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A network-based strategy of price correlations for optimal cryptocurrency portfolios

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  • Ruixue Jing
  • Luis Enrique Correa Rocha

Abstract

A cryptocurrency is a digital asset maintained by a decentralised system using cryptography. Investors in this emerging digital market are exploring the profitability potential of portfolios in place of single coins. Portfolios are particularly useful given that price forecasting in such a volatile market is challenging. The crypto market is a self-organised complex system where the complex inter-dependencies between the cryptocurrencies may be exploited to understand the market dynamics and build efficient portfolios. In this letter, we use network methods to identify highly decorrelated cryptocurrencies to create diversified portfolios using the Markowitz Portfolio Theory agnostic to future market behaviour. The performance of our network-based portfolios is optimal with 46 coins and superior to benchmarks up to an investment horizon of 14 days, reaching up to 1,066% average expected return within 1 day, with reasonable associated risks. We also show that popular cryptocurrencies are typically not included in the optimal portfolios. Past price correlations reduce risk and may improve the performance of crypto portfolios in comparison to methodologies based exclusively on price auto-correlations. Short-term crypto investments may be competitive to traditional high-risk investments such as the stock market or commodity market but call for caution given the high variability of prices.

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  • Ruixue Jing & Luis Enrique Correa Rocha, 2023. "A network-based strategy of price correlations for optimal cryptocurrency portfolios," Papers 2304.02362, arXiv.org.
    • Handle: RePEc:arx:papers:2304.02362
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    Cited by:

    1. Zhao, Yingxiu & Goodell, John W. & Shen, Dehua, 2024. "Spillover effects according to classification of cryptocurrency," Finance Research Letters, Elsevier, vol. 65(C).
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    3. Nichanan Sakolvieng, 2024. "Optimizing Cryptocurrency Portfolios: A Comparative Study of Rebalancing Strategies," GATR Journals jfbr220, Global Academy of Training and Research (GATR) Enterprise.
    4. Fakhfekh, Mohamed & Bejaoui, Azza & Bariviera, Aurelio F. & Jeribi, Ahmed, 2024. "Dependence structure between NFT, DeFi and cryptocurrencies in turbulent times: An Archimax copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).

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