In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate. In particular, we apply in a two-step...

A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the jump component is persistent when forecasting the oil...

Several market and macro-level variables influence the evolution of equity risk in addition to the well-known volatility persistence. However, the impact of those covariates might change depending on the risk level, being different between low and high volatility states. By combining equity risk...