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A mutual information based R-vine copula strategy to estimate VaR in high frequency stock market data
In this paper, we explore mutual information based stock networks to build regular vine copula structure on high frequency log returns of stocks and use it for the estimation of Value at Risk (VaR) of a portfolio of stocks. Our model is a data driven model that learns from a high frequency time seri...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211166/ https://www.ncbi.nlm.nih.gov/pubmed/34138970 http://dx.doi.org/10.1371/journal.pone.0253307 |