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An evolutionary multi‐objective optimization of trading rules in call markets

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  • Xinyang Li
  • Andreas Krause

Abstract

We evaluate an agent‐based model featuring near‐zero‐intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices and which orders are executed, as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. We optimize these trading rules using a multi‐objective population‐based incremental learning algorithm seeking to maximize the trading volume and minimize the bid–ask spread. Our results suggest that markets should choose a small tick size if concerns about the bid–ask spread are dominating and a large tick size if maximizing trading volume is the main aim. We also find that unless concerns about trading volume dominate, time priority is the optimal priority rule. Copyright © 2011 John Wiley & Sons, Ltd.

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  • Xinyang Li & Andreas Krause, 2011. "An evolutionary multi‐objective optimization of trading rules in call markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(1), pages 1-14, January.
    • Handle: RePEc:wly:isacfm:v:18:y:2011:i:1:p:1-14
    DOI: 10.1002/isaf.320
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