Optimization and Diversification of Cryptocurrency Portfolios: A Composite Copula-Based Approach

Abstract

This paper focuses on the selection and optimisation of a cryptoasset portfolio, using the K-means clustering algorithm and GARCH C-Vine copula model combined with the differential evolution algorithm. This integrated approach allows the construction of a diversified portfolio of eight cryptocurrencies and determines an optimal allocation strategy making it possible to minimize the conditional value-at-risk of the portfolio and maximise the return. Our results show that stablecoins such as True-USD are negatively correlated to the other cryptoassets in the portfolio and could therefore be a safe haven for crypto-investors during market turmoil. Our findings are in line with previous studies exhibiting stablecoins as potential diversifiers.

A K-Means Classification and Entropy Pooling Portfolio Strategy for Small and Large Capitalization Cryptocurrencies

“…They find that the best risk–return ratio (return 0.46%, risk 5.56%) is from the cluster with an average level of international diversification. Tenkam et al [ 22 ] use the K-means clustering algorithm and the GARCH C-Vine copula model to explore the diversification benefits of a portfolio comprising the 100 largest cryptocurrencies. They find a negative correlation between stablecoins and other cryptocurrencies, implying that they have the potential to be a haven during market instability for cryptocurrency holders.…”

Crypto Price Prediction as an Investment Opportunity: An Empirical Study of Three Global Cryptocurrencies

“…According to Tenkam et al [31], the crypto market in 2009 spawned a diversification of digital financial portfolios that was efficiently spread across financial market classes. A diverse price distribution promotes investors' assessment of the risk management of their crypto portfolio in terms of calculating risk with a return on wealth proportional to the number of assets invested.…”

“…Tenkam et al [31] found that diversified digital financial distribution leads to growth results by investors in managerial portfolio risk, with a rate of return from investment weights that can produce 80% of each crypto coin asset selection.…”

“…These results show that investors' expectations of returns on the value of crypto assets can be reduced using these cryptocurrencies. Concurrently with the selection indicator for cryptocurrency coin investment price weights where [31] through the development of crypto assets up until now in investments that have the potential to be diversified by portfolio expectations can increase from cryptocurrency returns (IWPP +) to investor expectations which will decrease or make investors warier of investing in crypto assets [32].…”

“…According to the findings of Drokin & Zhitlukhin's study [11], if the variability of price distribution disparities is allowed, this can interact with various altcoin assets. Moreover, BTC and ETH assets have a large price movement variability, hence raising the risk in crypto portfolio management for investors selecting future crypto price evaluations [31].…”