@inproceedings{b0e6869a72094c9b8024a1ab1b67ddd8,
title = "Diversified Crypto Assets Portfolio Optimization Using K-Means Clustering Algorithm And The Efficient Frontier",
abstract = "The objective of this study is to examine the possibility of utilizing the machine learning approach (K-means clustering) for finding efficient frontier based on the risk and return association. Using 84 crypto coins included in CMC Crypto 200, this research applies k-means clustering to group the research data. The result show that crypto coins are grouped into 6 clusters. Eight crypto coins selected to construct portfolio investment based on Sharpe ratio and market capitalization for portfolio optimization stage. Our testing model shown that all of our portfolio model outperforms the market especially compared with CMC Crypto 200 Index performance.",
keywords = "efficient frontier, k-means clustering, portfolio optimization",
author = "Rizki Setiawan and Hakim, {Muhammad Saiful}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Technology and Engineering Management Conference - Asia Pacific, TEMSCON-ASPAC 2023 ; Conference date: 15-12-2023 Through 16-12-2023",
year = "2023",
doi = "10.1109/TEMSCON-ASPAC59527.2023.10531468",
language = "English",
series = "Proceedings of 2023 IEEE Technology and Engineering Management Conference - Asia Pacific, TEMSCON-ASPAC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2023 IEEE Technology and Engineering Management Conference - Asia Pacific, TEMSCON-ASPAC 2023",
address = "United States",
}