Atenção do investidor e o comportamento dos mercados acionários

• Ano de defesa: 2023
• Autor(a) principal: Marschner, Paulo Fernando
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Administração; UFSM; Programa de Pós-Graduação em Administração; Centro de Ciências Sociais e Humanas
• Palavras-chave em Português: Atenção do investidor; Mercado de capitais; Eficiência informacional; Investor attention; Stock market; Informational efficiency; CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/28795

The close connection between information and the price of an asset has long been discussed in the financial literature. In order for information to be incorporated into the asset price, investors must pay sufficient attention to the market. However, individuals have scarce cognitive abilities, and since there is a large amount of information, they tend to be selective and pay limited attention to their choices. So, investor attention should play an important role in capital markets. This relationship is potentially affected by the economic, cultural and regulatory characteristics of the markets, and by the existing informational advantages between local and non-local investors. Given this context, the objective of this research is to detect and measure how the attention of investors, with different levels of informational advantage (local and nonlocal), impacts return, volatility and trading volume, in capital markets of countries emerging and developed. To this end, closing price and volume data were collected from the main stock exchange indices for ten developed markets (Germany, Canada, Spain, United States, France, Holland, Italy, Japan, United Kingdom and Switzerland) and ten emerging markets. (South Africa, Brazil, China, India, Indonesia, Malaysia, Mexico, Pakistan, Russia and Turkey). To construct measures of local and non-local investor attention, Google Trends search volume was used, which tracks the volume of queries for each term/word during a given period of time and geographic location. The collection period was from January 2017 to December 2021 for the main models, and from January 2015 to December 2019 for the robustness tests. Based on these data, the characteristics of each variable were examined and a Panel vector autoregression model was used in six panels. From these, causal relationships and temporal precedence were estimated, impulse response functions and variance decompositions were generated to determine the impact of investor attention on return, volatility and trading volume. The empirical evidence found converges with the investor recognition hypothesis and indicated that local and foreign attention measures significantly affected return, volatility and abnormal trading volume. As far as market development is concerned, it has been found that stock exchanges in developed markets are more responsive to attention than those in emerging markets. The results also showed that it is not possible to attribute an informational advantage to local investors in relation to non-local ones.