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

Author

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  • Jacopo Staccioli

    (Unicatt - Università cattolica del Sacro Cuore [Milano], SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa])

  • Mauro Napoletano

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur, OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po, SKEMA Business School, SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa])

Abstract

We build an agent-based model of a financial market that is able to jointly reproduce many of the stylized facts at different time-scales. 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 contributions we introduce a strict event scheduling borrowed from the EURONEXT exchange, and an endogenous rule for traders participation. We show that such a rule is crucial to match stylized facts.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Jacopo Staccioli & Mauro Napoletano, 2021. "An agent-based model of intra-day financial markets dynamics," SciencePo Working papers Main halshs-03046657, HAL.
    • Handle: RePEc:hal:spmain:halshs-03046657
    DOI: 10.1016/j.jebo.2020.05.018
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    2. Davide Bazzana & Michele Colturato & Roberto Savona, 2021. "Learning about Unprecedented Events: Agent-Based Modelling and the Stock Market Impact of COVID-19," Working Papers 2021.26, Fondazione Eni Enrico Mattei.

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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