Risk and return for cryptocurrencies as alternative investment: Kohonen maps clustering

A. Kaminskyi, I. Miroshnychenko, Kostiantyn Pysanets
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引用次数: 1

Abstract

The active development of cryptocurrencies in recent years allows identifying the process of forming new class of alternative investment assets. There was formed a sample of cryptocurrencies based on criteria capitalization and historical returns for estimation investment risk of this asset class. The sample included 327 cryptocurrencies, each of which has a capitalization of more than $ 1 mln. Measurement of investment risk was carried out on the basis of five approaches. The first one is grounded on the variability indicators. The second approach includes risk assessment in the context of asymmetry. The third is based on the concept of capital formation as part of the risk measures VaR and CVaR. The fourth focuses on measuring sensitivity risk. The fifth approach supposes using the Hurst exponent to measure risk. Based on the measures of these approaches, a comprehensive risk assessment was carried out. To cluster cryptocurrencies by riskiness, indicators from each group were selected, to which the technique of Kohonen self-organizing map was applied. The result was a partition of cryptocurrencies into three clusters. The analysis of the results is proposed and the corresponding conclusions and recommendations are made.
加密货币作为另类投资的风险和回报:Kohonen地图聚类
近年来,加密货币的积极发展使人们能够确定形成新型另类投资资产的过程。根据标准资本化和历史回报形成了一个加密货币样本,用于估计该资产类别的投资风险。样本包括327种加密货币,每种加密货币的市值都超过100万美元。在五种方法的基础上进行了投资风险的度量。第一个是基于可变性指标。第二种方法包括不对称背景下的风险评估。第三种是基于资本形成概念的风险度量VaR和CVaR。第四个侧重于测量敏感性风险。第五种方法假设使用赫斯特指数来衡量风险。根据这些方法的措施,进行了全面的风险评估。根据风险对加密货币进行聚类,从每组中选取指标,并应用Kohonen自组织图技术对其进行聚类。其结果是将加密货币划分为三个簇。对研究结果进行了分析,并提出了相应的结论和建议。
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CiteScore
1.70
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