Modelling main worldwide financial índices risk management: so far, but so close!/

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Fonseca, Ronald Bernardes
Orientador(a): Matos, Paulo Rogério Faustino
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/15296
Resumo: This paper enter into the search of a refined and trustable metric for measuring financial risk. RiskMetrics (1994) marked the start of this search and since them many researches contributed with innovations and new models for that measure, and here we find a stepforward into the search, by aggregating multivariate models, with this it’s possible to capture the effect of a worldwide contagion and financial interdependence. The group of 10 countries presents in this study represents 49,9% of world GDP and has representation across 5 continents. We follow the model of volatilities suggested in Cappielo, Engle e Sheppard (2006) and Value-at-Risk follows Matos, Cruz, Macedo e Jucá (CAEN-UFC Working paper), though this procedure it’s possible to accurate VaR model, and take in count the contagion and interdependence between markets, in long term. Our results are robust to problems with omitted variable, heteroskedasticity and endogeneity. We also take into account for structural break. According to our results, the interdependence plays an important role into financial risk measure process, although its until now usually forbidden by modelers, mostly because world’s financial integration leads the global economies to the scenario of increasing dependence among them and contagion effect that spreads the impacts that occur into one market to the others. We invite researchers to revisit this issue in order obtain evidences using larger data and other countries as well. We claim that the world is year by year more globalized, and so are the other economies, here we add this into account for measuring financial risks. This leads to model, legal and internal, more accurate that help supervisors to guarantee the long term stability across the markets, have trustable measure of the financial institutions under their responsibility. Besides, helps the Risk Management area of banks and other financial institutions to better understand their risk profile, improve communication with institutional investors worldwide and rank effiently their investments and applications into the markets. Previous studies have a common aspect: they only consider the volatilities change across the domestic market, not tanking in consider the effect of the other countries into the domestic volatility, and this effect here is proven to be important and representative, the univariate domestic risk measure fails more and harder than the multivariate model. That being said, here we take this step, the challenge of modeling no more univariate, domestic risk measures, but a worldwide multivariate. This is a methodological innovation that helps better measure and understands the financial risks behavior across the world.
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spelling Fonseca, Ronald BernardesMatos, Paulo Rogério Faustino2016-02-29T20:26:16Z2016-02-29T20:26:16Z2015FONSECA, Ronald Bernardes. Modelling main worldwide financial índices risk management: so far, but so close! 2015. 42f. Dissertação (mestrado profissional) - Universidade Federal do Ceará, Programa de Pós Graduação em Economia, CAEN, Fortaleza - Ce, 2015http://www.repositorio.ufc.br/handle/riufc/15296This paper enter into the search of a refined and trustable metric for measuring financial risk. RiskMetrics (1994) marked the start of this search and since them many researches contributed with innovations and new models for that measure, and here we find a stepforward into the search, by aggregating multivariate models, with this it’s possible to capture the effect of a worldwide contagion and financial interdependence. The group of 10 countries presents in this study represents 49,9% of world GDP and has representation across 5 continents. We follow the model of volatilities suggested in Cappielo, Engle e Sheppard (2006) and Value-at-Risk follows Matos, Cruz, Macedo e Jucá (CAEN-UFC Working paper), though this procedure it’s possible to accurate VaR model, and take in count the contagion and interdependence between markets, in long term. Our results are robust to problems with omitted variable, heteroskedasticity and endogeneity. We also take into account for structural break. According to our results, the interdependence plays an important role into financial risk measure process, although its until now usually forbidden by modelers, mostly because world’s financial integration leads the global economies to the scenario of increasing dependence among them and contagion effect that spreads the impacts that occur into one market to the others. We invite researchers to revisit this issue in order