Clustering Mutual Funds Based on Investment Similarity

被引:6
|
作者
Sakakibara, Takumasa [1 ]
Matsui, Tohgoroh [2 ]
Mutoh, Atsuko [1 ]
Inuzuka, Nobuhiro [1 ]
机构
[1] Nagoya Inst Technol, Nagoya, Aichi, Japan
[2] Chubu Univ, Kasugai, Aichi 487, Japan
关键词
clustering; mutual fund; k-means; spectral;
D O I
10.1016/j.procs.2015.08.251
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It is risky to invest to single or similar mutual funds because the variance of the return becomes large. Mutual funds are categorized based on the investment strategy by a company that rated funds based on performance, but the fund categories are different from its actual operations. While some previous studies have proposed methods to cluster mutual funds based on the historical performances, we cannot apply these methods to new mutual funds. In this paper, we clusters mutual funds based on the investment similarity instead of the historical performances. The contributions of this paper are: 1. To propose two new methods for classifying mutual funds based on the investment similarity, 2. To evaluate the proposed methods based on actual 551 Japanese mutual funds. (C) 2015 The Authors. Published by Elsevier B.V.
引用
收藏
页码:881 / 890
页数:10
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