852 resultados para Parametric VaR (Value-at-Risk)
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Estatística, 2015.
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This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.
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Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.
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Seismic microzonation has generally been recognized as the most accepted tool in seismic hazard assessment and risk evaluation. In general, risk reduction can be done by reducing the hazard, the vulnerability or the value at risk. Since the earthquake hazard can not be reduced, one has to concentrate on vulnerability and value at risk. The vulnerability of an urban area / municipalities depends on the vulnerability of infrastructure and redundancies within the infrastructure. The earthquake risk is the damage to buildings along with number of people that are killed / hurt and the economic losses during the event due to an earthquake with a return period corresponding to this time period. The principal approaches one can follow to reduce these losses are to avoid, if possible, high hazard areas for the siting of buildings and infrastructure, and further ensure that the buildings and infrastructure are designed and constructed to resist expected earthquake loads. This can be done if one can assess the hazard at local scales. Seismic microzonation maps provide the basis for scientifically based decision-making to reduce earthquake risk for Govt./public agencies, private owners and the general public. Further, seismic microzonation carried out on an appropriate scale provides a valuable tool for disaster mitigation planning and emergency response planning for urban centers / municipalities. It provides the basis for the identification of the areas of the city / municipality which are most likely to experience serious damage in the event of an earthquake.
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Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.
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The objective of this paper is to improve option risk monitoring by examining the information content of implied volatility and by introducing the calculation of a single-sum expected risk exposure similar to the Value-at-Risk. The figure is calculated in two steps. First, there is a need to estimate the value of a portfolio of options for a number of different market scenarios, while the second step is to summarize the information content of the estimated scenarios into a single-sum risk measure. This involves the use of probability theory and return distributions, which confronts the user with the problems of non-normality in the return distribution of the underlying asset. Here the hyperbolic distribution is used to describe one alternative for dealing with heavy tails. Results indicate that the information content of implied volatility is useful when predicting future large returns in the underlying asset. Further, the hyperbolic distribution provides a good fit to historical returns enabling a more accurate definition of statistical intervals and extreme events.
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Esta dissertação trata da construção sociológica do conceito de desenvolvimento, caracterizando-o como imaginário social, temporalidade explícita e auto-atribuída do socialhistórico (nos termos de Cornelius Castoriadis). Este imaginário é um conjunto entrelaçado de significações articuladas cosmologicamente e tributárias de uma teologia, mesmo em suas simbologias e concepções secularizadas. Essa cosmologia se sobrepõe a uma concepção de natureza humana distinta e a uma ontologia ocidental dualista. Neste quadro, o desenvolvimento aparece como conceito central da cosmologia ocidental e da ciência social, que orquestra essas significações no imaginário imprimindo a necessidade de uma ordenação de elementos com vistas a uma finalidade paramétrica ou valorativa, uma versão de teodicéia complementada por uma governamentalidade elementos formados pelo encontro da tradição bíblica com o pensamento grego. O desenvolvimento é a expressão paradigmática do imaginário social ocidental. Ao traçar suas características principais, explorando um pouco de suas origens, o conceito de desenvolvimento é reconstruído como um instrumento analítico para permitir a comparação entre as diversas concepções particulares e específicas de desenvolvimento encontradas no pensamento social e na política contemporânea.
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From 2008-2012, a dramatic upsurge in incidents of maritime piracy in the Western Indian Ocean led to renewed global attention to this region: including the deployment of multi national naval patrols, attempts to prosecute suspected pirates, and the development of financial interdiction systems to track and stop the flow of piracy ransoms. Largely seen as the maritime ripple effect of anarchy on land, piracy has been slotted into narratives of state failure and problems of governance and criminality in this region.
This view fails to account for a number of factors that were crucial in making possible the unprecedented rise of Somali piracy and its contemporary transformation. Instead of an emphasis on failed states and crises of governance, my dissertation approaches maritime piracy within a historical and regional configuration of actors and relationships that precede this round of piracy and will outlive it. The story I tell in this work begins before the contemporary upsurge of piracy and closes with a foretaste of the itineraries beyond piracy that are being crafted along the East African coast.
Beginning in the world of port cities in the long nineteenth century, my dissertation locates piracy and the relationship between trade, plunder, and state formation within worlds of exchange, including European incursions into this oceanic space. Scholars of long distance trade have emphasized the sociality engendered through commerce and the centrality of idioms of trust and kinship in structuring mercantile relationships across oceanic divides. To complement this scholarship, my work brings into view the idiom of protection: as a claim to surety, a form of tax, and a moral claim to authority in trans-regional commerce.
To build this theory of protection, my work combines archival sources with a sustained ethnographic engagement in coastal East Africa, including the pirate ports of Northern Somalia, and focuses on the interaction between land-based pastoral economies and maritime trade. This connection between land and sea calls attention to two distinct visions of the ocean: one built around trade and mobility and the other built on the ocean as a space of extraction and sovereignty. Moving between historical encounters over trade and piracy and the development of a national maritime economy during the height of the Somali state, I link the contemporary upsurge of maritime piracy to the confluence of these two conceptualizations of the ocean and the ideas of capture, exchange, and redistribution embedded within them.
