Optimization of Cryptocurrency Investment Portfolio Based on Modern Portfolio Theory

Abstract

Purpose of the article: The article examines the suitability of using the Modern Portfolio Theory (MPT) principle in cryptocurrency portfolio optimization.

Methodology/methods: As an input data was used the daily data of 10 most traded cryptocurrencies extracted from the web CoinMarketCap. The data for the period from 2 January 2021 to 1 September 2021 was selected as a sample. The Python programming language was used as a tool for implementation of the Modern Portfolio Theory. The Pandas open source tool was used for data analysis and manipulation. Mathematical operations were performed using the NumPy package. Library Matplotlib was used for creating static, animated, and interactive visualizations in Python.

Scientific aim: The research objective is to determine the possibilities of diversifying the cryptocurrency investment portfolio risk based on MPT.

Findings: The proposed optimal investment portfolio demonstrates that its performance is profitable not only in the optimization period but also in the validation period. Verification of the optimal investment portfolio confirms that the risk and profitability characteristics are fully respected by the proposed model. The article benefit is also the presentation of a comprehensive methodology for the creation and verification of an optimal portfolio based on MPT principles in the context of software support.

Conclusions: The case study of investment portfolio optimization (with the top 10 most traded cryptocurrencies) using MPT was developed, including verification of the proposed investment portfolio. Compared to traditional approaches, which include investor’s or portfolio manager’s decision-making, this approach provides investors with automated portfolio optimization processing based on mathematical and statistical calculations.