Presents an application of an expert system in the commodities market. The system is designed to facilitate decision making with regard to when to buy and sell. This system has several attractive features which make it very appealing to users without much computer background. Executives of large...

This study examines the temporal causal relationships in the stock price returns of eight U.S. lumber supply chain-related stocks and four economic and financial instruments over a 15-year period using daily closing stock prices. A prediction vector (PV) model that is based on Granger causality...

In this study, we apply several advanced machine learning techniques including extreme gradient boosting (XGBoost), support vector machine (SVM), and a deep neural network to predict bankruptcy using easily obtainable financial data of 3728 Belgian Small and Medium Enterprises (SME's) during the...

Purpose: The purpose of this paper is to examine the impact of oil price shocks on capital spending in relation to the following firm characteristics: firm size, debt ratio, growth prospects, earnings and key sectors of the oil and gas industry. Design/methodology/approach: To examine the...