Modeling Time-Varying Unconditional Variance by Means of a Free-Knot Spline-GARCH Model
Published on 28. July 2022
Book
Paperback/Softback
XXII, 237 pages
978-3-658-38617-7 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2022
Language
English
Place of publication
Wiesbaden
Germany
Publishing group
Springer Fachmedien Wiesbaden GmbH
Target group
Professional and scholarly
Illustrations
57 farbige Abbildungen
XXII, 237 p. 57 illus. in color.
Dimensions
Height: 210 mm
Width: 148 mm
Thickness: 15 mm
Weight
341 gr
ISBN-13
978-3-658-38617-7 (9783658386177)
DOI
10.1007/978-3-658-38618-4
Schweitzer Classification
Other editions
Additional editions
E-Book
07/2022
Springer Gabler
€96.29
Available for download
Person
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.
Content
Introduction.- Financial time series.- Smoothing long term volatility.- 4 Free-knot spline-GARCH model.- Simulation study.- Empirical study.- Conclusion.