Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arciniegas I., Barrett C., Marathe A. (2003). Assessing the efficiency of US electricity markets. Utilities Policy 11(2): 75–86
Arciniegas I., Marathe A. (2005). Important variables in explaining real-time peak price in the independent power market of ontario. Utilities Policy 3(1): 27–39
Atkins, K., Barrett, C., Homan, C., Marathe, A., Marathe, M., & Thite, S. (2004a). Marketecture: A simulation-based framework for studying experimental deregulated power markets. Los Alamos Technical Report, LAUR 04-2032.
Atkins, K., Barrett, C., Homan, C., Marathe, A., Marathe, M., & S. Thite. (2004b). Agent based economic analysis of deregulated electricity markets. 6th IAEE European Conference, Zurich, Switzerland.
Atkins, K., Homan, C., & Marathe, A. (2004c). Physical clearing mechanisms in power industry. To be presented at the IEEE Power Systems Conference and Exposition, New York City, New York.
Barrett, C. L., Beckman, R. J., Berkbigler, K . P., Bisset, K. R., Bush, B. W., Eubank, S., Hurford, J. M., Konjevod, G., Kubicek, D. A., Marathe, M. V., Morgeson, J. D., Rickert, M., Romero, P. R., Smith, L. L., Speckman, M. P., Speckman, P. L., Stretz, P. E., Thayer, G. L., & Williams, M. D. (1999) TRANSIMS (TRansportation ANalysis SIMulation System):, Overview, LA-UR-99-1658, Los Alamos National Laboratory.
Barrett C., Cook D., Faber V., Hicks G., Marathe A., Marathe M., Srinivasan A., Sussmann Y.J., Thornquist H. (2003). Experimental analysis of algorithms for bilateral-contract clearing mechanisms arising in deregulated power industry. Journal of Graph Algorithms and Applications 7(1): 3–31
Bogomolnaia A., Moulin H. (2004). Random matching and assignment under dichotomous preferences. Econometrica 72(1): 257–279
Bunn D., Oliveira F.S. (2001). Agent-based simulation - an application to the new electricity trading arrangements of England and Wales. IEEE Transactions on Evolutionary Computation 5(5): 493–503
Falk A., Fehr E. (2003). Why labour market experiments?. Labour Economics 10: 399–406
Huberman B.A., Glance N.S. (1993). Evolutionary games and computer simulations. Proceedings of National Academy Science 90: 7716–7718
Huberman, B.A., Hogg, T. (1995). Distributed computation as an economic system. Journal of Economic Perspectives, 141–152
Judd, K. (2005) Computationally intensive analysis in economics. Handbook of computational economics, (Vol. 2). North Amsterdam.
Klaus B., Klijn F. (2006). Procedurally fair and stable matching. Economic Theory 27(2): 431–447
Lin, M. W. (1998). A Model and simulation of competitive electric power systems, Ph.D Dissertation, The University of Texas at Austin. www.ece.utexas.edu/baldick/papers/compmodel.pdf
Li C., Giampapa J.A., Sycara K. (2006). Bilateral negotiation decisions with uncertain dynamic outside options. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Special Issue on Game-theoretic Analysis and Stochastic Simulation of Negotiation Agents 36(1): 31–44
MacKie-Mason, J. J., & Wellman, M. (2005). Automated markets and trading agents. Handbook of computational economics, (Vol. 2). North-Holland.
Miller M.S., Drexler K.E. (1988). Comparative ecology: a computational perspective. In Huberman B. (eds) The Ecology of Computation. Amsterdam, Elsevier Science Publishers
Mozumder P, Marathe A. (2004). Implications of an integrated market for tradable renewable energy contracts. Ecological Economics 49(3): 259–272
Ramey, G., & Watson, J. (2001). Bilateral trade and opportunism in a matching market. Contributions to Theoretical Economics, 1(1), Article 3.
Roth A. E. (1999). Game theory as a tool for market design. http://kuznets.fas.harvard.edu/aroth/alroth.html#vshort
Roth A. E. (2005). Matching and allocation in medicine and health care. Building a better delivery system: A new engineering/health care partnership, National Academy of Engineering and Institute of Medicine, National Academies Press, pp. 237–239.
Roth A.E., Vande V., John H. (1990). Random paths to stability in two-sided matching. Econometrica 58(6): 1475–1480
Rust J., Miller J.H., Palmer R. (1994). Characterizing effective trading strategies: Insights from a computerized double auction tournament. Journal of Economic Dynamics and Control 18: 61–96
Sargent T.J. (1993). Bounded rationality in macroeconomics. The Arne Ryde memorial lectures. Oxford U.K., Clarendon Press
Smith V.L. (1962). An experimental study of competitive market behavior. The Journal of Political Economy 70(2): 111–137
Spulber D.F. (2002). Market microstructure and incentives to invest. Journal of Political Economy 110(2): 352–381
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Atkins, K., Marathe, A. & Barrett, C. A computational approach to modeling commodity markets. Comput Econ 30, 125–142 (2007). https://doi.org/10.1007/s10614-007-9090-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10614-007-9090-6