IDEAS home Printed from https://ideas.repec.org/p/sce/scecfa/240.html
   My bibliography  Save this paper

A Computational Approach to Modeling Commodity Markets

Author

Listed:
  • Karla Atkins

    (Virginia Tech)

  • Achla Marathe

    (Virginia Tech)

  • Chris Barrett

    (Virginia Tech)

Abstract

We apply agent based computer techniques to develop a modeling framework that can be used to study all aspects of commodity markets. The goal is to use advances in computation to study the micro level behavior of the market and its players. This work is motivated by the understanding that the non-equilibrium dynamics of the transitioning markets can best be analyzed through an experimental framework. The experimental framework makes it possible to observe not only the equilibrium but also the disequilibrium and transition to the equilibrium. The transient dynamics that lead to the equilibrium can sometimes provide the most insightful observations and result in innovative discoveries and explanations. Such transients cannot be studied through traditional closed form economic models. Our framework provides users the ability to control individuals' preferences, behavior, market elements, initial conditions, trading mechanisms along with various other parameters. This facilitates the study of different economic structures, institutions, policies and strategies in isolation. A detailed representation of the consumers, producers and the market is used to study the micro level behavior of the market and its participants. We first describe the computational framework and its main modules. The later part describes a case study that examines the decentralized market in detail; specifically the 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, social welfare, to different schemes for matching buyers and suppliers in a computational setting. Our results, based on seven different matching orders show that the results can vary dramatically for different pairing orders. This variation is found to be even higher for markets with a larger number of participants. This result has important implications for computational modeling based analysis. The user needs to be cognizant of the sensitivity of the ordering scheme and hence should use statistical methods for ensuring the robustness of the results.

Suggested Citation

  • Karla Atkins & Achla Marathe & Chris Barrett, 2006. "A Computational Approach to Modeling Commodity Markets," Computing in Economics and Finance 2006 240, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:240
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bettina Klaus & Flip Klijn, 2006. "Procedurally fair and stable matching," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), pages 431-447.
    2. Mozumder, Pallab & Marathe, Achla, 2004. "Gains from an integrated market for tradable renewable energy credits," Ecological Economics, Elsevier, vol. 49(3), pages 259-272, July.
    3. Roth, Alvin E. & Sotomayor, Marilda, 1992. "Two-sided matching," Handbook of Game Theory with Economic Applications,in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 1, chapter 16, pages 485-541 Elsevier.
    4. Arciniegas, Ismael & Barrett, Chris & Marathe, Achla, 2003. "Assessing the efficiency of US electricity markets," Utilities Policy, Elsevier, vol. 11(2), pages 75-86, June.
    5. Daniel F. Spulber, 2002. "Market Microstructure and Incentives to Invest," Journal of Political Economy, University of Chicago Press, vol. 110(2), pages 352-381, April.
    6. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 111-111.
    7. Moulin Hervé & Anna Bogomolnaia, 2001. "Random Matching and assignment under dichotomous preferences," Economics Bulletin, AccessEcon, vol. 28(19), pages 1.
    8. Falk, Armin & Fehr, Ernst, 2003. "Why labour market experiments?," Labour Economics, Elsevier, vol. 10(4), pages 399-406, August.
    9. MacKie-Mason, Jeffrey K. & Wellman, Michael P., 2006. "Automated Markets and Trading Agents," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 28, pages 1381-1431 Elsevier.
    10. Bernardo A. Huberman & Tad Hogg, 1995. "Distributed Computation as an Economic System," Journal of Economic Perspectives, American Economic Association, vol. 9(1), pages 141-152, Winter.
    11. Ramey Garey & Watson Joel, 2001. "Bilateral Trade and Opportunism in a Matching Market," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 1(1), pages 1-35, November.
    12. Rust, John & Miller, John H. & Palmer, Richard, 1994. "Characterizing effective trading strategies : Insights from a computerized double auction tournament," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 61-96, January.
    13. Arciniegas Rueda, Ismael E. & Marathe, Achla, 2005. "Important variables in explaining real-time peak price in the independent power market of Ontario," Utilities Policy, Elsevier, vol. 13(1), pages 27-39, March.
    14. Roth, Alvin E & Vande Vate, John H, 1990. "Random Paths to Stability in Two-Sided Matching," Econometrica, Econometric Society, vol. 58(6), pages 1475-1480, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dufresne, Daniel & Vázquez-Abad, Felisa, 2012. "Cobweb theorems with production lags and price forecasting," Economics Discussion Papers 2012-17, Kiel Institute for the World Economy (IfW).
    2. Gabriel Galand, 2009. "The Neutrality of Money Revisited with a Bottom-Up Approach: Decentralisation, Limited Information and Bounded Rationality," Computational Economics, Springer;Society for Computational Economics, vol. 33(4), pages 337-360, May.

    More about this item

    Keywords

    Computational Markets; Decentralized; Matching Orders;

    JEL classification:

    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sce:scecfa:240. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/sceeeea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.