Measuring value-at-risk and expected shortfall of newer cryptocurrencies: new insights
A significant amount of historical returns is needed for the generalized autoregressive conditional heteroscedasticity (GARCH) models to be calibrated. Newer cryptocurrencies, such as non-fungible tokens (NFTs), have relatively limited data to create robust parameter estimates. This study uses a new...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Cogent Business & Management |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23311975.2024.2416096 |