Forecasting the Realized Volatility of Stock Markets: The Roles of Jumps and Asymmetric Spillovers

Abstract

This paper evaluates the roles of jump and sign-asymmetry spillovers in forecasting the realized volatility in a large sample of 20 stock markets. We compare for the first time whether controlling for either the jumps or asymmetric spillovers into the heterogeneous autoregressive–realized volatility (HAR-RV) model improves the forecasts over 1, 5 and 22 days. Before doing so, the spillovers predictors are generated. In analyzing the spillover process, we find that the US stock market remains the main net transmitter of shocks, and while China is relatively detached from the spillover linkages, such effects may be transmitted through Hong Kong, which is a significant receiver of shocks. The out-of-sample results reveal that the incorporation of jump spillovers improves forecast performance the most across a range of measures. This is more clearly demonstrated at the 22-day forecasting horizon more notably in Europe, France, Germany, India, and the United Kingdom. Lastly, irrespective of the forecasting horizon, performing the predicting stability test uncovers significant improvements in the jump spillover–based model during periods of notable market stress such as the 2014–2016 oil price crash and COVID-19. Overall, results suggest paying more attention to jump spillover while constructing international portfolios based on the realized volatility.