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Aplicação da metodologia LDA para gestão do risco operacional de companhia seguradoraAssad, Alaim Mosciaro 19 August 2013 (has links)
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Previous issue date: 2013-08-19 / Fundo Mackenzie de Pesquisa / The Operational Risk did not receive much attention from firms, regulators and the market
until the event of the fraud on Bahrings Bank, in 1995. The regulatory agencies have issued
more complex and rigorous regulations in reply to this and to many other events of
operational losses. Their goal is to improve the quality of the controls of the financial
institutions, as well as to mitigate the occurrence of new events of this kind. As a new
discipline, the regulatory agencies have been incentivizing the financial firms to develop
advance approaches based on internal models. In response, they shall have a decrease on the
regulatory capital applicable. In other hand, the financial firms themselves shall benefit from
na internal model that fits their characteristics, and so, as taylor made. The goal of this
research is to study the development of an internal model for operational risk, based on LDA,
which has been largely used by financial firms worldwide. The focus on an Insurance
company is due to the expressive growth of this market in the later years, which has giving it
an increasing importance to the national economy as well as institutional investors role. / Até 1995, com a fraude do Banco Bahrings, não era dada maior relevância ao Risco
Operacional pelas firmas, órgãos reguladores e pelo mercado em geral. Após esse e uma série
de outros eventos de perdas, algumas delas com consequências desastrosas para o mercado
financeiro, os órgãos reguladores passaram a publicar regulamentações cada vez mais
rigorosas, para melhorar o controle das instituições financeiras, e evitar a ocorrência de novas
perdas. Esses requerimentos regulatórios, dado o seu caráter ainda incipiente, estimulam o
desenvolvimento de técnicas de abordagens avançadas, calcadas em modelos internos, com a
promessa que, como um modelo de gestão adequado às características de cada instituição será
mais eficiente, em consequência, reduzirá a necessidade de capital regulatório. Esta pesquisa
encaixa-se no rol desse desenvolvimento do conhecimento das técnicas de gestão avançadas
do Risco Operacional, ao abordar o desenvolvimento de um modelo de gestão de Riscos
Operacionais baseado numa dessas técnicas avançadas: a distribuição de perdas operacionais
(LDA). A LDA vem sendo cada vez mais utilizada pelas instituições financeiras
internacionais, e seu uso já é previsto nos normativos regulamentares nacionais em fase de
audiência pública. A ênfase da aplicação desta pesquisa numa companhia seguradora se deve
ao expressivo crescimento do setor nos últimos anos, que vem lhe conferindo importância
cada vez maior na economia, especialmente quanto ao seu papel de investidor institucional.
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Measuring and managing operational risk in the insurance and banking sectors / Mesure et gestion du risque opérationnel en assurance et financeKaram, Elias 26 June 2014 (has links)
Notre intérêt dans cette thèse est de combiner les différentes techniques de mesure du risque opérationnel dans les secteurs financiers, et on s'intéresse plus particulièrement aux conséquences du risque d'estimation dans les modèles, qui est un risque opérationnel particulier. Nous allons présenter les concepts mathématiques et actuariels associés ainsi qu'une application numérique en ce qui concerne l'approche de mesure avancée comme Loss Distribution pour calculer l'exigence en capital. En plus, on se concentre sur le risque d'estimation illustré avec l'analyse des scénarios de l'opinion d'experts en conjonction avec des données de pertes internes pour évaluer notre exposition aux évènements de gravité. Nous concluons cette première partie en définissant une technique de mise l'échelle sur la base de (MCO) qui nous permet de normaliser nos données externes à une banque locale Libanaise.Dans la deuxième partie, on donne de l'importance sur la mesure de l'erreur induite sur le SCR par l'erreur d'estimation des paramètres, on propose une méthode alternative pour estimer une courbe de taux et on termine par attirer l'attention sur les réflexions autour des hypothèses de calcul et ce que l'on convient de qualifier d'hypothèse "cohérente avec les valeurs de marché" serait bien plus pertinente et efficace que la complexification du modèle, source d'instabilité supplémentaire, ainsi mettre en évidence le risque d'estimation qui est lié au risque opérationnel et doit être accordé beaucoup plus d'attention dans nos modèles de travail / Our interest in this thesis is first to combine the different measurement techniques for operational risk in financial companies, and we highlight more and more the consequences of estimation risk which is treated as a particular part of operational risk. In the first part, we will present a full overview of operational risk, from