An analysis of long horizon exchange rate predictability

• Autor(a) principal: Santos, Patrícia Vicente Lopes Da Silva
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/105633
• topic: Predictability; Exchange rates; Quantile regression; Domínio/Área Científica::Ciências Sociais::Economia e Gestão

Exchange rate predictability in long-horizons has turned into a debatable topic. Many were the ones achieving evidence of higher predictive power by economic models as larger periods were considered, while others argued against this premise. The main problem resides in the data properties that the regressors used exhibit, more specifically, overlapping observations, high ly persistent regressors, and endogeneity, which affect the statistical inference. Consequently, if the biases are wrongfully corrected, invalid conclusions will be reached. Bearing this in mind, this analysis applies suitable tests aimed at overcoming these issues, after which it is in ferred that mean-based regressions present weak statistical evidence on larger predictability in longer horizons. Lastly, a quantile regression is implemented, contemplating all potential biases. This innovative procedure finally provides results favoring long-horizon predictability.