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dc.contributor.authorPonta, L.
dc.contributor.authorScalas, E. 
dc.contributor.authorRaberto, M.
dc.contributor.authorCincotti, S.
dc.description.abstractA simulation of high-frequency market data is performed with the Genoa Artificial Stock Market. Heterogeneous agents trade a risky asset in exchange for cash. Agents have zero intelligence and issue random limit or market orders depending on their budget constraints. The price is cleared by means of a limit order book. A renewal order-generation process is used having a waiting-time distribution between consecutive orders that follows a Weibull law, in line with previous studies. The simulation results show that this mechanism can reproduce fat-tailed distributions of returns without ad-hoc behavioral assumptions on agents. In the simulated trade process, when the order waiting-times are exponentially distributed, trade waiting times are exponentially distributed. However, if order waiting times follow a Weibull law, analogous results do not hold. These findings are interpreted in terms of a random thinning of the order renewal process. This behavior is compared with order and trade durations taken from real financial data.
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.subjectArtificial stock market
dc.subjecthigh-frequency financial time-series
dc.subjectrandom thinning
dc.subjectWeibull distribution
dc.titleStatistical analysis and agent-based microstructure modeling of high-frequency financial trading
dc.journal.titleIEEE Journal on Selected Topics in Signal Processingen_US

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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España