In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The model follows a "zero intelligence" approach where the actions of the traders are related to a stochastic variable,  the market sentiment  , which we define as a mixture of public and private information. The model, despite the parsimonious approach , is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.
In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a stochastic variable, " the market sentiment " , which we define as a mixture of public and private information. The model, despite making just few basic assumptions over the trading strategies of the agents , is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.
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model follows a "zero intelligence" approach where the actions of the traders
agents follow a noise decision making process where their actions
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the parsimonious approach
making just few basic assumptions over the trading strategies of the agents