Projections of commodity prices have long been a significant source of dependence for
investors and the government. This study investigates the challenging topic of forecasting …

Purpose Predicting commodity futures trading volumes represents an important matter to
policymakers and a wide spectrum of market participants. The purpose of this study is to …

Investors and authorities have always placed a high emphasis on commodity price
forecasting. In this study, the issue of daily price index forecasting for flat steel products on …

We conducted text mining analyses on nearly the entirety of academic literature related to
food security. Assessing the literature's spatial scope, we found a truly global body of …

Social media data are rapidly evolving and accessible, which presents opportunities for
research. Data science techniques, such as sentiment or emotion analysis which analyse …

For market players and policy officials, commodity price forecasts are crucial problems that
are challenging to address due to the complexity of price time series. Given its strategic …

Price forecasting is a key concern for market participants in the agriculture sector. This study
explores usefulness of the nonlinear autoregressive neural network (NARNN) and NARNN …

Forecasting commodity prices is a vital issue to a wide spectrum of market participants and
policy makers in the metal sector. In this work, the forecast problem is investigated by …

Cash-futures basis forecasting represents a vital concern for various market participants in
the agricultural sector, which has been rarely explored due to limitations on data and …

Projections of commodity prices have long been heavily relied upon by investors and the
government. This study examines the challenging task of estimating the daily regional steel …