Previsibilidade da taxa de câmbio com sentimento das notícias

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Lima, Lucas-Matheus Souza de Araújo
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal da Paraíba
Brasil
Economia
Programa de Pós-Graduação em Economia
UFPB
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/22070
Resumo: This paper aims to study the out-of-sample predictability of nominal exchange rate variations with news sentiment, we use financial news from The New York Times and The Wall Street Journal to construct these sentiments for the period from january 1980 to may 2017. The results suggest a strong predictive power of the news sentiment generated with the time variant dictionary, which can be used as the only predictor or as an additional predictor to the model based on the conventional Taylor rule. Besides demonstrating that the time-varying dictionary method is more suitable for large textual samples compared to fixed dictionaries when the objective of the work passes through predictive power. When used as the only predictor, superiority of performance was observed in the prediction on random walk for all analyzed countries and on the conventional Taylor rule for 7 of 9 countries. For extended Taylor rule models with news sentiment, superior performance was observed for all countries in relation to the conventional Taylor rule models. All of these results at 1% significance.