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 …

The uncertainty of U.S. core inflation, measured by the stochastic volatility of forecast errors, has soared to a level …

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 …

-time data flow as well as parameter uncertainty and time-varying volatility. In addition, we develop a fast estimation algorithm …

We use volatility impulse response analysis estimated from the bivariate GARCH-BEKK model to quantify the size and the … persistence of different types of oil price shocks on stock return volatility and the covariance between oil price changes and …

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