Determining the optimal market structure using near-zero intelligence traders

Xinyang Li, Andreas Krause

Research output: Contribution to journalArticle

1 Citation (Scopus)

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, which orders are executed as well as a range of parameters regarding market intervention by specialists and the presence of informed traders. We optimize these trading rules using a population-based incremental learning algorithm seeking to maximize the trading volume. Our results suggest markets should choose a large tick size and ensure only a small fraction of traders are informed about the order book. The effect of trading rules regarding the determination of prices, priority rules, and specialist intervention, we find to have an ambiguous effect on the outcome.
Original languageEnglish
Pages (from-to)155-167
JournalJournal of Economic Interaction and Coordination
Volume5
Issue number2
DOIs
Publication statusPublished - Dec 2010

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Trading rules
Market structure
Traders
Call markets
Learning algorithm
Priority rules
Incremental
Agent-based model
Trading volume
Informed traders
Order book
Market intervention
Tick size

Cite this

Determining the optimal market structure using near-zero intelligence traders. / Li, Xinyang; Krause, Andreas.

In: Journal of Economic Interaction and Coordination, Vol. 5, No. 2, 12.2010, p. 155-167.

Research output: Contribution to journalArticle

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