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Análise de contágio a partir do modelo de correlação condicional constante com mudança de regime MarkovianaRotta, Pedro Nielsen 18 December 2012 (has links)
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Previous issue date: 2012-12-18 / Nas últimas décadas, a análise dos padrões de propagação internacional de eventos financeiros se tornou o tema de grande parte dos estudos acadêmicos focados em modelos de volatilidade multivariados. Diante deste contexto, objetivo central do presente estudo é avaliar o fenômeno de contágio financeiro entre retornos de índices de Bolsas de Valores de diferentes países a partir de uma abordagem econométrica, apresentada originalmente em Pelletier (2006), sobre a denominação de Regime Switching Dynamic Correlation (RSDC). Tal metodologia envolve a combinação do Modelo de Correlação Condicional Constante (CCC) proposto por Bollerslev (1990) com o Modelo de Mudança de Regime de Markov sugerido por Hamilton e Susmel (1994). Foi feita uma modificação no modelo original RSDC, a introdução do modelo GJR-GARCH formulado em Glosten, Jagannathan e Runkle (1993), na equação das variâncias condicionais individuais das séries para permitir capturar os efeitos assimétricos na volatilidade. A base de dados foi construída com as séries diárias de fechamento dos índices das Bolsas de Valores dos Estados Unidos (SP500), Reino Unido (FTSE100), Brasil (IBOVESPA) e Coréia do Sul (KOSPI) para o período de 02/01/2003 até 20/09/2012. Ao longo do trabalho a metodologia utilizada foi confrontada com outras mais difundidos na literatura, e o modelo RSDC com dois regimes foi definido como o mais apropriado para a amostra selecionada. O conjunto de resultados encontrados fornecem evidências a favor da existência de contágio financeiro entre os mercados dos quatro países considerando a definição de contágio financeiro do Banco Mundial denominada de 'muito restritiva'. Tal conclusão deve ser avaliada com cautela considerando a extensa diversidade de definições de contágio existentes na literatura. / Over the last decades, the analysis of the transmissions of international financial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the financial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modification was made in the original model RSDC, the introduction of the GJR-GARCH Glosten model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric effects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 20/09/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was defined as the most appropriate for the selected sample. The set of results provide evidence for the existence of financial contagion between markets of the four countries considering the definition of financial contagion from the World Bank called 'very restrictive'. Such a conclusion should be evaluated carefully considering the wide diversity of definitions of contagion in the literature.
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Multivariate Financial Time Series and Volatility Models with Applications to Tactical Asset Allocation / Multivariata finansiella tidsserier och volatilitetsmodeller med tillämpningar för taktisk tillgångsallokeringAndersson, Markus January 2015 (has links)
The financial markets have a complex structure and the modelling techniques have recently been more and more complicated. So for a portfolio manager it is very important to find better and more sophisticated modelling techniques especially after the 2007-2008 banking crisis. The idea in this thesis is to find the connection between the components in macroeconomic environment and portfolios consisting of assets from OMX Stockholm 30 and use these relationships to perform Tactical Asset Allocation (TAA). The more specific aim of the project is to prove that dynamic modelling techniques outperform static models in portfolio theory. / Den finansiella marknaden är av en väldigt komplex struktur och modelleringsteknikerna har under senare tid blivit allt mer komplicerade. För en portföljförvaltare är det av yttersta vikt att finna mer sofistikerade modelleringstekniker, speciellt efter finanskrisen 2007-2008. Idéen i den här uppsatsen är att finna ett samband mellan makroekonomiska faktorer och aktieportföljer innehållande tillgångar från OMX Stockholm 30 och använda dessa för att utföra Tactial Asset Allocation (TAA). Mer specifikt är målsättningen att visa att dynamiska modelleringstekniker har ett bättre utfall än mer statiska modeller i portföljteori.
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