The second section of my dissertation reframes piracy as an economy of protection and a form of labor implicated within other legal and illegal economies in the Indian Ocean. Based on extensive field research, including interviews with self-identified pirates, I emphasize the forms of labor, value, and risk that characterize piracy as an economy of protection. The final section of my dissertation focuses on the diverse international, regional, and local responses to maritime piracy. This section locates the response to piracy within a post-Cold War and post-9/11 global order and longer attempts to regulate and assuage the risks of maritime trade. Through an ethnographic focus on maritime insurance markets, navies, and private security contractors, I analyze the centrality of protection as a calculation of risk and profit in the contemporary economy of counter-piracy.
Through this focus on longer histories of trade, empire, and regulation my dissertation reframes maritime piracy as an economy of protection straddling boundaries of land and sea, legality and illegality, law and economy, and history and anthropology.
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We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation of the coordinate system. The advantage of the second method is not only its applicability to any continuous distribution but also the evaluation of the forecast accuracy in specific regions of its domain as defined by the user’s interest. We show that the latter property is particularly useful for evaluating a multidimensional generalization of the Value at Risk. In simulations and in an empirical study, we examine the performance of both tests.
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Les adolescents qui décrochent de l’école secondaire arrivent difficilement à s’intégrer dans une économie axée sur le savoir et éprouvent plusieurs problèmes d’ajustement à l’adolescence et à l’âge adulte. Pour prévenir le décrochage scolaire, une étape cruciale consiste à dépister efficacement les élèves les plus à risque. Deux formes de dépistage axées sur des données peuvent être utilisées en milieu scolaire: une forme utilisant des informations auto-rapportées par les élèves à partir de questionnaires, et une autre fondée sur des informations administratives consignées au dossier des élèves. Toutefois, à notre connaissance, l’efficacité de ces différentes modalités n’a jamais été comparée directement. De plus, il est possible que l’efficacité relative de ces outils de dépistage soit différente selon le sexe de l’élève. Cette étude vise à comparer différents outils de dépistage pour prédire le décrochage scolaire, en tenant compte de l’effet modérateur du sexe. Les outils utilisés seront a) un questionnaire auto-rapporté validé (Archambault et Janosz, 2009) et b) un outil conçu à l’aide de données administratives, créé par une commission scolaire du Québec. La comparaison de ces outils est effectuée en termes de qualités psychométriques et d’aspect pratique pour le milieu scolaire. Pour ce faire, un échantillon de 1557 élèves (50% de garçons), âgé entre 14 et 18 ans est utilisé. Les résultats indiquent que l’indice administratif possède une capacité discriminante adéquate, mais inférieure à celle de l’indice auto-rapportée, jugée excellente. L’effet modérateur du sexe n’a pas été confirmé. Les avantages et inconvénients respectifs de ces deux modes de dépistage sont discutés.
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El presente proyecto tiene como objeto identificar cuáles son los conceptos de salud, enfermedad, epidemiología y riesgo aplicables a las empresas del sector de extracción de petróleo y gas natural en Colombia. Dado, el bajo nivel de predicción de los análisis financieros tradicionales y su insuficiencia, en términos de inversión y toma de decisiones a largo plazo, además de no considerar variables como el riesgo y las expectativas de futuro, surge la necesidad de abordar diferentes perspectivas y modelos integradores. Esta apreciación es pertinente dentro del sector de extracción de petróleo y gas natural, debido a la creciente inversión extranjera que ha reportado, US$2.862 millones en el 2010, cifra mayor a diez veces su valor en el año 2003. Así pues, se podrían desarrollar modelos multi-dimensional, con base en los conceptos de salud financiera, epidemiológicos y estadísticos. El termino de salud y su adopción en el sector empresarial, resulta útil y mantiene una coherencia conceptual, evidenciando una presencia de diferentes subsistemas o factores interactuantes e interconectados. Es necesario mencionar también, que un modelo multidimensional (multi-stage) debe tener en cuenta el riesgo y el análisis epidemiológico ha demostrado ser útil al momento de determinarlo e integrarlo en el sistema junto a otros conceptos, como la razón de riesgo y riesgo relativo. Esto se analizará mediante un estudio teórico-conceptual, que complementa un estudio previo, para contribuir al proyecto de finanzas corporativas de la línea de investigación en Gerencia.
