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TSANG, EDWARD and MARKOSE, SHERI and HAKAN, ER (2005) 'CHANCE DISCOVERY IN STOCK INDEX OPTION AND FUTURES ARBITRAGE.' New Mathematics and Natural Computation, 01 (03). pp. 435-447.

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The prices of the option and futures of a stock both reflect the market's expectation of futures changes of the stock's price. Their prices normally align with each other within a limited window. When they do not, arbitrage opportunities arise: an investor who spots the misalignment will be able to buy (sell) options on the one hand, and sell (buy) futures on the other and make risk-free profits. Historical data suggest that option and futures prices on the LIFFE Market do not align occasionally. Arbitrage chances are rare. Besides, they last for seconds only before the market adjusts itself. The challenge is not only to discover such chances, but to discover them ahead of other arbitragers. In the past, we have introduced EDDIE as a genetic programming tool for forecasting. This paper describes EDDIE-ARB, a specialization of EDDIE, for forecasting arbitrage opportunities. As a tool, EDDIE-ARB was designed to enable economists and computer scientists to work together to identify relevant independent variables. Trained on historical data, EDDIE-ARB was capable of discovering rules with high precision. Tested on out-of-sample data, EDDIE-ARB out-performed a naive ex ante rule, which reacted only when misalignments were detected. This establishes EDDIE-ARB as a promising tool for arbitrage chances discovery. It also demonstrates how EDDIE brings domain experts and computer scientists together.

Item Type: Article
Uncontrolled Keywords: Chance discovery; stock index futures and options arbitrage; EDDIE-ARB
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Science and Health
Faculty of Social Sciences
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Faculty of Social Sciences > Economics, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 16 Aug 2012 13:54
Last Modified: 23 Sep 2022 19:02

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