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Does parameterization affect the complexity of agent-based models?

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    SYSNO ASEP0547638
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleDoes parameterization affect the complexity of agent-based models?
    Author(s) Kukačka, Jiří (UTIA-B) RID, ORCID
    Krištoufek, Ladislav (UTIA-B) RID, ORCID
    Number of authors2
    Source TitleJournal of Economic Behavior & Organization. - : Elsevier - ISSN 0167-2681
    Roč. 192, č. 1 (2021), s. 324-356
    Number of pages33 s.
    Publication formPrint - P
    Languageeng - English
    CountryNL - Netherlands
    Keywordsfinancial agent-based models ; parameterization ; complex systems ; multifractal sensitivity analysis
    Subject RIVAH - Economics
    OECD categoryEconomic Theory
    R&D ProjectsGJ17-12386Y GA ČR - Czech Science Foundation (CSF)
    Method of publishingLimited access
    Institutional supportUTIA-B - RVO:67985556
    UT WOS000719785700002
    EID SCOPUS85118496051
    DOI10.1016/j.jebo.2021.10.007
    AnnotationWe examine the complexity of financial returns generated by popular agent-based models through studying multifractal properties of such time series. Specifically, we are interested in the sensitivity of the models to their parameter settings and whether some patterns emerge in the connection between complexity and a specific type of parameter. We find that (i) herding behavior mostly boosts the model complexity as measured by multifractality, (ii) various in-built stabilizing factors increase model complexity, while (iii) the role of the intensity of choice, the number of agents, as well as the chartists’ representation have rather model-specific effects. Finally, the core feature driving the model complexity seems to be the implementation of a switching mechanism governing agents’ interactions. The heterogeneous set of nine analyzed models thus offers some universal concepts that hold across their range. Our results also indicate that complex dynamics are observed not only for the benchmark parameter settings but also for other combinations of parameter values for most models. This opens new avenues for future research and specifically motivates examining the models in more detail by focusing on other dynamic properties in addition to the herein presented multifractality.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2022
    Electronic addresshttps://www.sciencedirect.com/science/article/pii/S0167268121004339
Number of the records: 1  

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