【Author】
Gao, Lingbo; Ye, Wuyi; Guo, Ranran
【Source】FINANCE RESEARCH LETTERS
【Abstract】We explore the dynamic tail risk in the Bitcoin market by jointly estimating value-at-risk (VaR) and expected shortfall (ES) using the conditional autoregressive value-at-risk (CAViaR) model. To enable more accurate measurement, we construct a Markov regime-switching (MS) model in which the time-varying transition probability is driven by the information contained in asset price bubbles. This is motivated by prior evidence that bubbles are a key indicator of the economic cycle and contain important information on systemic risk. Using daily Bitcoin data from 2013 to 2021, the results provide strong evidence of a form of regime change in Bitcoin's VaR and ES. Furthermore, the bubble index has a significant impact on tail risk and improves the model's ability to estimate and predict VaR and ES.
【Keywords】CAViaR; Bitcoin; Bubble index; Markov regime-switching models
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