Many risk management strategies, including hedging the price risk using forward or futures contracts require accurate forecasts of basis, i.e., spot price minus the futures price. Recent literature in this area has applied nonlinear time-series models, which are refinements of the linear autoregressive models that allow the parameters to transition from one regime to another. These parametric n...

The ability to scientifically forecast the price of aquatic products plays an important role in the healthy and sustainable development of aquaculture. This paper presents a method for forecasting aquatic product prices using Case-Based Reasoning. Some key processes include automatic extraction of web data, attribute-oriented induction based on concept hierarchy, generation and representation o...

In this paper we focus on the development of multiple time series models for forecasting Irish Inflation. The Bayesian approach to the estimation of vector autoregressive (VAR) models is employed. This allows the estimated models combine the evidence in the data with any prior information which may also be available. A large selection of inflation indicators are assessed as potential candidates...