Combining provides a pragmatic way of synthesising the information provided by individual
forecasting methods. In the context of forecasting the mean, numerous studies have shown …

We introduce a novel regression framework which simultaneously models the quantile and
the Expected Shortfall (ES) of a response variable given a set of covariates. This regression …

We propose a new method for conducting Bayesian prediction that delivers accurate
predictions without correctly specifying the unknown true data generating process. A prior is …

Recent studies have analyzed whether one forecast method dominates another under a
class of consistent scoring functions. While the existing literature focuses on empirical tests …

Renewable energy forecasts are critical to renewable energy grids and backup plans,
operational plans, and short-term power purchases. This paper focused on short-term …

Consider two forecasters, each making a single prediction for a sequence of events over
time. We ask a relatively basic question: how might we compare these forecasters, either …

Proper scoring rules are used to assess the out-of-sample accuracy of probabilistic
forecasts, with different scoring rules rewarding distinct aspects of forecast performance …

Forecasting VaR and ES using the joint regression combined forecasting model in the
Chinese stock market | Emerald Insight Books and journals Case studies Expert Briefings …

The existing literature provides mixed results on the usefulness of implied volatility for
managing risky assets, while evidence for expected shortfall predictions is almost …

In response to the Subprime mortgage crisis, the Basel Committee on Banking Supervision
(BCBS) has spent the previous decade overhauling the regulatory framework that governs …