Forecasting and backtesting systemic risk in the cryptocurrency market

【Author】 Fang, Sheng; Cao, Guangxi; Egan, Paul

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【Abstract】Cryptocurrency has become an increasingly important tool in both portfolio investment and government regulation. As a relatively new asset class, cryptocurrencies are prone to extreme volatility, with the potential for significant downward movements over the short term. This paper uses MES and oCoVaR to forecast the systemic risk in the cryptocurrency market and subse-quently tests the validity based on unconditional coverage and independence. The results of this paper show that a DCC-GARCH model performs well in forecasting systemic risk. The paper also shows that Aoen, EOS and Sinacoin are the best forecasters of systemic risk across the 191 cryptocurrencies analysed over the full estimation period. Our findings have important implica-tions for investors and policy-makers with a vested interest in the cryptocurrency market.

【Keywords】Cryptocurrency; Systemic risk; Forecasting; Backtesting

【发表时间】2023 JUN

【收录时间】2023-06-10

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-区块链金融监管