Medidas de riesgo, características y técnicas de medición: una aplicación del VaR y el ES a la tasa interbancaria de Colombia

Este texto describe en detalle diversas metodologías que permiten calcular dos medidas utilizadas para cuantificar el riesgo de mercado asociado a un activo financiero: el valor en riesgo VAR y el Expected Shortfall (ES). Los métodos analizados se basan en técnicas estadísticas apropiadas para el caso de series financieras, como son los modelos ARIMA, GARCH y modelos basados en la teoría del valor extremo. Estas metodologías se aplican a las variaciones diarias de la tasa interbancaria de Colombia para el período comprendido entre 1995 y 2004. Los conceptos utilizados en este texto suponen que el lector esté familiarizado con algunos elementos básicos de estadística, series de tiempo y finanzas. Se trata, por tanto, de un texto escrito para estudiantes de economía y finanzas de últimos cursos de pregrado, maestría y para profesionales interesados en el tema.

Respuesta del producto con respecto a la política monetaria, el gasto de déficit, y la depreciación de la moneda en Venezuela: un modelo VAR.

Este estudio aplica el modelo VAR para hallar posibles respuestas del PIB real a variables macroeconómicas seleccionadas en Venezuela. Basado en una muestra anual de 1961-2001, el autor encuentra que el PIB real responde positivamente a choques en el M2 real, al déficit del gobierno, a la depreciación de la tasa de cambio y al producto rezagado, y negativamente a choques en la inflación durante algunos períodos de tiempo. Excepto por el producto rezagado, el déficit del gobierno y la inflación son las variables que tienen mayor influencia en el primer año. El M2 real y la tasa de cambio real son las que más influyen y tienen impactos de más largo plazo después del primer año.

Madrid desde el Cerro Almod??var

Material sin publicar

Estructura del portafolio de inversiones con el VAR (Valué at Risk)

El propósito general de este trabajo de investigación es el de identificar las herramientas que permitan evaluar riesgos, poder determinar un modelo de ayuda para la estructuración de portafolios y así retribuir al inversionista la mejor manera con un premio por riesgo en retorno de su inversión, Además de presentar un instrumento y demostrar las ventajas de su utilización en la valoración de riesgos en portafolios, se pretende distinguir los efectos económicos y financieros que el inversionista enfrenta. Para cumplir con este propósito, se realizo un diagnóstico y análisis de la actividad de los mercados Financieros y de Capitales, determinando los factores más importantes dentro de un modelo de valoración de riesgo para la estructura de un portafolio de renta variable, lo que me permitirá presentar de una manera clara, los aspectos técnicos y económicos que afectan a la estructura de una inversión aplicando la metodología denominada VAR (Valué at Risk); adicionalmente el manejo que se podría dar a las mismas para obtener un mayor beneficio. Los resultados obtenidos y su respectivo análisis constan a lo largo de este trabajo de investigación.

Gestión de riesgo de liquidez en Mutualista Pichincha: metodología VAR para determinar la volatilidad las fuentes de sondeo

La presente disertación tiene como objetivo la evaluación de la metodología VAR, tanto histórica como paramétrica, a las fuentes de fondeo de Mutualista Pichincha, con el fin de determinar el nivel de liquidez requiere la institución para cubrir el riesgo de volatilidad de estas fuentes. El primer capítulo describe el riesgo de liquidez, sus principales fuentes de origen, la importancia de su gestión. Se presenta un análisis de la normativa ecuatoriana en lo que tiene que ver a riesgo de liquidez. El segundo capítulo de este trabajo se centra en la teoría del Valor en Riesgo, explicando las principales metodologías para calcularlo, los supuestos en lo que se basa y las ventajas de su aplicación. En el tercer capítulo se presenta una breve reseña de las actividades de Mutualista Pichincha, se analiza la aplicación de la normativa ecuatoriana en la institución financiera. En base al estudio de las metodología VAR realizas a las fuentes de fondeo, se selección el método de cálculo del VAR mas adecuado. Por último, el cuarto capítulo corresponde las conclusiones y recomendaciones, resultado del estudio realizado.

Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

Exploring the spatial variation of take-all (Gaeumannomyces graminis var. tritici) for site-specific management

The fungus Gaeumannomyces graminis var. tritici (Ggt), commonly known as the take-all fungus, causes damage to roots of wheat and barley that limits crop growth and causes loss of yield. There was little knowledge on the within-field spatial variation of take-all and relations with features in the growing crop, selected soil properties and spectral information from remotely sensed imagery. Geostatistical analyses showed that take-all, chlorosis and leaf area index had similar patchy distributions. Many of the spectral bands from a hyperspectral image also had similar spatial patterns to take-all and chlorosis. Relations between take-all and mineral nitrogen, elevation and pH were generally weaker.

Hybridization between Brassica napus and B. rapa on a national scale in the United Kingdom

Measures blocking hybridization would prevent or reduce biotic or environmental change caused by gene flow from genetically modified (GM) crops to wild relatives. The efficacy of any such measure depends on hybrid numbers within the legislative region over the life-span of the GM cultivar. We present a national assessment of hybridization between rapeseed (Brassica napus) and B. rapa from a combination of sources, including population surveys, remote sensing, pollen dispersal profiles, herbarium data, local Floras, and other floristic databases. Across the United Kingdom, we estimate that 32,000 hybrids form annually in waterside B. rapa populations, whereas the less abundant weedy populations contain 17,000 hybrids. These findings set targets for strategies to eliminate hybridization and represent the first step toward quantitative risk assessment on a national scale.

