Statistical analysis and agent-based microstructure modeling of high-frequency financial trading

Linda Ponta, Enrico Scalas, Marco Raberto, Silvano Cincotti

Risultato della ricerca: Contributo su rivistaArticolo in rivistapeer review

Abstract

A 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.

Lingua originaleInglese
Numero di articolo6064868
pagine (da-a)381-387
Numero di pagine7
RivistaIEEE Journal on Selected Topics in Signal Processing
Volume6
Numero di pubblicazione4
DOI
Stato di pubblicazionePubblicato - 2012
Pubblicato esternamente

Fingerprint

Entra nei temi di ricerca di 'Statistical analysis and agent-based microstructure modeling of high-frequency financial trading'. Insieme formano una fingerprint unica.

Cita questo