A computational approach to modeling commodity markets

We build an agent based computational framework to study large commodity markets. A detailed representation of the consumers, producers and the market is used to study the micro level behavior of the market and its participants. The user can control players' preferences, their strategies, assumptions of the model, its initial conditions, market elements and trading mechanisms. The first part of the paper describes the computational framework and its three main modules. The later part describes a case study that examines the decentralized market in detail, specifically the computational options available for matching the buyers and suppliers in a synthetic market. The study illustrates the sensitivity of the outcome of various economic variables, such as clearing price, quantity, profits and social welfare, to different matching schemes in a bilateral computational setting. Based on seven different matching orders for the buyers and suppliers, our study shows that the results can vary dramatically for different pairing orders. © Springer Science+Business Media, LLC 2007.