Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Statistics & Risk Modeling

with Applications in Finance and Insurance

Editor-in-Chief: Stelzer, Robert

4 Issues per year


Cite Score 2016: 0.33

SCImago Journal Rank (SJR) 2016: 0.346
Source Normalized Impact per Paper (SNIP) 2016: 0.167

Mathematical Citation Quotient (MCQ) 2016: 0.32

Online
ISSN
2196-7040
See all formats and pricing
More options …
Volume 30, Issue 4 (Dec 2013)

Issues

Dynamic structured copula models

Wolfgang Karl Härdle / Ostap Okhrin / Yarema Okhrin
Published Online: 2013-12-10 | DOI: https://doi.org/10.1524/strm.2013.2004

Abstract

There is an increasing demand for models of multivariate time-series with time-varying and non-Gaussian dependencies. The available models suffer from the curse of dimensionality or from restrictive assumptions on the parameters and distributions. A promising class of models is that of hierarchical Archimedean copulae (HAC), which allows for non-exchangeable and non-Gaussian dependency structures with a small number of parameters. In this paper we develop a novel adaptive estimation technique of the parameters and of the structure of HAC for time-series. The approach relies on a local change-point detection procedure and a locally constant HAC approximation. Typical applications are in the financial area but also recently in the spatial analysis of weather parameters. We analyse the time varying dependency structure of stock indices and exchange rates. Both examples reveal periods with constant and turmoil dependencies. The economic significance of the suggested modelling is evaluated using the Value-at-Risk of a portfolio.

Keywords: Copula; multivariate distribution; Archimedean copula; adaptive estimation

About the article

Accepted: 2013-08-18

Received: 2013-01-16

Published Online: 2013-12-10

Published in Print: 2013-12-01


Citation Information: Statistics & Risk Modeling, ISSN (Online) 2196-7040, ISSN (Print) 2193-1402, DOI: https://doi.org/10.1524/strm.2013.2004.

Export Citation

© 2013 by Walter de Gruyter Berlin Boston. Copyright Clearance Center

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Ostap Okhrin and Anastasija Tetereva
Econometrics, 2017, Volume 5, Number 2, Page 26
[2]
Matthias R. Fengler and Ostap Okhrin
Computational Statistics & Data Analysis, 2016, Volume 100, Page 131

Comments (0)

Please log in or register to comment.
Log in