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Using High-Frequency Entropy to Forecast Bitcoin’s Daily Value at Risk
In this paper we investigate the ability of several econometrical models to forecast value at risk for a sample of daily time series of cryptocurrency returns. Using high frequency data for Bitcoin, we estimate the entropy of intraday distribution of logreturns through the symbolic time series analy...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514585/ https://www.ncbi.nlm.nih.gov/pubmed/33266818 http://dx.doi.org/10.3390/e21020102 |