RT Journal Article
T1 Self-organizing maps could improve the classification of Spanish mutual funds
A1 Moreno, David
A1 Marco, Paulina
A1 Olmeda, Ignacio
AB In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. The methodology that we propose allows us to identify which mutual funds are misclassified in the sense that they have historical performances which do not conform to the investment objectives established in their official category. According to this, we conclude that, on average, over 40% of mutual funds could be misclassified. Then, we propose an alternative classification, based on a double-step methodology, and we find that it achieves a significantly lower rate of misclassifications. The portfolios obtained from this alternative classification also attain better performances in terms of return/risk and include a smaller number of assets.
PB Elsevier
SN 0377-2217
YR 2006
FD 2006-10
LK https://hdl.handle.net/10016/7747
UL https://hdl.handle.net/10016/7747
LA eng
DS e-Archivo
RD 27 jul. 2024