Stock market reaction to macroeconomic variables: An assessment with dynamic autoregressive distributed lag simulations

Abstract

AbstractThis research investigates the impact of oil prices, gold prices and exchange rate on Shanghai stock exchange returns. In this study, we used monthly time series data from January 2000 to December 2018. The dynamic autoregressive distributed lag simulations model proposed by Jordan and Philips is used to examine the real change in regressors and their impact on regressand by using graphical representations. The examined results of the dynamic simulated autoregressive distributed lag model indicate that oil prices and gold prices have a positive effect on the stock returns in the short run and in the long run while the exchange rate indicate negative effect both in the short run and in the long run. Our research findings have significant implications for policymakers.