retailers. Forecasting the demand for cash on a granular level is crucial in the process to keep logistics costs low, while … models to define banknote production for the coming years, our contribution is to combine features of macro level forecasting … forecasting methods on granular level can substantially improve inventory performance for this use-case. To guide the …

the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier … 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 …

volatility. For forecasting, the choice among outlier-robust error structures is less important, however, when a large cross … COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that …