Pricing options with portfolio-holding trading agents in direct double auction

Sarvar Abdullaev, Peter McBurney, Katarzyna Musial

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Options constitute integral part of modern financial trades, and are priced according to the risk associated with buying or selling certain asset in future. Financial literature mostly concentrates on risk-neutral methods of pricing options such as Black-Scholes model. However, it is an emerging field in option pricing theory to use trading agents with utility functions to determine the option's potential payoff for the agent. In this paper, we use one of such methodologies developed by Othman and Sandholm to design portfolio-holding agents that are endowed with popular option portfolios such as bullish spread, butterfly spread, straddle, etc to price options. Agents use their portfolios to evaluate how buying or selling certain option would change their current payoff structure, and form their orders based on this information. We also simulate these agents in a multi-unit direct double auction. The emerging prices are compared to risk-neutral prices under different market conditions. Through an appropriate endowment of option portfolios to agents, we can also mimic market conditions where the population of agents are bearish, bullish, neutral or non-neutral in their beliefs.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Pages1754-1755
Number of pages2
Volume285
ISBN (Print)9781614996712
DOIs
Publication statusPublished - 2016
Event22nd European Conference on Artificial Intelligence, ECAI 2016 - The Hague, Netherlands
Duration: 29 Aug 20162 Sept 2016

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume285
ISSN (Print)09226389

Conference

Conference22nd European Conference on Artificial Intelligence, ECAI 2016
Country/TerritoryNetherlands
CityThe Hague
Period29/08/20162/09/2016

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