The empirical literature is very far from any consensus about the appropriate model for oil price forecasting that … frequencies on a common sample and common data. Fourth, we evaluate the forecasting performance of each selected model using …

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the … forecasting performance of our proposed model relative to most of the existing alternative specifications. While most of the … and useful for forecasting. …

that asymmetries show up in their unconditional distribution, as well as in their unconditional copula. The VaR forecasting …

, their local-factor SVF model is not powerful enough in forecasting Asian volatility. This has led us to propose an extension …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …

uncertainty in the data. We apply the method to UK aggregate expenditure data, and illustrate the gains in forecasting from …

In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by … weights. We consider the use of model averaging in forecasting UK inflation with a large dataset from this perspective. We …

Recently, there has been increasing interest in forecasting methods that utilise large datasets. We explore the … possibility of forecasting with model averaging using the out-of-sample forecasting performance of various models in a frequentist … setting, using the predictive likelihood. We apply our method to forecasting UK inflation and find that the new method …