Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models

Stock and oil relationship is usually time-varying and depends on the current economic conditions. In this study, we propose a new Dynamic Stochastic Mixed data frequency sampling (DSM) copula model, that decomposes the stock-oil relationship into a short-run dynamic stochastic component and a long-run component, governed by related macro-finance variables. We find that inflation/interest rate, uncertainty and liquidity factors are the main drivers of the long-run co-dependence. We show that investment portfolios, based on the proposed DSM copula model, are more accurate and produce better economic outcomes as compared to other alternatives.