An evolutionary multi-objective optimization of market structures using PBIL
Li, X. and Krause, A., 2010. An evolutionary multi-objective optimization of market structures using PBIL. In: Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings. Springer-Verlag, pp. 78-85. (Lecture Notes in Computer Science; 6283)
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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, 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 (PIBL) algorithm seeking to maximize the trading price and minimize the bid-ask spread. Our results suggest that markets should choose a relatively large tick size unless concerns about either the bid-ask spread or the trading price are dominating. We also find that in contrast to trading rules in actual markets, reverse time priority is an optimal priority rule.
|Item Type||Book Sections|
|Creators||Li, X.and Krause, A.|
|Departments||School of Management|
|Additional Information||11th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2010. 1-3 September 2010. Paisley, UK.|
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