A singular vector perspective of 4D-Var: Filtering and interpolation

Four-dimensional variational data assimilation (4D-Var) combines the information from a time sequence of observations with the model dynamics and a background state to produce an analysis. In this paper, a new mathematical insight into the behaviour of 4D-Var is gained from an extension of concepts that are used to assess the qualitative information content of observations in satellite retrievals. It is shown that the 4D-Var analysis increments can be written as a linear combination of the singular vectors of a matrix which is a function of both the observational and the forecast model systems. This formulation is used to consider the filtering and interpolating aspects of 4D-Var using idealized case-studies based on a simple model of baroclinic instability. The results of the 4D-Var case-studies exhibit the reconstruction of the state in unobserved regions as a consequence of the interpolation of observations through time. The results also exhibit the filtering of components with small spatial scales that correspond to noise, and the filtering of structures in unobserved regions. The singular vector perspective gives a very clear view of this filtering and interpolating by the 4D-Var algorithm and shows that the appropriate specification of the a priori statistics is vital to extract the largest possible amount of useful information from the observations. Copyright © 2005 Royal Meteorological Society

Can 4D-Var use dynamical information from targeted observations of a baroclinic structure?

Targeted observations are generally taken in regions of high baroclinicity, but often show little impact. One plausible explanation is that important dynamical information, such as upshear tilt, is not extracted from the targeted observations by the data assimilation scheme and used to correct initial condition error. This is investigated by generating pseudo targeted observations which contain a singular vector (SV) structure that is not present in the background field or routine observations, i.e. assuming that the background has an initial condition error with tilted growing structure. Experiments were performed for a single case-study with varying numbers of pseudo targeted observations. These were assimilated by the Met Office four-dimensional variational (4D-Var) data assimilation scheme, which uses a 6 h window for observations and background-error covariances calculated using the National Meteorological Centre (NMC) method. The forecasts were run using the operational Met Office Unified Model on a 24 km grid. The results presented clearly demonstrate that a 6 h window 4D-Var system is capable of extracting baroclinic information from a limited set of observations and using it to correct initial condition error. To capture the SV structure well (projection of 0.72 in total energy), 50 sondes over an area of 1×106 km2 were required. When the SV was represented by only eight sondes along an example targeting flight track covering a smaller area, the projection onto the SV structure was lower; the resulting forecast perturbations showed an SV structure with increased tilt and reduced initial energy. The total energy contained in the perturbations decreased as the SV structure was less well described by the set of observations (i.e. as fewer pseudo observations were assimilated). The assimilated perturbation had lower energy than the SV unless the pseudo observations were assimilated with the dropsonde observation errors halved from operational values. Copyright © 2010 Royal Meteorological Society

Landscape gene flow, coexistence and threshold effect: The case of genetically modified herbicide tolerant oilseed rape (Brassica napus)

Globally there have been a number of concerns about the development of genetically modified crops many of which relate to the implications of gene flow at various levels. In Europe these concerns have led the European Union (EU) to promote the concept of 'coexistence' to allow the freedom to plant conventional and genetically modified (GM) varieties but to minimise the presence of transgenic material within conventional crops. Should a premium for non-GM varieties emerge on the market, the presence of transgenes would generate a 'negative externality' to conventional growers. The establishment of maximum tolerance level for the adventitious presence of GM material in conventional crops produces a threshold effect in the external costs. The existing literature suggests that apart from the biological characteristics of the plant under consideration (e.g. self-pollination rates, entomophilous species, anemophilous species, etc.), gene flow at the landscape level is affected by the relative size of the source and sink populations and the spatial arrangement of the fields in the landscape. In this paper, we take genetically modified herbicide tolerant oilseed rape (GM HT OSR) as a model crop. Starting from an individual pollen dispersal function, we develop a spatially explicit numerical model in order to assess the effect of the size of the source/sink populations and the degree of spatial aggregation on the extent of gene flow into conventional OSR varieties under two alternative settings. We find that when the transgene presence in conventional produce is detected at the field level, the external cost will increase with the size of the source area and with the level of spatial disaggregation. on the other hand when the transgene presence is averaged among all conventional fields in the landscape (e.g. because of grain mixing before detection), the external cost will only depend on the relative size of the source area. The model could readily be incorporated into an economic evaluation of policies to regulate adoption of GM HT OSR. (c) 2007 Elsevier B.V. All rights reserved.

Characterization and origin of infection of Rhizoctonia solani associated with Brassica oleracea crops in the UK

An extensive study was conducted to determine where in the production chain Rhizoctonia solani became associated with UK module-raised Brassica oleracea plants. In total, 2600 plants from 52 crops were sampled directly from propagators and repeat sampled from the field. Additional soil, compost and water samples were collected from propagation nurseries and screened using conventional agar isolation methods. No isolates of R. solani were recovered from any samples collected from propagation nurseries. Furthermore, nucleic acid preparations from samples of soil and compost from propagation nurseries gave negative results when tested for R. solani using real-time PCR. Conversely, R. solani was recovered from 116 of 1300 stem bases collected from field crops. All the data collected suggested R. solani became associated with B. oleracea in the field rather than during propagation. Parsimony and Bayesian phylogenetic studies of ribosomal DNA suggested the majority of further classified isolates belonged to anastomosis groups 2-1 (48/57) and AG-4HGII (8/57), groups known to be pathogenic on Brassica spp. in other countries. Many R. solani isolates were recovered from symptomless plant material and the possibilities for such an association are discussed.

Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modeling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.