Modeling Time-Varying Unconditional Variance by Means of a Free-Knot Spline-GARCH Model

The book addresses the problem of a time-varying unconditional variance of return processes utilizing a spline function. The knots of the spline functions are estimated as free parameters within a joined estimation process together with the parameters of the mean, the conditional variance and the sp...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (-)
Otros Autores: Old, Oliver, autor (autor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Wiesbaden : Springer Fachmedien Wiesbaden 2022.
Edición:1st ed
Colección:Springer eBooks.
Gabler Theses,
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b47162442*spi
Descripción
Sumario:The book addresses the problem of a time-varying unconditional variance of return processes utilizing a spline function. The knots of the spline functions are estimated as free parameters within a joined estimation process together with the parameters of the mean, the conditional variance and the spline function. With the help of this method, the knots are placed in regions where the unconditional variance is not smooth. The results are tested within an extensive simulation study and an empirical study employing the S&P500 index. About the author: The dissertation was written at the Chair of Applied Statistics and Methods of Empirical Social Research at the Faculty of Economics and Business Administration of the FernUniversität in Hagen. From 2021 Oliver Old researched in the field of applied statistics, machine learning and data science at two EU-Horizon projects at the Department of Anesthesiology, Intensive Care and Pain Therapy at the University Hospital Frankfurt.
Descripción Física:XXII, 237 páginas, 57 ilustraciones (color)
Formato:Forma de acceso: World Wide Web.