Implementación de cópulas para la estimación del valor en riesgo

La dependencia entre las series financieras, es un parámetro fundamental para la estimación de modelos de Riesgo. El Valor en Riesgo (VaR) es una de las medidas más importantes utilizadas para la administración y gestión de Riesgos Financieros, en la actualidad existen diferentes métodos para su estimación, como el método por simulación histórica, el cual no asume ninguna distribución sobre los retornos de los factores de riesgo o activos, o los métodos paramétricos que asumen normalidad sobre las distribuciones. En este documento se introduce la teoría de cópulas, como medida de dependencia entre las series, se estima un modelo ARMA-GARCH-Cópula para el cálculo del Valor en Riesgo de un portafolio compuesto por dos series financiera, la tasa de cambio Dólar-Peso y Euro-Peso. Los resultados obtenidos muestran que la estimación del VaR por medio de copulas es más preciso en relación a los métodos tradicionales.

Capacidad predictiva del euroscore II en una cohorte de pacientes de cirugía cardiovascular en una institución de cuarto nivel de Bogotá

El EuroSCORE II es una de las escalas más empleadas como predictor de riesgo de mortalidad en los servicios de cirugía cardiovascular. Esta ha sido validada en diferentes hospitales alrededor del mundo demostrando una adecuada capacidad de discriminación. El objetivo de este estudio fue evaluar el valor predictivo de la escala de riesgo EuroSCORE II en los pacientes sometidos a Cirugía Cardiovascular en una institución de cuarto nivel de Bogotá. Metodología: Estudio de prueba diagnóstica observacional y retrospectivo de la cohorte de pacientes en una institución de cuarto nivel durante los años 2012 a 2014. Se realizó el cálculo del EuroSCORE II para cada paciente, comparando la mortalidad predicha versus la observada, de forma global y por grupo de riesgo. Resultados: Del total de la población que tuvo intervención cardiaca mayor en una institución de cuarto nivel en la cohorte estudiada se presentaron 58 casos de muerte en los treinta días posteriores a la intervención, que corresponde al 7,46%. La mortalidad esperada calculada con el EuroSCORE II fue del 9,26%, lo cual indica un buen poder de predicción para esta población. Por otro lado, la curva ROC evidencia con un valor de 0.757 del área bajo la curva, que el modelo El EuroSCORE II es un buen modelo predictivo con un adecuado valor de discriminación. Se evidenció que las variables estado crítico preoperatorio y función del ventrículo izquierdo tienen mayor peso estadístico en nuestra población objeto, con una significancia del 0,001, seguido de infarto agudo de miocardio, sexo y peso de la intervención con una significancia del 0,01. Adicionalmente, el Euroscore II tiene mejor valor predictivo cuando se realiza un solo procedimiento o revascularización, en comparación a cuando se realiza procedimientos mixtos. Se recomienda realizar un estudio multicéntrico donde se incluyan pacientes con diferentes características demográficas

Análisis de supervivencia en pacientes con prótesis valvular biológica, Fundación Cardioinfantil-Instituto de Cardiología, Colombia, 2005-2013

Introducción: A partir de la década de los cincuenta el manejo de la enfermedad valvular presenta cambios significativos cuando se incorporan los reemplazos valvulares tanto mecánicos como biológicos dentro de las opciones de tratamiento quirúrgico (1). Las válvulas biológicas se desarrollaron como una alternativa que buscaba evitar los problemas relacionados con la anticoagulación y con la idea de utilizar un tejido que se comportara hemodinámicamente como el nativo. Este estudio está enfocado en establecer la sobrevida global y la libertad de reoperación de la válvula de los pacientes sometidos a reemplazo valvular aórtico y mitral biológicos en la Fundación Cardioinfantil - IC a 1, 3, 5 y 10 años. Materiales y métodos: Estudio de cohorte retrospectiva de supervivencia de pacientes sometidos a reemplazo valvular aórtico y/o mitral biológico intervenidos en la Fundación Cardioinfantil entre 2005 y 2013. Resultados: Se obtuvieron 919 pacientes incluidos en el análisis general y 876 (95,3%) pacientes con seguimiento efectivo para el análisis de sobrevida. La edad promedio fue 64años. La sobrevida a 1, 3, 5 y 10 años fue 95%,90%,85% y 69% respectivamente. El seguimiento efectivo para el desenlace reoperación fue del 55% y se encontró una libertad de reoperación del 99%, 96%, 93% y 81% a los 1, 3, 5 y 10 años. No hubo diferencias significativas entre la localización de la válvula ni en el tipo de válvula aortica empleada. Conclusiones: La sobrevida de los pacientes que son llevados a reemplazo valvular biológico en este estudio es comparable a grandes cohortes internacionales. La sobrevida de los pacientes llevados a reemplazo valvular con prótesis biológicas en posición mitral y aortica fue similar a 1, 3, 5 y 10 años.

