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Journals / Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi / 2022 / Cilt: 10 - Sayı: 1

A Swarm Intelligence Optimization Algorithm for Cryptocurrency Portfolio Optimization

Ahmet YURTSAL
Yunus KARAÖMER
Ali İhsan BENZER
Pages
347–363
Publication Date
2022-04-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In addition, the method was tested with different parameter values and different risk-averse coefficient values (λ).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent years, cryptocurrency has been widely adopted and seen as an alternative investment tool for investors.
📊
Key Findings & Data:Hourly data of 12 cryptocurrencies between 01.09.2020 and 01.04.2021 were used as data.
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Conclusion & Impact:In addition, the method was tested with different parameter values and different risk-averse coefficient values (λ).
🔬Design:Modeling & Simulation
📍Scope:2020 Verileri
⚙️Variables:Portfolio Optimization · Artificial Bee Colony · Cryptocurrency

Abstract

In recent years, cryptocurrency has been widely adopted and seen as an alternative investment tool for investors. However, which cryptocurrency to invest in and how much to invest becomes a problem. Since there is a conflict of multiple criteria, portfolio optimization (PO) is needed to solve the problem. In this study, an Artificial Bee Colony (ABC) algorithm has been developed based on Markowitz's mean-variance model (M-MVM). With this method, the portfolio of cryptocurrencies has been tried to be optimized. Hourly data of 12 cryptocurrencies between 01.09.2020 and 01.04.2021 were used as data. It has been observed that the ABC algorithm achieves good results in the solution of the problem in a reasonable time. In addition, the method was tested with different parameter values and different risk-averse coefficient values (λ).

Özet

In recent years, cryptocurrency has been widely adopted and seen as an alternative investment tool for investors. However, which cryptocurrency to invest in and how much to invest becomes a problem. Since there is a conflict of multiple criteria, portfolio optimization (PO) is needed to solve the problem. In this study, an Artificial Bee Colony (ABC) algorithm has been developed based on Markowitz's mean-variance model (M-MVM). With this method, the portfolio of cryptocurrencies has been tried to be optimized. Hourly data of 12 cryptocurrencies between 01.09.2020 and 01.04.2021 were used as data. It has been observed that the ABC algorithm achieves good results in the solution of the problem in a reasonable time. In addition, the method was tested with different parameter values and different risk-averse coefficient values (λ).

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Cite This Article

YURTSAL, A., KARAÖMER, Y., BENZER, A. İ. (2022). A Swarm Intelligence Optimization Algorithm for Cryptocurrency Portfolio Optimization. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, Cilt: 10 - Sayı: 1, 347–363. https://ajindex.com/articles/461874

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