Forecasting tail risk for Bitcoin: A dynamic peak over threshold approach

Rui Ke, Luyao Yang and Changchun Tan

Finance Research Letters, 2022, vol. 49, issue C

Abstract: This paper employs a dynamic peak over threshold (PoT) model to measure and forecast both the lower and upper tail Value at Risks (VaRs) of Bitcoin returns, which offers a new perspective to investigate the tail risk dynamics for Bitcoin. We evaluate the VaR forecasting accuracy of this model compared with that of the GARCH-EVT models based on Student-t, skewed Student-t and Generalized error distribution. The empirical results illustrate that the dynamic PoT model exhibits superior out-of-sample VaR predictive ability, specifically for the lower tail VaR. Thus, this model can be a useful and reliable alternative for forecasting tail risk.

Keywords: Tail risk; Value at risk; Peak over threshold; Bitcoin (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:49:y:2022:i:c:s1544612322003129

DOI: 10.1016/j.frl.2022.103086

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