Uncertainty assessment of a process-based integrated catchment model of phosphorus

Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.

GC/multiple collector-ICPMS method for chlorine stable isotope analysis of chlorinated aliphatic hydrocarbons

Stable isotopic characterization of chlorine in chlorinated aliphatic pollution is potentially very valuable for risk assessment and monitoring remediation or natural attenuation. The approach has been underused because of the complexity of analysis and the time it takes. We have developed a new method that eliminates sample preparation. Gas chromatography produces individually eluted sample peaks for analysis. The He carrier gas is mixed with Ar and introduced directly into the torch of a multicollector ICPMS. The MC-ICPMS is run at a high mass resolution of >= 10 000 to eliminate interference of mass 37 ArH with Cl. The standardization approach is similar to that for continuous flow stable isotope analysis in which sample and reference materials are measured successively. We have measured PCE relative to a laboratory TCE standard mixed with the sample. Solvent samples of 200 nmol to 1.3 mu mol ( 24- 165 mu g of Cl) were measured. The PCE gave the same value relative to the TCE as measured by the conventional method with a precision of 0.12% ( 2 x standard error) but poorer precision for the smaller samples.

Evaluating the risk of non-point source pollution from biosolids: integrated modelling of nutrient losses at field and catchment scales

A semi-distributed model, INCA, has been developed to determine the fate and distribution of nutrients in terrestrial and aquatic systems. The model simulates nitrogen and phosphorus processes in soils, groundwaters and river systems and can be applied in a semi-distributed manner at a range of scales. In this study, the model has been applied at field to sub-catchment to whole catchment scale to evaluate the behaviour of biosolid-derived losses of P in agricultural systems. It is shown that process-based models such as INCA, applied at a wide range of scales, reproduce field and catchment behaviour satisfactorily. The INCA model can also be used to generate generic information for risk assessment. By adjusting three key variables: biosolid application rates, the hydrological connectivity of the catchment and the initial P-status of the soils within the model, a matrix of P loss rates can be generated to evaluate the behaviour of the model and, hence, of the catchment system. The results, which indicate the sensitivity of the catchment to flow paths, to application rates and to initial soil conditions, have been incorporated into a Nutrient Export Risk Matrix (NERM).

Farmland biodiversity and the footprint of agriculture

Sustainable development requires the reconciliation of demands for biodiversity conservation and increased agricultural production. Assessing the impact of novel farming practices on biodiversity and ecosystem services is fundamental to this process. Using farmland birds as a model system, we present a generic risk assessment framework that accurately predicts each species' current conservation status and population growth rate associated with past changes in agriculture. We demonstrate its value by assessing the potential impact on biodiversity of two controversial land uses, genetically modified herbicide-tolerant crops and agri-environment schemes. This framework can be used to guide policy and land management decisions and to assess progress toward sustainability targets.

The extrapolation problem and how population modeling can help

We argue that population modeling can add value to ecological risk assessment by reducing uncertainty when extrapolating from ecotoxicological observations to relevant ecological effects. We review other methods of extrapolation, ranging from application factors to species sensitivity distributions to suborganismal (biomarker and "-omics'') responses to quantitative structure activity relationships and model ecosystems, drawing attention to the limitations of each. We suggest a simple classification of population models and critically examine each model in an extrapolation context. We conclude that population models have the potential for adding value to ecological risk assessment by incorporating better understanding of the links between individual responses and population size and structure and by incorporating greater levels of ecological complexity. A number of issues, however, need to be addressed before such models are likely to become more widely used. In a science context, these involve challenges in parameterization, questions about appropriate levels of complexity, issues concerning how specific or general the models need to be, and the extent to which interactions through competition and trophic relationships can be easily incorporated.

Population-level assessment of risks of pesticides to birds and mammals in the UK

It is generally acknowledged that population-level assessments provide,I better measure of response to toxicants than assessments of individual-level effects. population-level assessments generally require the use of models to integrate potentially complex data about the effects of toxicants on life-history traits, and to provide a relevant measure of ecological impact. Building on excellent earlier reviews we here briefly outline the modelling options in population-level risk assessment. Modelling is used to calculate population endpoints from available data, which is often about Individual life histories, the ways that individuals interact with each other, the environment and other species, and the ways individuals are affected by pesticides. As population endpoints, we recommend the use of population abundance, population growth rate, and the chance of population persistence. We recommend two types of model: simple life-history models distinguishing two life-history stages, juveniles and adults; and spatially-explicit individual-based landscape models. Life-history models are very quick to set up and run, and they provide a great deal or insight. At the other extreme, individual-based landscape models provide the greatest verisimilitude, albeit at the cost of greatly increased complexity. We conclude with a discussion of the cations of the severe problems of parameterising models.

