An evolutionary multi-objective optimization of the market structure in call markets
نویسندگان
چکیده
We evaluate an agent-based model featuring nearzero-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 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 in contrast to trading rules in actual markets reverse time priority is an optimal priority rule.
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