This paper examines the connectedness between cryptocurrencies and major fiat currencies in a multivariate framework using vine copulas. One of the advantages of this method is the flexibility in the choice of distributions used to model complex dependencies. The results show that the dependence, measured conditionally or unconditionally, is positive and higher for the pairs of the same market than those across markets. Moreover, a low significant dependency is found between cryptocurrencies and the main conventional currencies. Based on the Value-at-Risk (VaR) and expected shortfall (ES) analyses, vine copulas produce accurate risk measures by adding cryptocurrencies to a portfolio of fiat currencies.

本文在使用藤蔓copulas的多变量框架中研究了加密货币与主要法定货币之间的联系。该方法的优点之一是可以灵活选择用于对复杂依赖性进行建模的分布。结果表明，有条件或无条件地测量的依赖关系对于同一市场中的货币对是正的，并且高于跨市场的货币对。此外，在加密货币和主要的常规货币之间发现了较低的重要依存关系。根据风险价值（VaR）和预期的缺口（ES）分析，藤本植物通过将加密货币添加到法定货币组合中来产生准确的风险度量。