the regulatory laws and regulations to the associated mathematical and actuarial concepts as well as a numerical application regarding the Advanced Measurement Approach, like Loss Distribution to calculate the capital requirement, then applying the Extreme Value Theory. We conclude this first part by setting a scaling technique based on (OLS) enabling us to normalize our external data to a local Lebanese Bank. On the second part, we feature estimation risk by first measuring the error induced on the SCR by the estimation error of the parameters, to having an alternative yield curve estimation and finishing by calling attention to the reflections on assumptions of the calculation instead of focusing on the so called hypothesis "consistent with market values", would be more appropriate and effective than to complicate models and generate additional errors and instability. Chapters in this part illustrate the estimation risk in its different aspects which is a part of operational risk, highlighting as so the attention that should be given in treating our models
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Simulação de Monte Carlo para mensuração do risco operacional: aplicação do modelo LDAGabbay, Arthur Monteiro 11 August 2010 (has links)
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Previous issue date: 2010-08-11 / Fundo Mackenzie de Pesquisa / Many authors consider Operational Risk as a key variable for maintaining the balance of the global financial market. The objective of this dissertation is to study the development of a Advanced Measurement Approach (AMA), specifically the Loss Distribution Approach (LDA) on a database of actual operational losses. Being more specifically, this study promotes an analysis about the results and possible limitations related to the implementation of the model. To achieve these goals, it is needed to discuss the definitions of Operational Risk, Monte Carlo Simulation and value-at-risk (VaR), considering that these concepts are crucial to the implementation of the LDA. / O risco operacional é considerado por muitos autores uma variável determinante para a manutenção do equilíbrio do mercado financeiro global. O objetivo desta dissertação é
estudar o desenvolvimento de uma modelo de Abordagem de Mensuração Avançada (AMA),mais especificamente a Loss Distribution Approach (LDA), sobre um banco de dados reais de
perdas operacionais. Mais especificamente este estudo promove uma análise sobre os resultados e sobre eventuais limitações relacionadas à aplicação do modelo. Para realização
destes objetivos, abordam-se as definições do risco operacional, simulação de Monte Carlo e value-at-risk (VaR), haja vista que estes são conceitos cruciais para a aplicação do LDA.
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Redes Bayesianas no gerenciamento e mensuração de riscos operacionais. / Managing and measuring operation risks using Bayesian networks.Queiroz, Cláudio De Nardi 14 November 2008 (has links)
A aplicação de Redes Bayesianas como modelo causal em Risco Operacional e extremamente atrativa do ponto de vista do gerenciamento dos riscos e do calculo do capital regulatorio do primeiro pilar do Novo Acordo da Basileia. Com as Redes e possível obter uma estimativa do VAR operacional utilizando-se não somente os dados históricos de perdas, mas também variáveis explicativas e conhecimento especialista através da possibilidade de inclusão de informações subjetivas. / The application of Bayesian Networks as causal model in Operational Risk is very attractive from the point of view of risk management and the calculation of regulatory capital under the first pillar of the New Basel Accord. It is possible to obtain with the networks an estimate of operational VAR based not only on the historical loss data but also in explanatory variables and expert knowledge through the possibility of inclusion of subjective information.
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Redes Bayesianas no gerenciamento e mensuração de riscos operacionais. / Managing and measuring operation risks using Bayesian networks.Cláudio De Nardi Queiroz 14 November 2008 (has links)
A aplicação de Redes Bayesianas como modelo causal em Risco Operacional e extremamente atrativa do ponto de vista do gerenciamento dos riscos e do calculo do capital regulatorio do primeiro pilar do Novo Acordo da Basileia. Com as Redes e possível obter uma estimativa do VAR operacional utilizando-se não somente os dados históricos de perdas, mas também variáveis explicativas e conhecimento especialista através da possibilidade de inclusão de informações subjetivas. / The application of Bayesian Networks as causal model in Operational Risk is very attractive from the point of view of risk management and the calculation of regulatory capital under the first pillar of the New Basel Accord. It is possible to obtain with the networks an estimate of operational VAR based not only on the historical loss data but also in explanatory variables and expert knowledge through the possibility of inclusion of subjective information.