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Las actividades de mantenimiento automotriz en el sector de autopartes conlleva el uso de agentes químicos bajo diversas circunstancias de exposición, tanto en las condiciones de manipulación de productos químicos como a las características propias de cada actividad de mantenimiento asociado a las tareas específicas del trabajo. Tradicionalmente la evaluación de contaminantes químicos desde la visión de la Higiene Ocupacional incluye la evaluación cuantitativa de la exposición mediante técnicas instrumentales concretas y estandarizadas, determinando el nivel de concentración en aire a la cual un trabajador se ve expuesto y que, en comparación con valores límites permisibles (VLPs), inducen el establecimiento de medidas de control y vigilancia, según el nivel de riesgo caracterizado. Sin embargo es evidente la limitación de la implementación de esta sistemática en particular en micros y pequeñas empresas que carecen de los recursos suficientes para abordar la problemática de forma objetiva. En este contexto diversas metodologías de evaluación cualitativa o subjetiva se han desarrollado por distintas organizaciones en el mundo con el fin de disminuir la brecha entre el establecimiento de medidas de control y la valoración del riesgo, ofreciendo alternativas confiables para la toma de decisiones preventivas sin la necesidad de acudir a mediciones cuantitativas. Mediante la presente investigación se pretende validar la efectividad en el uso de una herramienta de evaluación simplificada del riesgo químico propuesta por el INRS (Institut National de Recherche et de Sécurité Francés) mediante la determinación del perfil de exposición potencial a contaminantes químicos de la población laboral de 36 almacenes de autopartes ubicados en el barrio la Paz de la ciudad de Bogotá, Colombia, divididos según énfasis de actividades en Partes Externas, Partes Eléctricas e Inyección, Partes Mecánicas, Partes Múltiples, a través de un estudio de corte transversal. El estudio permitió Jerarquizar el riesgo potencial, valorar el riesgo vía inhalatoria y dérmica para finalmente construir el perfil de exposición potencial a contaminantes químicos de trabajadores. La información de las variables de análisis fue consolidada en una herramienta informática diseñada para tal fin, la cual facilito la administración de los datos y su respectivo análisis. Con base en los hallazgos fue posible establecer los productos químicos que de acuerdo a las condiciones de trabajo y circunstancias de exposición sugieren medidas específicas para la disminución del riesgo potencial de acuerdo a la calificación global de los agentes, permitiendo deducir la viabilidad de la aplicación de herramientas de valoración cualitativa para la evaluación del riesgo químico como estrategia de prevención primaria.
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The abattoir and the fallen stock surveys constitute the active surveillance component aimed at improving the detection of scrapie across the European Union. Previous studies have suggested the occurrence of significant differences in the operation of the surveys across the EU. In the present study we assessed the standardisation of the surveys throughout time across the EU and identified clusters of countries with similar underlying characteristics allowing comparisons between them. In the absence of sufficient covariate information to explain the observed variability across countries, we modelled the unobserved heterogeneity by means of non-parametric distributions on the risk ratios of the fallen stock over the abattoir survey. More specifically, we used the profile likelihood method on 2003, 2004 and 2005 active surveillance data for 18 European countries on classical scrapie, and on 2004 and 2005 data for atypical scrapie separately. We extended our analyses to include the limited covariate information available, more specifically, the proportion of the adult sheep population sampled by the fallen stock survey every year. Our results show that the between-country heterogeneity dropped in 2004 and 2005 relative to that of 2003 for classical scrapie. As a consequence, the number of clusters in the last two years was also reduced indicating the gradual standardisation of the surveillance efforts across the EU. The crude analyses of the atypical data grouped all the countries in one cluster and showed non-significant gain in the detection of this type of scrapie by any of the two sources. The proportion of the population sampled by the fallen stock appeared significantly associated with our risk ratio for both types of scrapie, although in opposite directions: negative for classical and positive for atypical. The initial justification for the fallen stock, targeting a high-risk population to increase the likelihood of case finding, appears compromised for both types of scrapie in some countries.
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Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk. A quantile forecast is the product of two factors: the model used to forecast volatility, and the method of computing quantiles from the volatility forecasts. In this paper we calculate and evaluate quantile forecasts of the daily exchange rate returns of five currencies. The forecasting models that have been used in recent analyses of the predictability of daily realized volatility permit a comparison of the predictive power of different measures of intraday variation and intraday returns in forecasting exchange rate variability. The methods of computing quantile forecasts include making distributional assumptions for future daily returns as well as using the empirical distribution of predicted standardized returns with both rolling and recursive samples. Our main findings are that the Heterogenous Autoregressive model provides more accurate volatility and quantile forecasts for currencies which experience shifts in volatility, such as the Canadian dollar, and that the use of the empirical distribution to calculate quantiles can improve forecasts when there are shifts
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The purpose of this article is to explore customer retention strategies and tactics implemented by firms in recession. Our investigations show just how big a challenge many organizations face in their ability to manage customer retention effectively. While leading organizations have embedded real-time customer life cycle management, developed accurate early warning systems, price elasticity models and ‘deal calculators’, the organizations we spoke to have only gone as far as calculating the value at risk and building simple predictive models.