obtain evidences using larger data and other countries as well. We claim that the world is year by year more globalized, and so are the other economies, here we add this into account for measuring financial risks. This leads to model, legal and internal, more accurate that help supervisors to guarantee the long term stability across the markets, have trustable measure of the financial institutions under their responsibility. Besides, helps the Risk Management area of banks and other financial institutions to better understand their risk profile, improve communication with institutional investors worldwide and rank effiently their investments and applications into the markets. Previous studies have a common aspect: they only consider the volatilities change across the domestic market, not tanking in consider the effect of the other countries into the domestic volatility, and this effect here is proven to be important and representative, the univariate domestic risk measure fails more and harder than the multivariate model. That being said, here we take this step, the challenge of modeling no more univariate, domestic risk measures, but a worldwide multivariate. This is a methodological innovation that helps better measure and understands the financial risks behavior across the world.O presente artigo busca uma métrica refinada e confiável para mensurar riscos financeiros. RiskMetrics (1994) marcou o início dessa busca e desde então vários pesquisadores contribuíram com inovações e novos modelos para essa medida e aqui se apresenta mais um passo desse caminho, ao se agregar uma modelagem multivariada. Com essa modelagem é possível capturar o efeito contágio e a interdependência financeira global. O grupo de 10 países presente no estudo representa 49,9% do PIB mundial e possuem representantes de 5 continentes. O modelo de volatilidade segue sugestão apresentada por Cappielo, Engle e Sheppard (2006) e modelos de Value-at-Risk (VaR) seguem Matos, Cruz, Macedo e Jucá (CAEN-UFC Workingpaper). Através desse procedimento é possível calcular VaR levando em consideração o efeito contágio e a interdependência entre os mercados ao longo do tempo. Os resultados encontrados são robustos contra problemas de variáveis omitidas, heterocedasticidade e endogeneidade, além de considerar quebras estruturais. De acordo com os resultados encontrados, a interdependência apresenta um papel importante dentro do processo de mensuração de risco de mercado, apesar de até agora ter sido esquecida pelos pesquisadores. Isso se deve, principalmente, porque a integração financeira a nível global leva ao cenário de dependência crescente entre os mercados financeiros e, dessa forma, aumentando o contágio de um impacto que ocorre em um mercado nos outros. Convidamos outros pesquisadores a rever nossa metodologia, utilizando inclusive mais informações e incluindo outros países. Acredita-se que o mundo está ano a ano se tornando mais globalizado e suas economias por consequência. Nesse artigo esse efeito está sendo considerado dentro da mensuração do risco de mercado. Incorporar esse efeito leva a modelagem, legal e interna, mais acurada, que ajuda supervisores de mercado a garantirem estabilidade de longo prazo para os mercados e possuírem métricas mais confiáveis dentro das instituições sob sua tutela. Além disso, é de grande valia para áreas de Gestão de Risco de bancos e instituições financeiras ao ajuda-las a compreender melhor seu perfil de risco, melhorar a comunicação com investidores institucionais internacionais e ranquear de maneira mais eficiente seus investimentos e aplicações. Estudos anteriores possuem um aspecto comum: Apenas levam em consideração mudanças de volatilidade nos mercados domésticos, não levando em consideração os efeitos que outros países possuem neles. No presente estudo, esse efeito se provou como importante e representativo, os modelos univariados domésticos falharam mais e com mais severidade que os modelos multivariados. Portanto, no presente artigo, buscou-se o desafio de dar o passo de não mais modelar modelos univariados domésticos, mas modelos 4 multivariados globais. Acredita-se que esse avanço metodológico ajudará a melhor mensurar e entender o comportamento do risco de mercado através do mundo.Administração de riscoRisco financeiroModelling main worldwide financial índices risk management: so far, but so close!/info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2015_dissert_rbfonseca.pdf2015_dissert_rbfonseca.pdfapplication/pdf1358735http://repositorio.ufc.br/bitstream/riufc/15296/1/2015_dissert_rbfonseca.pdfdb31b9a544c323ee192b2f988a2b0123MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81786http://repositorio.ufc.br/bitstream/riufc/15296/2/license.txt8c4401d3d14722a7ca2d07c782a1aab3MD52riufc/152962023-08-17 16:05:16.233oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2023-08-17T19:05:16Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv Modelling main worldwide financial índices risk management: so far, but so close!/