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特別處理監管制度與盈餘管理 / Special Treatments Policy and Earnings Management李東峰, Lee, Tung Feng, Unknown Date (has links)
中國證監會於1998年設置特別處理政策(special treatment policy, ST)以管理上市公司是否得持續保有上市的狀態,在該制度下,上市公司如果連續報導二年虧損,其股票將被標記「特別處理」。為了瞭解中國證券市場避免虧損的盈餘管理現象是證券市場誘因或是ST政策誘因所致,本文以ST監管政策的臺灣證券市場為對照樣本,以檢視ST政策影響中國上市公司盈餘管理的證據。主要研究結果為:
一、不論是臺灣上市公司或中國上市公司,都可以很清楚的看到在0%附近出現了明顯的跳動,都有為了避免虧損的盈餘管理現象。
二、中國大陸證券市場在1998年特別處理制度實施後,小額利潤佔利潤公司家數比例與小額虧損公司佔虧損公司家數比例之差異比呈現顯著上升趨勢,足見有比較多的公司會操弄盈餘通過零盈餘的門檻。
三、在排除非ST政策環境下所固有的避免虧損之證券市場誘因盈餘管理現象後,中國證券市場的差異比仍明顯集中於0%上方,這種避免虧損的嚴重傾向說明了ST監管制度為中國大陸上市公司避免虧損盈餘管理的政策誘因。
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Modelagem de perdas com ações trabalhistas em instituições financeirasRachman, Luciano 07 August 2013 (has links)
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Previous issue date: 2013-08-07 / As perdas trabalhistas nas Instituições Financeiras representam um valor considerável que devem ser consideradas no modelo de capital regulatório para risco operacional, segundo Basileia. A presente dissertação demonstra uma forma de mensurar o risco às quais as Instituições Financeiras estão expostas nesse tipo de perdas. Diversos tipos de distribuições são analisados conforme sua aderência tanto na frequência como na severidade das perdas. Para os valores de frequência, foi obtida uma amostra de dados real, enquanto para a severidade foram utilizados valores obtidos de relatórios de instituto de pesquisa que serviram de insumo para os cálculos de ações trabalhistas conforme legislação brasileira vigente na CLT (Consolidação das Leis do Trabalho). / According to Basel, the labor losses in Financial Institutions represent a substantial value that should be regarded in the model of regulatory capital for operational risk. This dissertation demonstrates a way to measure the risk to which Financial Institutions are exposed to in this type of loss. Several types of distributions are analyzed according to their adherence both in frequency and severity of losses. For frequency values, it was obtained a sample of actual data, whilst for the severity were used values given from reports of research institute which served as an input for the calculations of labor actions according to the present Brazilian legislation in CLT (Consolidation of Labor Laws).
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[pt] IMPLEMENTAÇÃO DE SOFTWARE PARA APOIO AO GERENCIAMENTO DE RISCO OPERACIONAL / [en] SOFTWARE IMPLEMENTATION FOR OPERATIONAL RISK MANAGEMENT SUPPORTJOSE LUIS COUTO LYRA JUNIOR 29 December 2005 (has links)
[pt] O gerenciamento de risco em instituições bancárias, mais
do que mera
imposição das agências reguladoras distingue-se como fator
de sucesso na
melhoria dos processos, aumentando o resultado financeiro.
