ASSESSMENT THE PREDICTABILITY IN THE PRICE DYNAMICS FOR THE TOP 10 CRYPTOCURRENCIES: THE IMPACTS OF RUSSIA-UKRAINE WAR

【Author】 De Araujo, Fernando H. A.; Fernandes, Leonardo H. S.; Silva, Jose W. L.; Sobrinho, Kleber E. S.; Tabak, Benjamin Miranda

【Source】FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY

【影响因子】4.555

【Abstract】This paper has investigated the predictability of the top 10 cryptocurrencies' price dynamics, ranked by their daily market capitalization and trade volume, via the information theory quantifiers. Our analysis considers the Complexity-entropy causality plane to study the temporal evolution of the price of these cryptocurrencies and their respective locations along this 2D map, bearing in mind after and during the Russia-Ukraine war. Moreover, we apply the permutation entropy and the Jensen-Shannon statistical complexity measure to rank these cryptocurrencies similarly to a complexity hierarchy. Our findings reflect that the Russian-Ukraine war affects the informational efficiency of cryptocurrency dynamics. Specifically, the cryptocurrencies notably showed a decrease in informational inefficiency (USD-coin, Binance-USD, BNB, Dogecoin, and XRP). At the same time, the cryptocurrencies with more expressiveness for the financial market, considering the volume traded and the capitalized market, were strongly impacted, presenting an increase in informational inefficiency (Tether, Cardano, Ethereum, and Bitcoin). It clarifies the potential of cryptocurrencies to mitigate exogenous shocks and their capability to use with portfolio selection, risk diversification and herding behavior.

【Keywords】Russia-Ukraine War; Cryptocurrency; Information Theory Quantifiers; Complexity; Inefficiency

【发表时间】2023 2023 JUN 21

【收录时间】2023-08-03

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-市场分析