文章基本信息

标题：A Particle Swarm Optimization Copula-Based Approach with Application to Cryptocurrency Portfolio Optimisation
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作者：Jules Clément Mba ; Magdaline Mbong Mai
期刊名称：Journal of Risk and Financial Management
印刷版ISSN：1911-8074
出版年度：2022
卷号：15
期号：7
页码：1-14
DOI：10.3390/jrfm15070285
语种：English
出版社：MDPI, Open Access Journal
摘要：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.
关键词：cryptocurrencies;copula;particle swarm optimization;differential evolution;CVaR