文章基本信息

标题：Dynamic Stock Dependence and Monetary Variables in the United States (2000-2016): A Copula and Neural Network Approach
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作者：Magnolia Miriam Sosa Castro ; Christian Bucio Pacheco ; Edgar Ortiz Calisto 等
期刊名称：Lecturas de Economía
印刷版ISSN：2323-0622
出版年度：2022
期号：96
页码：201-234
DOI：10.17533/udea.le.n96a345321
语种：English
出版社：Universidad de Antioquia
摘要：This paper investigates dynamic dependence between the American Stock Market (S&P 500) and the World Share Market (MSCIW) and examines whether key monetary variables (short and long-term interest rates, interest rate spreads, and exchange rate) explain changes in this relation, during the period January 2000 - June 2016. The methodology includes a Dynamic Copula approach and a Multilayer Perceptron Network. Results suggest that there is interdependence between the American and global stock market and that the dynamic dependence is mainly explained by the short-term interest rate spread, 3-month T-bill's rate and 3-month London Interbank Offered Rate LIBOR rate.