An integrated assessment of carbon dioxide capture and storage in the UK

Geological carbon dioxide storage (CCS) has the potential to make a significant contribution to the decarbonisation of the UK. Amid concerns over maintaining security, and hence diversity, of supply, CCS could allow the continued use of coal, oil and gas whilst avoiding the CO2 emissions currently associated with fossil fuel use. This project has explored some of the geological, environmental, technical, economic and social implications of this technology. The UK is well placed to exploit CCS with a large offshore storage capacity, both in disused oil and gas fields and saline aquifers. This capacity should be sufficient to store CO2 from the power sector (at current levels) for a least one century, using well understood and therefore likely to be lower-risk, depleted hydrocarbon fields and contained parts of aquifers. It is very difficult to produce reliable estimates of the (potentially much larger) storage capacity of the less well understood geological reservoirs such as non-confined parts of aquifers. With the majority of its large coal fired power stations due to be retired during the next 15 to 20 years, the UK is at a natural decision point with respect to the future of power generation from coal; the existence of both national reserves and the infrastructure for receiving imported coal makes clean coal technology a realistic option. The notion of CCS as a ‘bridging’ or ‘stop-gap’ technology (i.e. whilst we develop ‘genuinely’ sustainable renewable energy technologies) needs to be examined somewhat critically, especially given the scale of global coal reserves. If CCS plant is built, then it is likely that technological innovation will bring down the costs of CO2 capture, such that it could become increasingly attractive. As with any capitalintensive option, there is a danger of becoming ‘locked-in’ to a CCS system. The costs of CCS in our model for UK power stations in the East Midlands and Yorkshire to reservoirs in the North Sea are between £25 and £60 per tonne of CO2 captured, transported and stored. This is between about 2 and 4 times the current traded price of a tonne of CO2 in the EU Emissions Trading Scheme. In addition to the technical and economic requirements of the CCS technology, it should also be socially and environmentally acceptable. Our research has shown that, given an acceptance of the severity and urgency of addressing climate change, CCS is viewed favourably by members of the public, provided it is adopted within a portfolio of other measures. The most commonly voiced concern from the public is that of leakage and this remains perhaps the greatest uncertainty with CCS. It is not possible to make general statements concerning storage security; assessments must be site specific. The impacts of any potential leakage are also somewhat uncertain but should be balanced against the deleterious effects of increased acidification in the oceans due to uptake of elevated atmospheric CO2 that have already been observed. Provided adequate long term monitoring can be ensured, any leakage of CO2 from a storage site is likely to have minimal localised impacts as long as leaks are rapidly repaired. A regulatory framework for CCS will need to include risk assessment of potential environmental and health and safety impacts, accounting and monitoring and liability for the long term. In summary, although there remain uncertainties to be resolved through research and demonstration projects, our assessment demonstrates that CCS holds great potential for significant cuts in CO2 emissions as we develop long term alternatives to fossil fuel use. CCS can contribute to reducing emissions of CO2 into the atmosphere in the near term (i.e. peak-shaving the future atmospheric concentration of CO2), with the potential to continue to deliver significant CO2 reductions over the long term.

Gene transcription in Daphnia magna: effects of acute exposure to a carbamate insecticide and an acetanilide herbicide.

Daphnia magna is a key invertebrate in the freshwater environment and is used widely as a model in ecotoxicological measurements and risk assessment. Understanding the genomic responses of D. magna to chemical challenges will be of value to regulatory authorities worldwide. Here we exposed D. magna to the insecticide methomyl and the herbicide propanil to compare phenotypic effects with changes in mRNA expression levels. Both pesticides are found in drainage ditches and surface water bodies standing adjacent to crops. Methomyl, a carbamate insecticide widely used in agriculture, inhibits acetylcholinesterase, a key enzyme in nerve transmission. Propanil, an acetanilide herbicide, is used to control grass and broad-leaf weeds. The phenotypic effects of single doses of each chemical were evaluated using a standard immobilisation assay. Immobilisation was linked to global mRNA expression levels using the previously estimated 48h-EC(1)s, followed by hybridization to a cDNA microarray with more than 13,000 redundant cDNA clones representing >5000 unique genes. Following exposure to methomyl and propanil, differential expression was found for 624 and 551 cDNAs, respectively (one-way ANOVA with Bonferroni correction, P

Entropic risk analysis by a high level decision support system (e-FDSS) for construction SMEs

The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects.

