Title: Oil prices and U.S. stock market dependence: A mixed-frequency data sampling copula approach
Authors: Ruijun Bu - University of Liverpool (United Kingdom) [presenting]
Abstract: The relationship between oil prices and stocks is an important issue for portfolio selection and risk management. Understanding the economic factors affecting the interaction between oil prices and stocks allows investors to improve their portfolio performance. A mixed frequency data sampling copula model with explanatory variables (Copula-MIDAS-X) is proposed that incorporates low frequency explanatory variables into a high frequency dynamic copula model. The new model enables us to investigate the impacts of economic factors on the relationship between oil and stock returns. In an application to Brent oil prices and S\&P 500 indices, we find that the dependence of oil and stock markets is influenced by aggregate demand and stock specific negative news. The impact of aggregate demand lasts for two years, while the impact of stock specific bad news lasts for one quarter. The implication for market regulators and investors is that changes in aggregate demand have influential and long-lasting effects on both oil prices and stock markets. Besides, investors who re-balance portfolios daily or weekly should use the information on both monthly economic indicators and daily returns in portfolio management.