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Num contexto de integração dos mercados, esta investigação analisa a relação entre o desempenho económico futuro, medido pela taxa de crescimento do Produto Interno Bruto (PIB) e os cinco fatores de risco do modelo de avaliação de ativos de Fama e French (2015), isto é, fator risco de mercado (MKT), dimensão (SMB), índice book-to-market (HML), lucro operacional (RMW) e investimento (CMA). A análise é conduzida para 47 países classificados como países desenvolvidos e emergentes e agrupados em diferentes regiões (América do Norte, Ásia Pacífico e Europa) para o período de janeiro de 1992 a dezembro de 2018. As metodologias usadas compreendem: (i) a regressão linear simples e múltipla por mínimos quadrados ordinários, (ii) a regressão quantílica que permite caraterizar toda a distribuição condicional da variável PIB, com base nos fatores de risco e, (iii) a técnica de regressão hierárquica de dois níveis (multinível) com medidas repetidas para investigar as diferenças em termos da taxa de crescimento do PIB ao longo do tempo bem como entre os países. Os resultados obtidos a partir da análise univariada permitiram constatar a existência de uma média anual positiva da taxa de crescimento do PIB em todos os países e regiões. De igual modo, os fatores de risco quando calculados individualmente para os diferentes mercados/regiões apresentaram rendibilidades médias positiva. A decomposição do fator de risco dimensão (SMB), em três fatores elementares formados a partir de carteiras diversificadas de ações compostas por dimensão e book-to-market (SMBB/M), dimensão e lucro operacional (SMBOP) e dimensão e investimento (SMBNIV) permitiu identificar o desempenho médio individual, o qual foi positivo para todos os mercados, exceto a rendibilidade do fator de risco SMBB/M calculado para o mercado da Ásia Pacífico. Os resultados obtidos com base na estimação dos modelos de regressão quantílica indicam que os fatores de risco individual ou associados entre si apresentam uma capacidade preditiva do desempenho económico futuro. Porém, o fator de risco SMBINV calculado para os mercados regionais apresenta maior capacidade preditiva do desempenho económico futuro do que o fator de risco CMA construídos com as mesmas carteiras de ações, o que poderá ser justificado pela predominância de empresas de pequena dimensão.
Considerando a estimação de modelos multinível, os resultados indicam que existe variabilidade significativa no desempenho económico ao longo do tempo, e entre países, apresentando o desempenho económico uma tendência linear de efeitos aleatórios de interceptos. A decomposição de variância do desempenho económico dos 22 países de mercados desenvolvidos a partir de um modelo nulo indica que 18,8% da variabilidade total do desempenho económico é devida à existência de diferenças de desempenho económico entre países. Os fatores de risco MKT, SMB, HML e CMA calculados para os mercados regionais (América do Norte, Ásia Pacífico e Europa) ajudam a prever 22,91% da variabilidade total do desempenho económico futuro. Já os fatores de risco MKT, HML e RMW calculados para o mercado de ações global desenvolvido (América do Norte, Ásia Pacífico e Europa) ajudam a prever 24,19% da variabilidade total do desempenho económico futuro.
A decomposição de variância do desempenho económico dos 47 países desenvolvidos e emergentes sustenta que 26,05% da variabilidade total do desempenho económico é devida à existência de diferenças no desempenho económico entre países. Os fatores de risco MKT e RMW calculados para os mercados de ações globais (desenvolvido e emergente) ajudam a prever 28,84% da variabilidade total do desempenho económico futuro.
