Up: 1:2

Inventory-based versus Prior-based Options Trading Agents

Abraham Othman; Tuomas Sandholm

Algorithmic Finance (2012), 1:2, 95-121
DOI: 10.3233/AF-2011-009

Published: Abstract, PDF, HTML.
Archived: SSRN.

Abstract

Options are a basic, widely-traded form of financial derivative that offer payouts based on the future price of an underlying asset. The finance literature gives us option-trading algorithms that take into consideration information about how prices move over time but do not explicitly involve the trades the agent made in the past. In contrast, the prediction market literature gives us automated market-making agents (like the popular LMSR) that are event-independent and price trades based only on the inventories the agent holds. We simulate the performance of five trading agents inspired by these literatures on a large database of recent historical option prices. We find that a combination of the two approaches produced the best results in our experiments: a trading agent that keeps track of previously-made trades combined with a good prior distribution on how prices move over time. The experimental success of this synthesized trader has implications for agent design in both financial and prediction markets.

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NYU School of Engineering

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Kent State University

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Stanford University

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AT&T Labs Research

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Boston University

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Stanford University

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Massachusetts Institute of Technology

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University of Chicago

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Wolfram Research

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California Institute of Technology

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Columbia University

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Northwestern University

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Lawrence Berkeley National Laboratory

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Georgia Tech

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Yale University

Robert Webb

University of Virginia

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Giovanni Barone-Adesi

University of Lugano

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University of California, San Diego

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