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Can Artificial Neural Networks Predict the Survival Capacity of Mutual Funds? Evidence from Spain

Author

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  • Laura Fabregat-Aibar

    (Department of Business Management, Faculty of Business and Economics, Universitat Rovira i Virgili, 43204 Reus, Spain)

  • Maria-Teresa Sorrosal-Forradellas

    (Department of Business Management, Faculty of Business and Economics, Universitat Rovira i Virgili, 43204 Reus, Spain)

  • Glòria Barberà-Mariné

    (Department of Business Management, Faculty of Business and Economics, Universitat Rovira i Virgili, 43204 Reus, Spain)

  • Antonio Terceño

    (Department of Business Management, Faculty of Business and Economics, Universitat Rovira i Virgili, 43204 Reus, Spain)

Abstract

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 disappearance.

Suggested Citation

  • Laura Fabregat-Aibar & Maria-Teresa Sorrosal-Forradellas & Glòria Barberà-Mariné & Antonio Terceño, 2021. "Can Artificial Neural Networks Predict the Survival Capacity of Mutual Funds? Evidence from Spain," Mathematics, MDPI, vol. 9(6), pages 1-10, March.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:6:p:695-:d:522910
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    References listed on IDEAS

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