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An equilibrium model for matching impatient demand and patient supply over time

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  • Garud Iyengar
  • Anuj Kumar

Abstract

We present a simple dynamic equilibrium model for an online exchange where both buyers and sellers arrive according to a exogenously defined stochastic process. The structure of this exchange is motivated by the limit order book mechanism used in stock markets. Both buyers and sellers are elastic in the price-quantity space; however, only the sellers are assumed to be patient, i.e. only the sellers have a price - time elasticity, whereas the buyers are assumed to be impatient. Sellers select their selling price as a best response to all the other sellers' strategies. We define and establish the existence of the equilibrium in this model and show how to numerically compute this equilibrium. We also show how to compute other relevant quantities such as the equilibrium expected time to sale and equilibrium expected order density, as well as the expected order density conditioned on current selling price. We derive a closed form for the equilibrium distribution when the demand is price independent. At this equilibrium the selling (limit order) price distribution is power tailed as is empirically observed in order driven financial markets.

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File URL: http://arxiv.org/pdf/cs/0612065
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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number cs/0612065.

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Date of creation: Dec 2006
Date of revision: Mar 2007
Handle: RePEc:arx:papers:cs/0612065

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  1. Severin Borenstein, 2002. "The Trouble With Electricity Markets: Understanding California's Restructuring Disaster," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 191-211, Winter.
  2. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2003. "Limit Order Book as a Market for Liquidity," Discussion Paper Series dp321, The Center for the Study of Rationality, Hebrew University, Jerusalem.
  3. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Science & Finance (CFM) working paper archive 0203511, Science & Finance, Capital Fund Management.
  4. Iori, G. & Daniels, M.G. & Farmer, J.D. & Gillemot, L. & Krishnamurthy, S. & Smith, E., 2003. "An analysis of price impact function in order-driven markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 146-151.
  5. Domowitz, Ian & Wang, Jianxin, 1994. "Auctions as algorithms : Computerized trade execution and price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 29-60, January.
  6. J. Doyne Farmer & Paolo Patelli & Ilija I. Zovko, 2003. "The Predictive Power of Zero Intelligence in Financial Markets," Papers cond-mat/0309233, arXiv.org, revised Feb 2004.
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