Mixed-frequency quantile regressions to forecast value-at-risk and expected shortfall

Although quantile regression to calculate risk measures is widely established in the financial literature, when considering data observed at mixed-frequency, an extension is needed. In this paper, a model is built on a mixed-frequency quantile regressions to directly estimate the Value-at-Risk (VaR)...

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Detalles Bibliográficos
Autores principales: Candila, Vincenzo, Gallo, Giampiero M., Petrella, Lea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191104/
https://www.ncbi.nlm.nih.gov/pubmed/37361082
http://dx.doi.org/10.1007/s10479-023-05370-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191104/
https://www.ncbi.nlm.nih.gov/pubmed/37361082
http://dx.doi.org/10.1007/s10479-023-05370-x

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