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 …

stochastic volatility of asset prices and to give theoretical arguments for empirically well documented facts. We show that … stochastic volatility. …

volatility. Hence, they are viable alternatives to the geometric Brownian motion. …