On the factors of Bitcoin’s value at risk
Abstract This study investigates the factors of Bitcoin’s tail risk, quantified by Value at Risk (VaR). Extending the conditional autoregressive VaR model proposed by Engle and Manganelli (2004), I examine 30 potential drivers of Bitcoin’s 5% and 1% VaR. For the 5% VaR, quantity variables, such as B...
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2021
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oai:doaj.org-article:065c625fa7a74ef8b415965ddc8bbe9d2021-11-14T12:25:10ZOn the factors of Bitcoin’s value at risk10.1186/s40854-021-00297-32199-4730https://doaj.org/article/065c625fa7a74ef8b415965ddc8bbe9d2021-11-01T00:00:00Zhttps://doi.org/10.1186/s40854-021-00297-3https://doaj.org/toc/2199-4730Abstract This study investigates the factors of Bitcoin’s tail risk, quantified by Value at Risk (VaR). Extending the conditional autoregressive VaR model proposed by Engle and Manganelli (2004), I examine 30 potential drivers of Bitcoin’s 5% and 1% VaR. For the 5% VaR, quantity variables, such as Bitcoin trading volume and monetary policy rate, were positively significant, but these effects were attenuated when new samples were added. The 5% VaR responds positively to the Internet search index and negatively to the fluctuation of returns on commodity variables and the Chinese stock market index. For the 1% VaR, variables related to the macroeconomy play a key role. The consumer sentiment index exerts a strong positive effect on the 1% VaR. I also find that the 1% VaR has positive relationships with the US economic policy uncertainty index and the fluctuation of returns on the corporate bond index.Ji Ho KwonSpringerOpenarticleBitcoinValue at riskCAViaRPublic financeK4430-4675FinanceHG1-9999ENFinancial Innovation, Vol 7, Iss 1, Pp 1-31 (2021) |
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Bitcoin Value at risk CAViaR Public finance K4430-4675 Finance HG1-9999 |
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Bitcoin Value at risk CAViaR Public finance K4430-4675 Finance HG1-9999 Ji Ho Kwon On the factors of Bitcoin’s value at risk |
| description |
Abstract This study investigates the factors of Bitcoin’s tail risk, quantified by Value at Risk (VaR). Extending the conditional autoregressive VaR model proposed by Engle and Manganelli (2004), I examine 30 potential drivers of Bitcoin’s 5% and 1% VaR. For the 5% VaR, quantity variables, such as Bitcoin trading volume and monetary policy rate, were positively significant, but these effects were attenuated when new samples were added. The 5% VaR responds positively to the Internet search index and negatively to the fluctuation of returns on commodity variables and the Chinese stock market index. For the 1% VaR, variables related to the macroeconomy play a key role. The consumer sentiment index exerts a strong positive effect on the 1% VaR. I also find that the 1% VaR has positive relationships with the US economic policy uncertainty index and the fluctuation of returns on the corporate bond index. |
| format |
article |
| author |
Ji Ho Kwon |
| author_facet |
Ji Ho Kwon |
| author_sort |
Ji Ho Kwon |
| title |
On the factors of Bitcoin’s value at risk |
| title_short |
On the factors of Bitcoin’s value at risk |
| title_full |
On the factors of Bitcoin’s value at risk |
| title_fullStr |
On the factors of Bitcoin’s value at risk |
| title_full_unstemmed |
On the factors of Bitcoin’s value at risk |
| title_sort |
on the factors of bitcoin’s value at risk |
| publisher |
SpringerOpen |
| publishDate |
2021 |
| url |
https://doaj.org/article/065c625fa7a74ef8b415965ddc8bbe9d |
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AT jihokwon onthefactorsofbitcoinsvalueatrisk |
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