| Research Title |
Mutual Fund Clustering by Using the K-means Method |
| Date of Distribution |
6 January 2022 |
| Conference |
| Title of the Conference |
SIBR 2022 (Tokyo) Conference on Interdisciplinary Business and Economics Research |
| Organiser |
Society of Interdisciplinary Business Research (SIBR) |
| Conference Place |
Hotel MyStays OchanomiZu in Tokyo, Japan |
| Province/State |
Tokyo, Japan |
| Conference Date |
6 January 2022 |
| To |
7 January 2022 |
| Proceeding Paper |
| Volume |
11(2022) |
| Issue |
1 (่January) |
| Page |
t22-036 |
| Editors/edition/publisher |
Society of Interdisciplinary Business Research |
| Abstract |
This study aimed to group mutual funds using K-means clustering analysis and compare the K-means clustering process and existing clustering techniques. Using information of mutual funds in the category of equity funds, general fixed-income funds, and balanced mutual funds open-end fund type that the Association of Investment Management Companies has rated. Using data from January 2016 to December 2020 for 60 months, information on prices, risks, and investment policies are employed. There are ten asset management funds with the highest net assets out of 173 funds. The tool used to analyze the K-means technique using a statistical package program set the value K=3. Funds can be divided into three groups, which can be divided into Group 1 has a total of 5 mutual funds or 2.89%, Group 2 has a total of 144 mutual funds or 83.24%, Group 3 has a total of 24 mutual funds or 13.87 percent, it was found that the efficiency of fund grouping using the K-Means technique was compared with the existing grouping close at 55.31%. |
| Author |
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| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Full paper |
| Type of Presentation |
Oral |
| Part of thesis |
true |
| Presentation awarding |
false |
| Attach file |
|
| Citation |
0
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Publication
Journal Publication
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