A Particle Swarm Optimization Copula-Based Approach with Application to Cryptocurrency Portfolio Optimisation

Jules Clément Mba, Magdaline Mbong Mai

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Blockchain and cryptocurrency are gradually going mainstream with new cryptocurrencies introduced every single day. The speculative nature of these digital assets expose their prices to large fluctuations. Trading these crypto-assets necessitate an adequate understanding of this emerging market as well as adequate tools to model the market risk and efficient allocation of funds. This may assist crypto investors in taking advantage of the highly volatile aspects of these assets. The portfolio consider in this study consists of six cryptocurrencies: four traditional cryptocurrencies (BTC, ETH, BNB and XRP) and two stablecoins (USDT and USDC). We examine the copula particle swarm optimization (CPSO) portfolio strategy against three other portfolio strategies, namely, the global minimum variance (GMV), the most diversified portfolio (MDP) and the minimum tail dependent (MTD). CPSO appears to be a promising strategy during extreme market conditions while GMV seem favorable during normal market conditions. Most importantly, hedge and safe-havens ability of the two stablecoins is clearly exhibited with CPSO, while their diversification property is inhibited.

Original languageEnglish
Article number285
JournalJournal of Risk and Financial Management
Volume15
Issue number7
DOIs
Publication statusPublished - Jul 2022
Externally publishedYes

Keywords

  • CVaR
  • copula
  • cryptocurrencies
  • differential evolution
  • particle swarm optimization

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics
  • Accounting
  • Business, Management and Accounting (miscellaneous)

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