Articles producció científica> Enginyeria Química

Complex decision-making strategies in a stock market experiment explained as the combination of few simple strategies

  • Identification data

    Identifier: imarina:9216729
    Authors:
    Poux-Medard, GaelCobo-Lopez, SergioDuch, JordiGuimera, RogerSales-Pardo, Marta
    Abstract:
    Many studies have shown that there are regularities in the way human beings make decisions. However, our ability to obtain models that capture such regularities and can accurately predict unobserved decisions is still limited. We tackle this problem in the context of individuals who are given information relative to the evolution of market prices and asked to guess the direction of the market. We use a networks inference approach with stochastic block models (SBM) to find the model and network representation that is most predictive of unobserved decisions. Our results suggest that users mostly use recent information (about the market and about their previous decisions) to guess. Furthermore, the analysis of SBM groups reveals a set of strategies used by players to process information and make decisions that is analogous to behaviors observed in other contexts. Our study provides and example on how to quantitatively explore human behavior strategies by representing decisions as networks and using rigorous inference and model-selection approaches.
  • Others:

    Author, as appears in the article.: Poux-Medard, Gael; Cobo-Lopez, Sergio; Duch, Jordi; Guimera, Roger; Sales-Pardo, Marta
    Department: Enginyeria Química
    URV's Author/s: Cobo Lopez, Sergio / Duch Gavaldà, Jordi / Guimera Manrique, Roger / Sales Pardo, Marta
    Keywords: Stochastic block model Prediction Persistence Human behavior Decision making process Choice mechanisms Blockmodels
    Abstract: Many studies have shown that there are regularities in the way human beings make decisions. However, our ability to obtain models that capture such regularities and can accurately predict unobserved decisions is still limited. We tackle this problem in the context of individuals who are given information relative to the evolution of market prices and asked to guess the direction of the market. We use a networks inference approach with stochastic block models (SBM) to find the model and network representation that is most predictive of unobserved decisions. Our results suggest that users mostly use recent information (about the market and about their previous decisions) to guess. Furthermore, the analysis of SBM groups reveals a set of strategies used by players to process information and make decisions that is analogous to behaviors observed in other contexts. Our study provides and example on how to quantitatively explore human behavior strategies by representing decisions as networks and using rigorous inference and model-selection approaches.
    Thematic Areas: Social sciences, mathematical methods Modeling and simulation Mathematics, interdisciplinary applications Engenharias iv Engenharias i Computer science applications Computational mathematics Ciencias sociales Ciência da computação
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: sergio.cobo@urv.cat roger.guimera@urv.cat jordi.duch@urv.cat marta.sales@urv.cat
    Author identifier: 0000-0002-3597-4310 0000-0003-2639-6333 0000-0002-8140-6525
    Record's date: 2024-10-19
    Journal volume: 10
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-021-00280-z
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Epj Data Science. 10 (1): 26-
    APA: Poux-Medard, Gael; Cobo-Lopez, Sergio; Duch, Jordi; Guimera, Roger; Sales-Pardo, Marta (2021). Complex decision-making strategies in a stock market experiment explained as the combination of few simple strategies. Epj Data Science, 10(1), 26-. DOI: 10.1140/epjds/s13688-021-00280-z
    Article's DOI: 10.1140/epjds/s13688-021-00280-z
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2021
    Publication Type: Journal Publications
  • Keywords:

    Computational Mathematics,Computer Science Applications,Mathematics, Interdisciplinary Applications,Modeling and Simulation,Social Sciences, Mathematical Methods
    Stochastic block model
    Prediction
    Persistence
    Human behavior
    Decision making process
    Choice mechanisms
    Blockmodels
    Social sciences, mathematical methods
    Modeling and simulation
    Mathematics, interdisciplinary applications
    Engenharias iv
    Engenharias i
    Computer science applications
    Computational mathematics
    Ciencias sociales
    Ciência da computação
  • Documents:

  • Cerca a google

    Search to google scholar