Master-Arbeit Univ. St. Gallen, 2007.

Master-Arbeit Univ. St. Gallen, 2007.

Master-Arbeit Univ. St. Gallen, 2007.

Master-Arbeit Univ. St. Gallen, 2007.

Techn. University, Diss., 2003--Kaiserslautern.

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Estatística, 2015. / Submitted by Fernanda Percia França (fernandafranca@bce.unb.br) on 2016-03-22T19:46:38Z No. of bitstreams: 1 2015_YuriSampaioMaluf.pdf: 4291479 bytes, checksum: 4a9954a7905294836d257652f0ce1753 (MD5) / Approved for entry into archive by Marília Freitas(marilia@bce.unb.br) on 2016-05-26T16:30:44Z (GMT) No. of bitstreams: 1 2015_YuriSampaioMaluf.pdf: 4291479 bytes, checksum: 4a9954a7905294836d257652f0ce1753 (MD5) / Made available in DSpace on 2016-05-26T16:30:44Z (GMT). No. of bitstreams: 1 2015_YuriSampaioMaluf.pdf: 4291479 bytes, checksum: 4a9954a7905294836d257652f0ce1753 (MD5) / Neste trabalho, estudamos a formulação da distribuição de funções de variáveis aleatórias contínuas dependentes. O mecanismo de modelagem da dependência é feita via funções cópulas. Dentre os resultados obtidos formulamos a expressão geral da distribuição da soma de n variáveis aleatórias dependentes. Expandimos a abordagem para a distribuição de outras funções de variáveis aleatórias tais como o quociente, produto e uma combinação convexa. Por meio das R-Vines Cópulas, obtivermos também a expressão da soma de n variáveis aleatórias em que cada componente é governada por um processo GARCH. A partir deste resultado, calculamos o Value-at-Risk (VaR) e Expected Shortfalls (ES) da soma dessas variáveis. Em função desta estrutura, as medidas de risco passam a adquirir um comportamento dinâmico. Ao final do trabalho exibimos algumas ilustrações numéricas via simulação de Monte Carlo. Apresentamos também uma aplicação com dados reais provenientes de bolsas de valores da América Latina. / In this thesis, we studied the distribution of function of dependents continuous random variables. The modeling dependencies structures are made via copula functions. We obtain the general expression of the distribution of the sum of n dependents random variables. This approach is expanded for other functions such as ratio, product and a convex combination. Using R-Vines Copulas, we also derive an expression of the sum of n dependents random variables, being each component governed by AR-GARCH process. From these results, we assess the Value-at-Risk (VaR) and Expected Shortfalls (ES) of the sum of these variables. According to this structure, the VaR takes a dynamic behavior. At the end of this thesis, we show some numerical illustrations via Monte Carlo simulation. An application with real data from Latin American stock markets is also presented.

Orientador: Jose Mario Martinez Perez / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-10T15:09:35Z (GMT). No. of bitstreams: 1 Bueno_LuisFelipeCesardaRocha_M.pdf: 1111693 bytes, checksum: 531a933822f5dcf9cacad7dea6be5f53 (MD5) Previous issue date: 2008 / Resumo: Nesta dissertacao fazemos uma exposicao sobre alguns modelos matematicos com aplicacoes em economia. Dentre os modelos estudados destacamos a versao discreta das populares medidas de risco VaR (Value at Risk ) e C-VaR (Conditional Value at Risk ). Discutimos algumas propriedades de tais medidas, e, principalmente, expomos sobre algumas ideias para otimiza-las sob uma formulação do tipo OVO (Order Value Optimization) e propomos uma nova formulação para o problema de minimizar a VaR / Abstract: In this dissertation we make a presentation on some mathematical models with applications in economics. Among the studied models we highlight a discrete version of the popular risk measures VaR (Value at Risk) and C-VaR (Conditional Value at Risk). We discuss about some properties of such measures, and, above all, expose on some ideas for optimizing the VaR and CVaR under a OVO (Order Value Optimization) formulation and propose a new formulation to the problem of minimizing the VaR / Mestrado / Otimização / Mestre em Matemática Aplicada

The aim of this diploma thesis is to theoretically describe the risks connected to entrepreneurship. Stress is put mainly on financial risks that are related to price shifts of agricultural commodities and to changes in the exchange rates. The basis lies in theoretical identification of the nature of possible risks, methods of risk evaluation and description of instruments that serve for the risk elimination. This theoretical knowledge is further applied in case studies dealing with hedging of commodity and currency risks of firms that conduct business in agricultural basic industry. The analysis of firm's position, demonstration of hedging and final evaluation of efficiency are included.

The graduation thesis addresses the problems of managing and measuring of financial risks in activities of insurance companies. The first chapter handles the definitions of the financial risk and it classification. The second chapter defines a random variable returns of measure of financial assets. Sets up formulas of the return measure and also focuses on problem of time aggregation. The third chapter theoretically describes methodology of value at risk as the most widely used method for measuring and managing risk by insurance companies and regulatory authority. The fourth chapter contains an empirical study from practice which compares the two basic method of computing value at risk. The fifth chapter is the main part of the graduation thesis and focuses on verifying of the model and his imperfections. It verifies also achievements of initial assumptions. The sixth chapter targets on possibilities of extension value at risk method by liquidity risk incorporation.

This thesis deals with commodity risk and its context. It concerns the commodity market, types of traded commodities, exchanges on which commodities are traded and pricing method usual for commodity market. The first section of the thesis consists of a theoretical perspective on measuring commodity risk and describes the derivatives used to hedging commodities. In the second section is a key part of the work calculations of the statistical characteristics of commodities, practical methods of measuring risk, modeling Value at Risk, stress scenarios and measuring risk using hedging transactions in the financial market. The aim is to measure the commodity risk for various risk situations on a commodity market.