Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Copula-based models provide a great deal of flexibility in modeling multivariate
distributions, allowing the researcher to specify the models for the marginal distributions …

Vector autoregressions (VARs) are flexible time series models that can capture complex
dynamic interrelationships among macroeconomic variables. However, their dense …

Expected Shortfall (ES) has been widely accepted as a risk measure that is conceptually
superior to Value-at-Risk (VaR). At the same time, however, it has been criticised for issues …

We propose a framework for out‐of‐sample predictive ability testing and forecast selection
designed for use in the realistic situation in which the forecasting model is possibly …

This article addresses some of the issues that arise with the Dynamic Conditional
Correlation (DCC) model. It is proven that the DCC large system estimator can be …

This paper compares alternative models of time‐varying volatility on the basis of the
accuracy of real‐time point and density forecasts of key macroeconomic time series for the …

We propose a method for comparing density forecasts that is based on weighted versions of
the continuous ranked probability score. The weighting emphasizes regions of interest, such …

Central banks and other forecasters are increasingly interested in various aspects of density
forecasts. However, recent sharp changes in macroeconomic volatility, including the Great …

Volatility has been one of the most active and successful areas of research in time series
econometrics and economic forecasting in recent decades. This chapter provides a selective …