Since the first multi-agents based market simulations in the nineties, many different artificial stock market models have been developped. There are mainly used to reproduce and understand real markets statistical properties such as fat tails, volatility clustering and positive auto-correlation of absolute returns. Though they share common goals, these market models are most of the time different one from another: some are based on equations, others on complex microstructures, some are synchronous, others are asynchronous. It is hence hard to understand which characteristic of the market model used is at the origin of observed statistical properties. To investigate this question, we propose a generic model of artificial markets architecture which allows to freely compose modules coming from existing market models. To illustrate this formalism, we implement these components to propose a model of an asynchronous double auction based on an order-book and show that many stylized facts of real stock markets are reproduced with our model.
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number
4918.
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