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Decomposição da Cross-Sectional Correlation no Mercado de Ações Portuguesas
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Autores
Orientador(es)
Resumo(s)
Com a evolução constante do mundo financeiro e com a globalização económica e respetiva
divulgação de informação, é fundamental criar um modelo estimativo que aborde as variações
temporais da correlação para beneficiar investidores, através da sua diversificação da carteira
e redução do risco. O objetivo principal da dissertação é abordar a temática da Decomposição
da Cross-Sectional Correlation no Mercado de Ações Portuguesas, com foco específico no PSI.
A comparação com a Time-Series Correlation acarreta peso na dissertação ao obter-se o
entendimento de que, o método Cross-Sectional, se torna imprescindível dada a sua
atualidade. O estudo visa analisar as correlações entre diferentes ativos financeiros num
determinado período de tempo, fornecendo insights importantes para a análise e gestão de
risco em investimentos. A aplicação do modelo tem uma perspetiva de implementação
simples e instantânea sobre as tendências de correlação globais, bem como o
acompanhamento do comportamento dos dados em análise. O período de observação
compreende os anos de 2000 a 2023, em Portugal, com a existência de dois períodos
revelatórios para análise, sendo eles a crise financeira global e consequente choque
económico no país e a pandemia COVID-19.
With the constant evolution of the financial world and the economic globalization with the respective dissemination of information, it is essential to create an estimation model that addresses the temporal variations of correlation in order to benefit investors through portfolio diversification and risk reduction. The main aim of this dissertation is to address the topic of Cross-Sectional Correlation Decomposition in Portuguese Stock Market, with a specific focus on the PSI. The comparison with the Time-Series Correlation carries weight in the dissertation as we realise that the Cross-Sectional method becomes essential given its relevance. The study aims to analyse the correlations between different financial assets over a specific period of time, providing important insights for analysing and managing investment risk. The application of the model has a simple and instantaneous implementation perspective on global correlation trends, as well as monitoring the behaviour of the data under analysis. The observation period covers the years 2000 to 2023 in Portugal, with two revealing periods for analysis, namely the global financial crisis and consequent economic shock in the country and the COVID-19 pandemic.
With the constant evolution of the financial world and the economic globalization with the respective dissemination of information, it is essential to create an estimation model that addresses the temporal variations of correlation in order to benefit investors through portfolio diversification and risk reduction. The main aim of this dissertation is to address the topic of Cross-Sectional Correlation Decomposition in Portuguese Stock Market, with a specific focus on the PSI. The comparison with the Time-Series Correlation carries weight in the dissertation as we realise that the Cross-Sectional method becomes essential given its relevance. The study aims to analyse the correlations between different financial assets over a specific period of time, providing important insights for analysing and managing investment risk. The application of the model has a simple and instantaneous implementation perspective on global correlation trends, as well as monitoring the behaviour of the data under analysis. The observation period covers the years 2000 to 2023 in Portugal, with two revealing periods for analysis, namely the global financial crisis and consequent economic shock in the country and the COVID-19 pandemic.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
Palavras-chave
Correlation Cross-Sectional Risco Dispersão Volatilidade SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 4 - Educação de qualidade SDG 8 - Trabalho decente e crescimento economico