Formulating MCoVaR to Quantify Joint Transmissions of Systemic Risk across Crypto and Non-Crypto Markets: A Multivariate Copula Approach

Evidence that cryptocurrencies exhibit speculative bubble behavior is well documented. This evidence could trigger global financial instability leading to systemic risk. It therefore crucial quantify risk and investigate its transmission mechanism across crypto markets other markets. We can accomplish this using the so-called multivariate conditional value-at-risk (MCoVaR), which measures tail of a targeted asset from each market on set multiple assets being jointly in distress remaining their median states. In paper, we aimed find analytic formulas by considering copulas, allow for separation margins dependence structures modeling returns aforementioned assets. Compared normal Student’s t benchmark models Johnson’s SU model, copula-based with non-normal produced MCoVaR forecast superior coverage backtesting performances. Using corresponding Delta MCoVaR, found be potential sources transmitted within towards S&P 500, oil, gold, was more apparent during COVID-19 period encompassing recent 2021 event.