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 …

Since the inception of competitive power markets two decades ago, electricity price
forecasting (EPF) has gradually become a fundamental process for energy companies' …

A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the
last 15 years, with varying degrees of success. This review article aims to explain 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 …

We propose new scoring rules based on conditional and censored likelihood for assessing
the predictive accuracy of competing density forecasts over a specific region of interest, such …

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality.
In this paper, for non-elliptically distributed financial returns, we propose copula-based …

This paper reviews current density forecast evaluation procedures, and considers a
proposal that such procedures be augmented by an assessment of 'sharpness'. This was …

Many finance questions require the predictive distribution of returns. We propose a bivariate
model of returns and realized volatility (RV), and explore which features of that time-series …

The Philippines is one of the many countries that consume and produce wheat grains.
Despite having agricultural resources, the country still struggles to supply wheat and …

This article proposes new dynamic component models of returns and realized covariance
(RCOV) matrices based on time-varying Wishart distributions. Bayesian estimation and …