Jointly forecasting the value-at-risk and expected shortfall of Bitcoin with a regime-switching CAViaR model

Lingbo Gao, Wuyi Ye and Ranran Guo

Finance Research Letters, 2022, vol. 48, issue C

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 (search for similar items in EconPapers)
JEL-codes: C58 G15 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:48:y:2022:i:c:s1544612322001258

DOI: 10.1016/j.frl.2022.102826

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