la venta de acciones en términos de sus resultados, el impacto sobre los accionistas y sobre la misma sociedad. Esta investigación busca responder a la pregunta: ¿Cuál es el impacto de la venta de acciones sobre la salud financiera y el riesgo en los grupos financieros? Nos interesaremos por la revisión bibliográfica acerca de la salud financiera abordando autores que hablan de la misma desde el punto de vista de la posición de la empresa, refiriéndonos siempre a tres indicadores relevantes para el estudio y que son utilizados en la literatura para medir la salud financiera: liquidez, rentabilidad y endeudamiento. En la revisión de la literatura se ha encontrado una relación entre la salud financiera y el riesgo, por lo tanto buscaremos identificar cuál es el riesgo que afecta a las empresas cuando se emiten acciones centrándonos en tres tipos de riesgos financieros: riesgo de mercado, de interés y riesgo operacional; se ha escogido el grupo Aval para éste estudio ya que es uno de los grupos financieros más importantes en Colombia, con varios años de gestión y que actualmente realiza la práctica de emitir acciones.

Modelos de presupuestación de capital en finanzas corporativas y utilidad de los mismos

La siguiente investigación describe una aproximación teórica al tema de los modelos de presupuestación de capital, el objetivo fundamental se basa en comprender su enfoque e importancia al momento de tomar decisiones de inversión por parte de los directores de una empresa, así como de prever los efectos de esta en un futuro. Al respecto, y sobre la base de que los modelos de presupuestación de capital son herramientas para analizar posibles erogaciones de capital por parte de una empresa, es necesario para efectos del presente proyecto de investigación, definir sus diferentes modelos desde lo teórico y metodológico, explicando los diferentes conceptos relacionados con el tema. Así mismo, se explican algunos de los indicadores financieros utilizados en las compañías para medir y estimar la “salud financiera” de la empresa, además de puntualizar su impacto en la perdurabilidad de las entidades, lo cual permite dar una visión más general sobre la importancia que trasciende de los indicadores financieros, generando un impacto positivo en la evolución o crecimiento de la organización. En complemento, la investigación aborda la presupuestación de capital de manera particular aplicado en la gestión empresarial, sean estas privadas o públicas (estatal y gubernamental). En este sentido, se abordan conceptos elaborados por diferentes académicos en los que se exponen algunas aproximaciones respecto al posible mejoramiento de la presupuestación para los sectores a los que pertenecen determinadas entidades. Finalmente, se presenta de manera explícita las conclusiones que surgieron a lo largo de la construcción del documento de investigación, con el fin de dar cumplimiento concreto al objetivo general del trabajo, el cual constituye una respuesta a la pregunta de investigación que se enunciará en el desarrollo del documento.

A review and classification of the existing models of cyanobacteria

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting bloom occurrence in lakes and rivers. In this paper existing key models of cyanobacteria are reviewed, evaluated and classified. Two major groups emerge: deterministic mathematical and artificial neural network models. Mathematical models can be further subcategorized into those models concerned with impounded water bodies and those concerned with rivers. Most existing models focus on a single aspect such as the growth of transport mechanisms, but there are a few models which couple both.

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller-Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated.

A study on intelligent building models

Mathematical models devoted to different aspects of building studies and brought about a significant shift in the way we view buildings. From this background a new definition of building has emerged known as intelligent building that requires integration of a variety of computer-based complex systems. Research relevant to intelligent continues to grow at a much faster pace. This paper is a review of different mathematical models described in literature, which make use of different mathematical methodologies, and are intended for intelligent building studies without complex mathematical details. Models are discussed under a wide classification. Mathematical abstract level of the applied models is detailed and integrated with its literature. The goal of this paper is to present a comprehensive account of the achievements and status of mathematical models in intelligent building research. and to suggest future directions in models.

