Agent-based modeling of a price information trading business
AbstractWe describe an agent-based simulation of a fictional (but feasible) information trading business. The Gas Price Information Trader (GPIT) buys information about real-time gas prices in a metropolitan area from drivers and resells the information to drivers who need to refuel their vehicles. Our simulation uses real world geographic data, lifestyle-dependent driving patterns and vehicle models to create an agent-based model of the drivers. We use real world statistics of gas price fluctuation to create scenarios of temporal and spatial distribution of gas prices. The price of the information is determined on a case-by-case basis through a simple negotiation model. The trader and the customers are adapting their negotiation strategies based on their historical profits. We are interested in the general properties of the emerging information market: the amount of realizable profit and its distribution between the trader and customers, the business strategies necessary to keep the market operational (such as promotional deals), the price elasticity of demand and the impact of pricing strategies on the profit.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1303.7445.
Date of creation: Mar 2013
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-04-06 (All new papers)
- NEP-CMP-2013-04-06 (Computational Economics)
- NEP-CWA-2013-04-06 (Central & Western Asia)
- NEP-ENE-2013-04-06 (Energy Economics)
- NEP-HME-2013-04-06 (Heterodox Microeconomics)
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- Raberto, Marco & Cincotti, Silvano & Focardi, Sergio M. & Marchesi, Michele, 2001.
"Agent-based simulation of a financial market,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 299(1), pages 319-327.
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