Publicación:
Forecasting realized densities: A comparison of historical, risk-neutral, risk-adjusted and sentiment-based transformations (Resumen)

Vista sencilla de ítem
dc.contributor.authorCrisostomo Ayala, Ricardo
dc.contributor.directorPrieto Rumeau, Tomás
dc.date.accessioned2024-05-20T19:56:24Z
dc.date.available2024-05-20T19:56:24Z
dc.date.issued2022
dc.description.abstractThis thesis deals with the mathematical models used to forecast future asset prices. Estimating asset prices is arguably one of the most relevant problems for risk managers, central bankers, and investors. Traditional statistical methods rely on point estimates or confidence intervals to estimate future realizations. However, when it comes to analyzing asset prices at a future date, obtaining the full price distribution significantly improves the information available for decision-making. This is particularly relevant in financial prices, which typically exhibit asymmetries, fat tails and other non-normal features. Consequently, estimation methods relying on mean-variance approximations do not appropriately reproduce the real-world characteristics of financial asset prices, leading to biased predictions and inappropriate model choices.en
dc.description.versionversión final
dc.identifier.urihttps://hdl.handle.net/20.500.14468/17490
dc.language.isoen
dc.publisherUniversidad Nacional de Educación a Distancia (España). Escuela Internacional de Doctorado. Programa de Doctorado en Ciencias
dc.relation.centerFacultad de Ciencias
dc.relation.phdPrograma de doctorado en ciencias
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.titleForecasting realized densities: A comparison of historical, risk-neutral, risk-adjusted and sentiment-based transformations (Resumen)es
dc.typetesis doctorales
dc.typedoctoral thesisen
dspace.entity.typePublication
Archivos
Bloque original
Mostrando 1 - 1 de 1
Miniatura
Nombre:
CRISOSTOMO_AYALA__Ricardo_Resumen.pdf
Tamaño:
1.05 MB
Formato:
Adobe Portable Document Format
Descargar
Colecciones
Tesis doctorales