Integrating agent-based modelling with copula theory: Preliminary insights and open problems

Open Access
Authors
Publication date 2020
Host editors
  • V.V. Krzhizhanovskaya
  • G. Závodszky
  • M.H. Lees
  • J.J. Dongarra
  • P.M.A. Sloot
  • S. Brissos
  • J. Teixeira
Book title Computational Science – ICCS 2020
Book subtitle 20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020 : proceedings
ISBN
  • 9783030504199
ISBN (electronic)
  • 9783030504205
Series Lecture Notes in Computer Science
Event 20th International Conference on Computational Science, ICCS 2020
Volume | Issue number III
Pages (from-to) 212-225
Number of pages 14
Publisher Cham: Springer
Organisations
  • Faculty of Law (FdR)
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
  • Faculty of Law (FdR) - Leibniz Center for Law (FdR)
  • Faculty of Science (FNWI)
Abstract

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.

Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-030-50420-5_16
Other links https://www.scopus.com/pages/publications/85087282371
Downloads
Permalink to this page
Back