An agent-based model of intra-day financial markets dynamics
| Autor: | Jacopo Staccioli, Mauro Napoletano |
|---|---|
| Přispěvatelé: | Università cattolica del Sacro Cuore [Milano] (Unicatt), Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP), Groupe de Recherche en Droit, Economie et Gestion (GREDEG), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Observatoire français des conjonctures économiques (Sciences Po) (OFCE), Sciences Po (Sciences Po), SKEMA Business School, HCC, European Project: 640772,H2020,H2020-FETPROACT-2014,DOLFINS(2015), Université Nice Sophia Antipolis (1965 - 2019) (UNS), Observatoire français des conjonctures économiques (OFCE) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Organizational Behavior and Human Resource Management
Economics and Econometrics Market microstructure Settore SECS-P/02 - POLITICA ECONOMICA Settore SECS-P/06 - ECONOMIA APPLICATA Settore SECS-P/01 - ECONOMIA POLITICA [SHS]Humanities and Social Sciences 0502 economics and business Intra-day financial dynamics Economics Econometrics Stylised facts High-Frequency Trading 050207 economics High-frequency trading Cluster analysis ComputingMilieux_MISCELLANEOUS Agent-based model Volatility clustering 050208 finance 05 social sciences Financial market Rational agent [SHS.ECO]Humanities and Social Sciences/Economics and Finance Agent-based artificial stock markets Volatility (finance) |
| Zdroj: | Journal of Economic Behavior and Organization Journal of Economic Behavior and Organization, Elsevier, 2021, ⟨10.1016/j.jebo.2020.05.018⟩ Journal of Economic Behavior and Organization, 2021, ⟨10.1016/j.jebo.2020.05.018⟩ |
| ISSN: | 0167-2681 |
| DOI: | 10.1016/j.jebo.2020.05.018⟩ |
| Popis: | We develop an agent-based model of a financial market which is able to jointly reproduce many of the stylised 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 tails in their distribution, order-side clustering). Our model combines heterogeneous boundedly rational agents, endogenously activating on the basis of market events, with realistic assumptions on market microstructure. In particular, we introduce a strict event scheduling borrowed from the Euronext exchange. We study the model in a bottom-up fashion under alternative scenarios regarding the sophistication of agents’ strategies. These scenarios allow us to disentangle the role of microstructure characteristics from trading behaviour in the emergence of market statistical properties. Our results reveal that traders’ endogenous activation is crucial to jointly reproduce most of these properties. The ability of the model to replicate the main stylised facts of financial markets proves that it can be fruitfully used by policymakers as a test-bed for regulatory experiments aimed at improving market outcomes at different time-scales. |
| Databáze: | OpenAIRE |
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