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In this paper we develop a new form of agent-based model for limit orderbooks based on heterogeneous trading agents, whose motivations are liquiditydriven. These agents are abstractions of real market participants, expressed ina stochastic model framework. We develop an efficient way to performstatistical calibration of the model parameters on Level 2 limit order bookdata from Chi-X, based on a combination of indirect inference andmulti-objective optimisation. We then demonstrate how such an agent-basedmodelling framework can be of use in testing exchange regulations, as well asinforming brokerage decisions and other trading based scenarios.

Stochastic simulation framework for the Limit Order Book using liquidity motivated agents