Automated traders in commodities markets: Case of producer–consumer institution

Automatizing commodities’ price negotiation was hard to achieve in practice, mainly because of logistical complications. The purpose of our work is to show that it is possible to automatize thoroughly commodities’ trading in the futures market by replacing human traders with artificial agents. As a starting step, we designed a market institution, called producer–consumer, where only an automated seller and an automated buyer can trade on behalf of the producer and consumer, respectively. The producer and consumer periodically feed their trading agents with supply and demand (S&D) forecasts. We suggested a parameterizable trading strategy, called bands and frequencies, for the agents. To measure the overall efficiency of this trading system in terms of price stability and liquidity, we made some hypotheses on the benchmark price curve and its linkages to S&D curves and other relevant market variables. Then we proposed analytical tools to measure strategy performance. Finally, we conducted some computer simulations to prove the workability of this approach.

► Algorithm for automated traders in producer–consumer commodity market. ► Properties of the benchmark price pattern in respect to market stability. ► Mathematical norms measuring distance between benchmark and actual prices. ► Optimal parameters for the ‘bands and frequencies’ automatic trading strategy.