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Calibration based on entropy minimization for a class of asset pricing models |
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| Affiliation: | 1. Department of Automobile Engineering, Noorul Islam Centre for Higher Education, Nagercoil 629180, Tamil Nadu, India;2. Department of Production Engineering, National Institute of Technology, Tiruchirappalli 620 015, Tamil Nadu, India;1. Department of Chemical Engineering, Texas A&M University at Qatar, Doha, Qatar;2. Department of Environmental Science, Aarhus University, Roskilde, Denmark;3. Department of Chemical Engineering, Biotechnology and Environmental Technology, University of Southern Denmark, Odense, Denmark;1. Department of Mathematics, Payame Noor University, PO BOX 19395-3697, Tehran, Iran;2. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran |
| Abstract: | We consider the problem of calibrating pricing models based on the binomial tree method to market data in a network of auctions where agents are supposed to maximize a given utility function. The calibration is carried out using the minimum entropy principle to find a probability distribution that minimizes a weighted misfit between predicted and observed data. Numerical results from calibrating the mid prices from the bid–ask pairs of the buyer and seller to Taobao data demonstrated the feasibility of this approach in the case of pricing goods in a sequential auction. Further numerical test cases have been presented and have shown promising results. This work can equip those engaged in electronic trading with computational tools to improve their decision-making process in an uncertain environment. |
| Keywords: | Sequential auctions Binomial tree Pricing algorithms Entropy minimization Model calibration |
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