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Optimal Strategies for Automated Traders in a Producer-Consumer Futures Market

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  • Laib, Fodil
  • Radjef, MS

Abstract

The aim of this work is to show how automated traders can operate a futures market. First, we established some hypothesises on the properties of the ’correct’ price pattern which translates accurately the underlying moves in the supply/demand balance and the nominal price, then mathematical measures were derived allowing to estimate the efficiency of a given trading strategy. As a starting step, we applied our approach to a simplified market setup where only two automated traders, a producer and a consumer, can trade. They receive a stream of forecasts on supply and demand levels and they should react instantaneously by adjusting these forecasts, then issuing sale and buy orders. Later, we suggested a parameterized trading strategy for the two automatons. Finally, we obtained by simulation the optimal parameters of this strategy in some particular cases.

Suggested Citation

  • Laib, Fodil & Radjef, MS, 2008. "Optimal Strategies for Automated Traders in a Producer-Consumer Futures Market," MPRA Paper 12965, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:12965
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    File URL: https://mpra.ub.uni-muenchen.de/12965/1/MPRA_paper_12965.pdf
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    References listed on IDEAS

    as
    1. Brock, W. A., 1986. "Distinguishing random and deterministic systems: Abridged version," Journal of Economic Theory, Elsevier, vol. 40(1), pages 168-195, October.
    2. Granovetter, Mark & Soong, Roland, 1986. "Threshold models of interpersonal effects in consumer demand," Journal of Economic Behavior & Organization, Elsevier, vol. 7(1), pages 83-99, March.
    3. Dalrymple, Douglas J., 1987. "Sales forecasting practices: Results from a United States survey," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 379-391.
    4. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    5. J. S. Armstrong & R. Brodie, 2005. "Forecasting for Marketing," General Economics and Teaching 0502018, EconWPA.
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    Cited by:

    1. Laib, Fodil & Radjef, MS, 2010. "Automatizing Price Negotiation in Commodities Markets," MPRA Paper 28277, University Library of Munich, Germany.

    More about this item

    Keywords

    Automated traders; optimal strategies; agent based;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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