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Can artificial neural networks predict the survival capacity of mutual funds? Evidence from Spain

  • Dades identificatives

    Identificador: imarina:9187029
    Autors:
    Fabregat-Aibar, LauraSorrosal-Forradellas, Maria-TeresaBarbera-Marine, GloriaTerceno, Antonio
    Resum:
    Recently, the total net assets of mutual funds have increased considerably and turned them into one of the main investment instruments. Despite this increment, every year a considerable number of funds disappear. The main purpose of this paper is to determine if the neural networks can be a valid instrument to detect the survival capacity of a fund, using the traditional variables linked to the literature of disappearance funds: age, size, performance and volatility. This paper also incorporates annualized variation in return and the Sharpe ratio as variables. The data used is a sample of Spanish mutual funds during 2018 and 2019. The results show that the network correctly classifies funds into surviving and non‐surviving with a total error of 13%. Moreover, it shows that not all variables are significant to determine the survival capacity of a fund. The results indicate that surviving and non‐surviving funds differ in variables related to performance and its variation, volatility and the Sharpe ratio. However, age and size are not significant variables. As a conclusion, the neural network correctly predicts the 87% of survival capacity of mutual funds. Therefore, this methodology can be used to classify this financial instrument according to its survival or disappear-ance.
  • Altres:

    Autor segons l'article: Fabregat-Aibar, Laura; Sorrosal-Forradellas, Maria-Teresa; Barbera-Marine, Gloria; Terceno, Antonio
    Departament: Gestió d'Empreses
    Autor/s de la URV: Barberà Mariné, Maria Glòria / Fabregat Aibar, Laura / Sorrosal Forradellas, Maria Teresa / Terceño Gómez, Antonio
    Paraules clau: Survival capacity Spanish market Neural network Mutual funds Improve Failure
    Resum: Recently, the total net assets of mutual funds have increased considerably and turned them into one of the main investment instruments. Despite this increment, every year a considerable number of funds disappear. The main purpose of this paper is to determine if the neural networks can be a valid instrument to detect the survival capacity of a fund, using the traditional variables linked to the literature of disappearance funds: age, size, performance and volatility. This paper also incorporates annualized variation in return and the Sharpe ratio as variables. The data used is a sample of Spanish mutual funds during 2018 and 2019. The results show that the network correctly classifies funds into surviving and non‐surviving with a total error of 13%. Moreover, it shows that not all variables are significant to determine the survival capacity of a fund. The results indicate that surviving and non‐surviving funds differ in variables related to performance and its variation, volatility and the Sharpe ratio. However, age and size are not significant variables. As a conclusion, the neural network correctly predicts the 87% of survival capacity of mutual funds. Therefore, this methodology can be used to classify this financial instrument according to its survival or disappear-ance.
    Àrees temàtiques: Química Mathematics (miscellaneous) Mathematics (all) Mathematics General mathematics Engineering (miscellaneous) Computer science (miscellaneous) Astronomia / física
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: laura.fabregat@urv.cat gloria.barbera@urv.cat gloria.barbera@urv.cat antonio.terceno@urv.cat antonio.terceno@urv.cat mariateresa.sorrosal@urv.cat
    Identificador de l'autor: 0000-0002-0077-161X 0000-0003-2578-1301 0000-0003-2578-1301 0000-0001-5348-8837 0000-0001-5348-8837 0000-0003-4719-452X
    Data d'alta del registre: 2024-09-28
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.mdpi.com/2227-7390/9/6/695
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Mathematics. 9 (6): 695-
    Referència de l'ítem segons les normes APA: Fabregat-Aibar, Laura; Sorrosal-Forradellas, Maria-Teresa; Barbera-Marine, Gloria; Terceno, Antonio (2021). Can artificial neural networks predict the survival capacity of mutual funds? Evidence from Spain. Mathematics, 9(6), 695-. DOI: 10.3390/math9060695
    DOI de l'article: 10.3390/math9060695
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2021
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Computer Science (Miscellaneous),Engineering (Miscellaneous),Mathematics,Mathematics (Miscellaneous)
    Survival capacity
    Spanish market
    Neural network
    Mutual funds
    Improve
    Failure
    Química
    Mathematics (miscellaneous)
    Mathematics (all)
    Mathematics
    General mathematics
    Engineering (miscellaneous)
    Computer science (miscellaneous)
    Astronomia / física
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