The SAFE FOODS framework for improved risk analysis of foods

Three main changes to current risk analysis processes are proposed to improve their transparency, openness, and accountability. First, the addition of a formal framing stage would allow interested parties, experts and officials to work together as needed to gain an initial shared understanding of the issue, the objectives of regulatory action, and alternative risk management measures. Second, the scope of the risk assessment is expanded to include the assessment of health and environmental benefits as well as risks, and the explicit consideration of economic- and social-impacts of risk management action and their distribution. Moreover approaches were developed for deriving improved information from genomic, proteomic and metabolomic profiling methods and for probabilistic modelling of health impacts for risk assessment purposes. Third, in an added evaluation stage, interested parties, experts, and officials may compare and weigh the risks, costs, and benefits and their distribution. As part of a set of recommendations on risk communication, we propose that reports on each stage should be made public.

Lessons from the private finance initiative in the UK: benefits, problems and critical success factors

Purpose – This paper summarises the main research findings from a detailed, qualitative set of structured interviews and case studies of private finance initiative (PFI) schemes in the UK, which involve the construction of built facilities. The research, which was funded by the Foundation for the Built Environment, examines the emergence of PFI in the UK. Benefits and problems in the PFI process are investigated. Best practice, the key critical factors for success, and lessons for the future are also analysed. Design/methodology/approach – The research is based around 11 semi-structured interviews conducted with stakeholders in key PFI projects in the UK. Findings – The research demonstrates that value for money and risk transfer are key success criteria. High procurement and transaction costs are a feature of PFI projects, and the large-scale nature of PFI projects frequently acts as barrier to entry. Research limitations/implications – The research is based on a limited number of in-depth case study interviews. The paper also shows that further research is needed to find better ways to measure these concepts empirically. Practical implications – The paper is important in highlighting four main areas of practical improvement in the PFI process: value for money assessment; establishing end-user needs; developing competitive markets and developing appropriate skills in the public sector. Originality/value – The paper examines the drivers, barriers and critical success factors for PFI in the UK for the first time in detail and will be of value to property investors, financiers, and others involved in the PFI process.

Development of a food-exchange model to replace saturated fat with MUFAS and n-6 PUFAS in adults at moderate cardiovascular risk

The recommendation to reduce saturated fatty acid (SFA) consumption to ≤10% of total energy (%TE) is a key public health target aimed at lowering cardiovascular disease (CVD) risk. Replacement of SFA with unsaturated fats may provide greater benefit than replacement with carbohydrates, yet the optimal type of fat is unclear. The aim was to develop a flexible food-exchange model to investigate the effects of substituting SFAs with monounsaturated fatty acids (MUFAs) or n-6 (ω-6) polyunsaturated fatty acids (PUFAs) on CVD risk factors. In this parallel study, UK adults aged 21-60 y with moderate CVD risk (50% greater than the population mean) were identified using a risk assessment tool (n = 195; 56% females). Three 16-wk isoenergetic diets of specific fatty acid (FA) composition (%TE SFA:%TE MUFA:%TE n-6 PUFA) were designed using spreads, oils, dairy products, and snacks as follows: 1) SFA-rich diet (17:11:4; n = 65); 2) MUFA-rich diet (9:19:4; n = 64); and 3) n-6 PUFA-rich diet (9:13:10; n = 66). Each diet provided 36%TE total fat. Dietary targets were broadly met for all intervention groups, reaching 17.6 ± 0.4%TE SFA, 18.5 ± 0.3%TE MUFA, and 10.4 ± 0.3%TE n-6 PUFA in the respective diets, with significant overall diet effects for the changes in SFA, MUFA, and n-6 PUFA between groups (P < 0.001). There were no differences in the changes of total fat, protein, carbohydrate, and alcohol intake or anthropometric measures between groups. Plasma phospholipid FA composition showed changes from baseline in the proportions of total SFA, MUFA, and n-6 PUFA for each diet group, with significant overall diet effects for total SFA and MUFA between groups (P < 0.001). In conclusion, successful implementation of the food-exchange model broadly achieved the dietary target intakes for the exchange of SFA with MUFA or n-6 PUFA with minimal disruption to the overall diet in a free-living population. This trial was registered at clinicaltrials.gov as NCT01478958.