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Calculations of the value at risk for a diversified portfolio
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O presente relatório apresenta o trabalho realizado num estágio curricular com duração de cinco meses e meio na seguradora Fidelidade, na equipa de Asset and Liability Management, pertencente à Direção de Gestão de Risco. O principal objetivo do estágio foi desenvolver um modelo em R que permitisse calcular o Value-at-Risk (VaR) da carteira da Fidelidade de forma eficiente, dada a complexidade de cálculo necessária para uma carteira diversificada.
Para melhorar as metodologias de gestão de risco da empresa, o processo de desenvolvimento do modelo em R iniciou-se com a pesquisa das principais metodologias de cálculo do VaR. O método escolhido, dadas as características da carteira da Fidelidade, foi o método da simulação de Monte Carlo. Uma vez que os instrumentos de renda fixa têm características específicas, utilizamos uma metodologia diferente das metodologias de “VaR mapping” (também analisadas), chamada de “New approach”, para que o cálculo do VaR pudesse ser similar ao realizado noutras classes de ativos. Devido a restrições de tempo, as classes de ativos como derivados, participações e investimentos estratégicos não foram incluídos na análise da carteira.
Utilizando dados históricos de um ano, com data de referência de 31 de dezembro de 2021, desenvolvemos o modelo em RStudio. O modelo foi testado inicialmente por classe de ativo e, posteriormente, aplicado à totalidade da carteira. Para validar os resultados utilizamos a ferramenta “PORT” da plataforma Bloomberg que produziu resultados próximos aos nossos, validando até certo ponto a performance do modelo criado.
This report presents the work produced during a five-and-a-half-months curricular internship at the insurance company Fidelidade, in the Asset and Liability Management team, which is part of the Risk Management Department. The main goal of the internship was to develop an R model that would allow the Value-at-Risk (VaR) of Fidelidade’s portfolio to be calculated efficiently, given the complexity of the calculation required for a diversified portfolio. In order to improve the company’s risk management methodologies, the process of developing the R model began with research into the main methodologies for calculating the VaR. Given the characteristics of Fidelidade’s portfolio, the Monte Carlo simulation method was chosen. Since fixed income instruments have specific characteristics, we used a methodology different from the “VaR mapping” approaches (also analysed), called the “New approach”, so that the VaR calculation could be similar to that applied to other asset classes. Due to time constraints, asset classes such as derivatives, participations and strategic investments were not included in the portfolio analysis. We developed the model in RStudio, using one year of historical data with a reference date of 31st of December 2021. The model was first tested by asset class and then applied to the entire portfolio. To validate the results, we used the “PORT” tool on the Bloomberg platform, which produced results close to our own, thus validating the performance of the model created to a certain extent.
This report presents the work produced during a five-and-a-half-months curricular internship at the insurance company Fidelidade, in the Asset and Liability Management team, which is part of the Risk Management Department. The main goal of the internship was to develop an R model that would allow the Value-at-Risk (VaR) of Fidelidade’s portfolio to be calculated efficiently, given the complexity of the calculation required for a diversified portfolio. In order to improve the company’s risk management methodologies, the process of developing the R model began with research into the main methodologies for calculating the VaR. Given the characteristics of Fidelidade’s portfolio, the Monte Carlo simulation method was chosen. Since fixed income instruments have specific characteristics, we used a methodology different from the “VaR mapping” approaches (also analysed), called the “New approach”, so that the VaR calculation could be similar to that applied to other asset classes. Due to time constraints, asset classes such as derivatives, participations and strategic investments were not included in the portfolio analysis. We developed the model in RStudio, using one year of historical data with a reference date of 31st of December 2021. The model was first tested by asset class and then applied to the entire portfolio. To validate the results, we used the “PORT” tool on the Bloomberg platform, which produced results close to our own, thus validating the performance of the model created to a certain extent.
Descrição
Mestrado Bolonha em Mathematical Finance
Palavras-chave
Value-at-Risk R Simulação de Monte Carlo Gestão de Risco Monte Carlo Simulation Risk Management
Contexto Educativo
Citação
Silva, Ana Beatriz Teodoro da (2023). “Calculations of the value at risk for a diversified portfolio”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão
Editora
Instituto Superior de Economia e Gestão