Após o Acordo da
Basiléia, a gerência de riscos de mercado e de crédito,
cuja atuação se dá sobre
as receitas, passou a ser realizada. Entretanto, alguns
riscos atuam sobre as
despesas, destacando-se o operacional, que é o risco de
perdas oriundas de
problemas com controles internos, sistemas, pessoas e
eventos externos. O
objetivo deste trabalho foi elaborar uma revisão
abrangente da literatura e um
protótipo de sistema computacional que permite medir o VaR
do risco
operacional de uma unidade de risco, utilizando o Modelo
de Distribuição de
Perdas (LDA), e aplicar modelos causais que expliquem
estas perdas. Este
protótipo é uma aplicação Internet/intranet desenvolvida
na linguagem ASP e
utilizou o MS-Access como banco de dados. Para os cálculos
estatísticos,
implementou-se uma interface de comunicação
aplicação/MATLAB. A revisão da
literatura objetivou a familiarização com conceitos
básicos de risco operacional
descritos pelo Comitê da Basiléia. Adicionalmente,
apresentou detalhes técnicos
para implementação do LDA, tais como Distribuição de
Freqüência e de
Severidade, métodos para determinação da distribuição de
perdas operacionais
e construção da base de dados de perdas. Independente das
particularidades
institucionais, esse protótipo permite a visualização das
providências
estratégicas e operacionais a serem tomadas para
implementação e implantação
de um sistema similar. Marca um ponto de partida para o
desenvolvimento de
um produto abrangente de gerenciamento de risco
operacional nas mais
variadas instituições e segmentos de mercado. / [en] The risk management in financial institutions, more than
just an imposition
of the regulatory agencies, represents a success factor in
the processes
enhancement, elevating the financial results. After Basel
Accord, credit and
market risks management, which acts over earnings, were
implemented.
However, some risks are associated to the expenses, such
as the operational
risk, related to the losses from internal control,
systems, human and external
events problems. The aim of the present study was the
elaboration of an
extensive literature review and the development of a
computation system
prototype able to measure the operational risk VaR of a
risk unit, using the Loss
Distribution Approach (LDA) and to apply causal models
that explain these
losses. This prototype is an Internet/intranet application
developed in ASP
language, using MS-Access as database. For statistical
evaluation, an interface
between the application and MATLAB was implemented. The
literature review
pretended to give a better understanding of the basic
concepts of operational risk
described by the Basel Committee. In addition, it
presented technical details for
LDA implementation, such as Frequency and Severity
Distribution, methods for
the distribution of the operational losses determination
and losses database
construction. Independent of institutional peculiarities,
this prototype allows the
observation of strategic and operational providences to be
taken for
implementation and implantation of a similar system. It
determines a startingpoint
in the development of an operational risk management
product valuable in
several institutions and market segments.
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Použití koherentních metod měření rizika v modelování operačních rizik / The use of coherent risk measures in operational risk modelingLebovič, Michal January 2012 (has links)
The debate on quantitative operational risk modeling has only started at the beginning of the last decade and the best-practices are still far from being established. Estimation of capital requirements for operational risk under Advanced Measurement Approaches of Basel II is critically dependent on the choice of risk measure, which quantifies the risk exposure based on the underlying simulated distribution of losses. Despite its well-known caveats Value-at-Risk remains a predominant risk measure used in the context of operational risk management. We describe several serious drawbacks of Value-at-Risk and explain why it can possibly lead to misleading conclusions. As a remedy we suggest the use of coherent risk measures - and namely the statistic known as Expected Shortfall - as a suitable alternative or complement for quantification of operational risk exposure. We demonstrate that application of Expected Shortfall in operational loss modeling is feasible and produces reasonable and consistent results. We also consider a variety of statistical techniques for modeling of underlying loss distribution and evaluate extreme value theory framework as the most suitable for this purpose. Using stress tests we further compare the robustness and consistency of selected models and their implied risk capital estimates...
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Measuring and managing operational risk in the insurance and banking sectorsKaram, Elias 26 June 2014 (has links) (PDF)
Our interest in this thesis is first to combine the different measurement techniques for operational risk in financial companies, and we highlight more and more the consequences of estimation risk which is treated as a particular part of operational risk. In the first part, we will present a full overview of operational risk, from the regulatory laws and regulations to the associated mathematical and actuarial concepts as well as a numerical application regarding the Advanced Measurement Approach, like Loss Distribution to calculate the capital requirement, then applying the Extreme Value Theory. We conclude this first part by setting a scaling technique based on (OLS) enabling us to normalize our external data to a local Lebanese Bank. On the second part, we feature estimation risk by first measuring the error induced on the SCR by the estimation error of the parameters, to having an alternative yield curve estimation and finishing by calling attention to the reflections on assumptions of the calculation instead of focusing on the so called hypothesis "consistent with market values", would be more appropriate and effective than to complicate models and generate additional errors and instability. Chapters in this part illustrate the estimation risk in its different aspects which is a part of operational risk, highlighting as so the attention that should be given in treating our models
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