Modelling oil absorption during post-frying cooling - II: solution of the mathematical model, model testing and simulations

The mathematical models that describe the immersion-frying period and the post-frying cooling period of an infinite slab or an infinite cylinder were solved and tested. Results were successfully compared with those found in the literature or obtained experimentally, and were discussed in terms of the hypotheses and simplifications made. The models were used as the basis of a sensitivity analysis. Simulations showed that a decrease in slab thickness and core heat capacity resulted in faster crust development. On the other hand, an increase in oil temperature and boiling heat transfer coefficient between the oil and the surface of the food accelerated crust formation. The model for oil absorption during cooling was analysed using the tested post-frying cooling equation to determine the moment in which a positive pressure driving force, allowing oil suction within the pore, originated. It was found that as crust layer thickness, pore radius and ambient temperature decreased so did the time needed to start the absorption. On the other hand, as the effective convective heat transfer coefficient between the air and the surface of the slab increased the required cooling time decreased. In addition, it was found that the time needed to allow oil absorption during cooling was extremely sensitive to pore radius, indicating the importance of an accurate pore size determination in future studies.

Markov models of aging: theory and practice

We review and structure some of the mathematical and statistical models that have been developed over the past half century to grapple with theoretical and experimental questions about the stochastic development of aging over the life course. We suggest that the mathematical models are in large part addressing the problem of partitioning the randomness in aging: How does aging vary between individuals, and within an individual over the lifecourse? How much of the variation is inherently related to some qualities of the individual, and how much is entirely random? How much of the randomness is cumulative, and how much is merely short-term flutter? We propose that recent lines of statistical inquiry in survival analysis could usefully grapple with these questions, all the more so if they were more explicitly linked to the relevant mathematical and biological models of aging. To this end, we describe points of contact among the various lines of mathematical and statistical research. We suggest some directions for future work, including the exploration of information-theoretic measures for evaluating components of stochastic models as the basis for analyzing experiments and anchoring theoretical discussions of aging.

Applied models to biodegradation kinetics of lubricant and vegetable oils in wastewater

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-linear growth models for bullfrog tadpoles

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation and identification of lightning models by artificial neural networks

This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.

Distribution line models analysis for loss calculation within three-phase three-wire power flow algorithms

Three-phase three-wire power flow algorithms, as any tool for power systems analysis, require reliable impedances and models in order to obtain accurate results. Kron's reduction procedure, which embeds neutral wire influence into phase wires, has shown good results when three-phase three-wire power flow algorithms based on current summation method were used. However, Kron's reduction can harm reliabilities of some algorithms whose iterative processes need loss calculation (power summation method). In this work, three three-phase three-wire power flow algorithms based on power summation method, will be compared with a three-phase four-wire approach based on backward-forward technique and current summation. Two four-wire unbalanced medium-voltage distribution networks will be analyzed and results will be presented and discussed. © 2004 IEEE.

Remarks on orthotropic elastic models applied to wood

Wood is generally considered an anisotropic material. In terms of engineering elastic models, wood is usually treated as an orthotropic material. This paper presents an analysis of two principal anisotropic elastic models that are usually applied to wood. The first one, the linear orthotropic model, where the material axes L (Longitudinal), R(radial) and T(tangential) are coincident with the Cartesian axes (x, y, z), is more accepted as wood elastic model. The other one, the cylindrical orthotropic model is more adequate of the growth caracteristics of wood but more mathematically complex to be adopted in practical terms. Specifically due to its importance in wood elastic parameters, this paper deals with the fiber orientation influence in these models through adequate transformation of coordinates. As a final result, some examples of the linear model, which show the variation of elastic moduli, i.e., Young's modulus and shear modulus, with fiber orientation are presented.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Generating VHDL-AMS models of digital-to-analogue converters from MATLAB®/SIMULINK®

Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB®/SIMULINK® models to structural VHDL-AMS descriptions. The tool developed, named MS 2SV, reads a SIMULINK® model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the System Vision™. To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB®/ SIMULINK®. The VHDL-AMS code generated automatically by MS 2SV, (MATLAB®/SIMULINK® to System Vision™), was then simulated in the System Vision™. The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.

Sistemas dinâmicos discretos: análise de estabilidade

Pós-graduação em Matemática Universitária - IGCE