forecasting performances across most of the forecasting horizons. Moreover, we found that models using the VRP as an additional … forecasting performances were not statistically different for most models, and only the Principal Component Regression (PCR) and … the Partial least squares (PLS) regression were consistently excluded from the set of best forecasting models. These …

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …

Recent contributions highlight the importance of intraday jumps in forecasting realized volatility at horizons up to … data in forecasting the density of returns. Considering both intra-week periodicity and signed jumps, we estimate two … importance of considering the continuous/jump decomposition of volatility for the purpose of density forecasting. Specifically …

theory assumes that return shocks can be caused by changes in conditional volatility through a time-varying risk premium. On …

present value theory. Long-term government bond yields exhibit predictive power over all horizons from one month through five …

based on a structural form representation of the model, but directly shrinkage the lead-lag cross sectional …, both in simulation and when forecasting a large cross section of industry portfolios spanning almost a hundred years of …. This result holds across a variety of alternative shrinkage priors, such as Bayesian adaptive lasso, normal-gamma and …