This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

In the academic literature, the economic interpretation of stock market volatility is inherently ambivalent, being considered an indicator of either information flow or uncertainty. We show in a stylized model economy that both views suggest volatility-dependent cross-market spillovers. If...

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

It is common practice to estimate the volatility-growth link by specifying a standard growth equation such that the variance of the error term appears as an explanatory variable in this growth equation. The variance in turn is modelled by a second equation. Hardly any of existing applications of...

This paper examines if overreaction of oil price forecasters is affected by uncertainty. Furthermore, it takes into account joint effects of uncertainty and oil price returns on forecast changes. The panel smooth transition regression model from Gonz alez et al. (2005) is applied with univariate...