Classifying Spanish mutual funds according to their survival capacity using SOM

Issue title: Special section: Fuzzy Systems in Management and Information Science

Guest editors: José M. Merigó, Salvador Linares-Mustaros and Joan Carles Ferrer-Comalat

Article type: Research Article

Authors: Barberà-Mariné, M. Glòria | Fabregat-Aibar, Laura^{; *} | Sorrosal-Forradellas, M. Teresa | Terceño, Antonio

Affiliations: Department of Business Management, Universitat Rovira i Virgili, Av. de la Universitat, Reus, Spain

Correspondence: [*] Corresponding author. Laura Fabregat-Aibar, Department of Business Management, Faculty of Business and Economics, Universitat Rovira i Virgili, Av. de la Universitat, 1, 43204, Reus, Spain. E-mail: [email protected].

Abstract: The main purpose of this article is to analyze the survival capacity of mutual funds based on their characteristics. The methodology used to meet this objective is Self-Organizing Maps (SOM), a type of Artificial Neural Network that allows patterns to be grouped together according to their similarity, enabling us to classify mutual funds into surviving funds and disappeared funds. We consider the following variables: age, size, investment flows, performance, volatility, and Morningstar rating. We use a sample of 1,617 Spanish mutual funds, of which 943 had disappeared between 2004 and 2016. The results obtained indicate that SOM accurately classifies 80% of mutual funds. Therefore, SOMs are effective instruments for classifying the disappearance of Spanish mutual funds and the variables used to define them can explain their survival capacity.

Keywords: Mutual funds, self-organizing maps, spanish market, survival capacity, surviving funds, disappeared funds

DOI: 10.3233/JIFS-179640

Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 5489-5495, 2020