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Automatizing Price Negotiation in Commodities Markets

Author

Listed:
  • Laib, Fodil
  • Radjef, MS

Abstract

This is an introductory work to trade automatization of the futures market, so far operated by human traders. We are not focusing on maximizing individual profits of any trader as done in many studies, but rather we try to build a stable electronic trading system allowing to obtain a fair price, based on supply and demand dynamics, in order to avoid speculative bubbles and crashes. In our setup, producers and consumers release regularly their forecasts of output and consumption respectively. Automated traders will use this information to negotiate price of the underlying commodity. We suggested a set of analytical criteria allowing to measure the efficiency of the automatic trading strategy in respect to market stability.

Suggested Citation

  • Laib, Fodil & Radjef, MS, 2010. "Automatizing Price Negotiation in Commodities Markets," MPRA Paper 28277, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:28277
    as

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    File URL: https://mpra.ub.uni-muenchen.de/28277/1/MPRA_paper_28277.pdf
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    References listed on IDEAS

    as
    1. Michael J. Barclay & Terrence Hendershott & D. Timothy McCormick, 2003. "Competition among Trading Venues: Information and Trading on Electronic Communications Networks," Journal of Finance, American Finance Association, vol. 58(6), pages 2637-2666, December.
    2. Levy, Moshe, 2008. "Stock market crashes as social phase transitions," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 137-155, January.
    3. Laib, Fodil & Radjef, MS, 2008. "Optimal Strategies for Automated Traders in a Producer-Consumer Futures Market," MPRA Paper 12965, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Automated Traders; Optimal Strategies; Futures Market; Commodities Trading;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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