The paper sketches and elaborates on a framework integrating agent-based modelling with advanced quantitative probabilistic methods based on copula theory. The motivation for such a framework is illustrated on a artificial market functioning with canonical asset pricing models, showing that dependencies specified by copulas can enrich agent-based models to capture both micro-macro effects (e.g. herding behaviour) and macro-level dependencies (e.g. asset price dependencies). In doing that, the paper highlights the theoretical challenges and extensions that would complete and improve the proposal as a tool for risk analysis.
CITATION STYLE
Fratrič, P., Sileno, G., van Engers, T., & Klous, S. (2020). Integrating agent-based modelling with copula theory: Preliminary insights and open problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12139 LNCS, pp. 212–225). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-50420-5_16
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