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- W4220891923 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. • We jointly estimate VaR and ES to study the tail risk of Bitcoin. • We expand CAViaR model using Markov regime-switching which outperformed in- and out sample analyses. • Adding appropriate exogenous variables (Bubble index) in regime-switching can effectively improve model accuracy." @default.
- W4220891923 created "2022-04-03" @default.
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- W4220891923 date "2022-08-01" @default.
- W4220891923 modified "2023-09-27" @default.
- W4220891923 title "Jointly forecasting the value-at-risk and expected shortfall of Bitcoin with a regime-switching CAViaR model" @default.
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- W4220891923 doi "https://doi.org/10.1016/j.frl.2022.102826" @default.
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