An agent-based model of intra-day financial markets dynamics

We propose a parsimonious agent-based model of a financial market at the intra-day time scale that is able to jointly reproduce many of the empirically validated stylised facts. These include properties related to returns (leptokurtosis, absence of linear autocorrelation, volatility clustering), trading volumes (volume clustering, correlation between volume and volatility), and timing of trades (number of price changes, autocorrelation of durations between subsequent trades, heavy tail in their distribution, order-side clustering). With respect to previous constributions we introduce a strict event scheduling borrowed from the Euronext exchange, and an endogenous rule for traders' participation. We find that the latter proves crucial for matching our target stylised facts.