Skip to main content
SpringerLink
Log in

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

  • Book
  • © 2022

Overview

Authors:
  1. Oliver Old

    1. Offenbach, Germany

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Gabler Theses (GT)

  • 777 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 16.99 USD 84.99
Discount applied Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 16.99 USD 109.99
Discount applied Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (7 chapters)

  1. Front Matter

    Pages i-xxii
    Download chapter PDF

  2. Introduction

    • Oliver Old
    Pages 1-12

  3. Financial time series

    • Oliver Old
    Pages 13-31

  4. Smoothing long term volatility

    • Oliver Old
    Pages 32-49

  5. Free-knot spline-GARCH model

    • Oliver Old
    Pages 50-103

  6. Simulation study

    • Oliver Old
    Pages 104-131

  7. Empirical study

    • Oliver Old
    Pages 132-152

  8. Conclusion

    • Oliver Old
    Pages 153-162

  9. Back Matter

    Pages 163-237
    Download chapter PDF
Back to top

Keywords

About this book

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.

Authors and Affiliations

  • Offenbach, Germany

    Oliver Old

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.

Bibliographic Information

  • Book Title: Modeling Time-Varying Unconditional Variance by Means of a Free-Knot Spline-GARCH Model

  • Authors: Oliver Old

  • Series Title: Gabler Theses

  • DOI: https://doi.org/10.1007/978-3-658-38618-4

  • Publisher: Springer Gabler Wiesbaden

  • eBook Packages: Business and Management, Business and Management (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022

  • Softcover ISBN: 978-3-658-38617-7Published: 28 July 2022

  • eBook ISBN: 978-3-658-38618-4Published: 27 July 2022

  • Series ISSN: 2731-3220

  • Series E-ISSN: 2731-3239

  • Edition Number: 1

  • Number of Pages: XXII, 237

  • Number of Illustrations: 57 illustrations in colour

  • Topics: IT in Business, Capital Markets

Publish with us

Policies and ethics

Back to top

Search

Navigation