In a context of market integration, this research analyzes the relationship between future economic performance, measured by the Gross Domestic Product (GDP) growth rate and the five risk factors of the asset pricing model by Fama and French (2015) , i.e., market (MKT), size (SMB), book-to-market ratio (HML), operating profitability (RMW) and investment (CMA). The analysis is conducted for 47 countries classified as developed and emerging countries and grouped in different regions (North America, Asia Pacific and Europe) for the period from January 1992 to December 2018. The methodologies used comprise (i) simple and multiple linear regression, (ii) quantile regression that allows characterizing the entire conditional distribution of the GDP variable, based on risk factors, and (iii) the two-level hierarchical regression technique (multilevel) with repeated measures to investigate differences in terms of GDP growth rate over time as well as between countries. The results obtained from the univariate analysis showed the existence of a positive annual average of the GDP growth rate in all countries and regions. Likewise, the risk factors when calculated individually for the different markets/regions showed positive premiums. The decomposition of the size risk factor (SMB), in three elementary factors formed from diversified portfolios of stocks composed by size and book-to-market (SMBB/M), size and operating profitability (SMBOP) and size and investment (SMBNIV) allowed identifying the individual average performance, which was positive for all markets, except the profitability of the risk factor SMBB/M calculated for the Asia Pacific market. The results obtained based on the estimation of quantile regression models indicate that individual or associated risk factors present predictive capacity of future economic performance. However, the risk factor SMBINV calculated for regional markets present predictive capacity of future economic performance than the risk factor CMA constructed with the same stock portfolios. Considering the multilevel modeling, the results indicate that there is significant variability in economic performance over time and between countries, with economic performance showing a linear trend of random intercept effects. The decomposition of variance in the economic performance of the 22 developed market countries, 18.8% of the total variability of economic performance is due to the existence of differences in economic performance between countries. The risk factors MKT, SMB, HML and CMA calculated for the regional markets (North America, Asia Pacific and Europe) help predict 22.91% of the total variability of future economic performance. The risk factors MKT, HML and RMW calculated for the developed global stock market (North America, Asia Pacific and Europe) help to predict 24.19% of the total variability of future economic performance. The decomposition of variance in the economic performance of the 47 developed and emerging countries, the results support that 26.05% of the total variability of economic performance is due to the existence of differences in economic performance between countries. The MKT and RMW risk factors calculated for global stock markets (developed and emerging) help to predict 28.84% of the total variability of future economic performance.
In a context of market integration, this research analyzes the relationship between future economic performance, measured by the Gross Domestic Product (GDP) growth rate and the five risk factors of the asset pricing model by Fama and French (2015) , i.e., market (MKT), size (SMB), book-to-market ratio (HML), operating profitability (RMW) and investment (CMA). The analysis is conducted for 47 countries classified as developed and emerging countries and grouped in different regions (North America, Asia Pacific and Europe) for the period from January 1992 to December 2018. The methodologies used comprise (i) simple and multiple linear regression, (ii) quantile regression that allows characterizing the entire conditional distribution of the GDP variable, based on risk factors, and (iii) the two-level hierarchical regression technique (multilevel) with repeated measures to investigate differences in terms of GDP growth rate over time as well as between countries. The results obtained from the univariate analysis showed the existence of a positive annual average of the GDP growth rate in all countries and regions. Likewise, the risk factors when calculated individually for the different markets/regions showed positive premiums. The decomposition of the size risk factor (SMB), in three elementary factors formed from diversified portfolios of stocks composed by size and book-to-market (SMBB/M), size and operating profitability (SMBOP) and size and investment (SMBNIV) allowed identifying the individual average performance, which was positive for all markets, except the profitability of the risk factor SMBB/M calculated for the Asia Pacific market. The results obtained based on the estimation of quantile regression models indicate that individual or associated risk factors present predictive capacity of future economic performance. However, the risk factor SMBINV calculated for regional markets present predictive capacity of future economic performance than the risk factor CMA constructed with the same stock portfolios. Considering the multilevel modeling, the results indicate that there is significant variability in economic performance over time and between countries, with economic performance showing a linear trend of random intercept effects. The decomposition of variance in the economic performance of the 22 developed market countries, 18.8% of the total variability of economic performance is due to the existence of differences in economic performance between countries. The risk factors MKT, SMB, HML and CMA calculated for the regional markets (North America, Asia Pacific and Europe) help predict 22.91% of the total variability of future economic performance. The risk factors MKT, HML and RMW calculated for the developed global stock market (North America, Asia Pacific and Europe) help to predict 24.19% of the total variability of future economic performance. The decomposition of variance in the economic performance of the 47 developed and emerging countries, the results support that 26.05% of the total variability of economic performance is due to the existence of differences in economic performance between countries. The MKT and RMW risk factors calculated for global stock markets (developed and emerging) help to predict 28.84% of the total variability of future economic performance.
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Keywords
Mercados de ações desenvolvidos e emergentes Crescimento económico Modelo de 5 fatores de Fama e French