the estimation severely distorts the analysis of the latest economic dynamics. …

This paper proposes a Skewed Stochastic Volatility (SSV) model to model time varying, asymmetric forecast distributions … volatility and asymmetric measurement densities. Estimating the model based on US data yields conditional forecast densities that …

constrained estimation produces a quantitative model with both reasonable asset-pricing as well as business-cycle implications. …

volatility. For forecasting, the choice among outlier-robust error structures is less important, however, when a large cross …

Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed … divergent when volatility clusters idiosyncratically.It is illustrated that this property is important for empirical …

VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine … transitory and persistent changes in volatility. The resulting density forecasts are much less sensitive to outliers in the data … the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier …