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

Crisostomo Ayala, Ricardo. Forecasting realized densities: A comparison of historical, risk-neutral, risk-adjusted and sentiment-based transformations (Resumen) . 2022. Universidad Nacional de Educación a Distancia (España). Escuela Internacional de Doctorado. Programa de Doctorado en Ciencias

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Título Forecasting realized densities: A comparison of historical, risk-neutral, risk-adjusted and sentiment-based transformations (Resumen)
Autor(es) Crisostomo Ayala, Ricardo
Abstract This 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.
Materia(s) Matemáticas
Editor(es) Universidad Nacional de Educación a Distancia (España). Escuela Internacional de Doctorado. Programa de Doctorado en Ciencias
Director de tesis Prieto Rumeau, Tomas
Fecha 2022
Formato application/pdf
Identificador tesisuned:ED-Pg-Ciencias-Rcrisostomo
http://e-spacio.uned.es/fez/view/tesisuned:ED-Pg-Ciencias-Rcrisostomo
Idioma eng
Versión de la publicación acceptedVersion
Nivel de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/closedAccess
Tipo de recurso Thesis
Tipo de acceso Acceso cerrado

 
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Creado: Mon, 17 Oct 2022, 21:50:06 CET