title Modelling main worldwide financial índices risk management: so far, but so close!/
spellingShingle Modelling main worldwide financial índices risk management: so far, but so close!/
Fonseca, Ronald Bernardes
Administração de risco
Risco financeiro
title_short Modelling main worldwide financial índices risk management: so far, but so close!/
title_full Modelling main worldwide financial índices risk management: so far, but so close!/
title_fullStr Modelling main worldwide financial índices risk management: so far, but so close!/
title_full_unstemmed Modelling main worldwide financial índices risk management: so far, but so close!/
title_sort Modelling main worldwide financial índices risk management: so far, but so close!/
author Fonseca, Ronald Bernardes
author_facet Fonseca, Ronald Bernardes
author_role author
dc.contributor.author.fl_str_mv Fonseca, Ronald Bernardes
dc.contributor.advisor1.fl_str_mv Matos, Paulo Rogério Faustino
contributor_str_mv Matos, Paulo Rogério Faustino
dc.subject.por.fl_str_mv Administração de risco
Risco financeiro
topic Administração de risco
Risco financeiro
description This paper enter into the search of a refined and trustable metric for measuring financial risk. RiskMetrics (1994) marked the start of this search and since them many researches contributed with innovations and new models for that measure, and here we find a stepforward into the search, by aggregating multivariate models, with this it’s possible to capture the effect of a worldwide contagion and financial interdependence. The group of 10 countries presents in this study represents 49,9% of world GDP and has representation across 5 continents. We follow the model of volatilities suggested in Cappielo, Engle e Sheppard (2006) and Value-at-Risk follows Matos, Cruz, Macedo e Jucá (CAEN-UFC Working paper), though this procedure it’s possible to accurate VaR model, and take in count the contagion and interdependence between markets, in long term. Our results are robust to problems with omitted variable, heteroskedasticity and endogeneity. We also take into account for structural break. According to our results, the interdependence plays an important role into financial risk measure process, although its until now usually forbidden by modelers, mostly because world’s financial integration leads the global economies to the scenario of increasing dependence among them and contagion effect that spreads the impacts that occur into one market to the others. We invite researchers to revisit this issue in order obtain evidences using larger data and other countries as well. We claim that the world is year by year more globalized, and so are the other economies, here we add this into account for measuring financial risks. This leads to model, legal and internal, more accurate that help supervisors to guarantee the long term stability across the markets, have trustable measure of the financial institutions under their responsibility. Besides, helps the Risk Management area of banks and other financial institutions to better understand their risk profile, improve communication with institutional investors worldwide and rank effiently their investments and applications into the markets. Previous studies have a common aspect: they only consider the volatilities change across the domestic market, not tanking in consider the effect of the other countries into the domestic volatility, and this effect here is proven to be important and representative, the univariate domestic risk measure fails more and harder than the multivariate model. That being said, here we take this step, the challenge of modeling no more univariate, domestic risk measures, but a worldwide multivariate. This is a methodological innovation that helps better measure and understands the financial risks behavior across the world.
publishDate 2015
dc.date.issued.fl_str_mv 2015
dc.date.accessioned.fl_str_mv 2016-02-29T20:26:16Z
dc.date.available.fl_str_mv 2016-02-29T20:26:16Z
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dc.identifier.citation.fl_str_mv FONSECA, Ronald Bernardes. Modelling main worldwide financial índices risk management: so far, but so close! 2015. 42f. Dissertação (mestrado profissional) - Universidade Federal do Ceará, Programa de Pós Graduação em Economia, CAEN, Fortaleza - Ce, 2015
dc.identifier.uri.fl_str_mv http://www.repositorio.ufc.br/handle/riufc/15296
identifier_str_mv FONSECA, Ronald Bernardes. Modelling main worldwide financial índices risk management: so far, but so close! 2015. 42f. Dissertação (mestrado profissional) - Universidade Federal do Ceará, Programa de Pós Graduação em Economia, CAEN, Fortaleza - Ce, 2015
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