Faculty of Business and Economics - list of publications


The following list contains all information available to the publication.

STŘELEC, L. et al. On improved volatility modelling by fitting skewness in ARCH models. Journal of Applied Statistics. 2020. v. 47, no. 6, p. 1031--1063. ISSN 0266-4763. URL: https://www.tandfonline.com/doi/full/10.1080/02664763.2019.1671323

Original name:
On improved volatility modelling by fitting skewness in ARCH models
Czech name:
Written by (author):
doc. Ing. Luboš Střelec, Ph.D.
Department:
Department of Statistics and Operation Analysis
Kind of publication:
article in a professional periodical
Periodical:
Journal of Applied Statistics
Nature of article: paper
Volume no. (year):
47
Periodical number within the volume:
6
Year of publication:
2020
Starting page: 1031
Up to page:
1063
Number of pages:
33
Sub-specification:
článek je obsažen v databázi Web of Science
UT code by Web of Science:
EID code by Scopus:
Form of publication: printed version
Original language: English
Description in original language:
We study ARCH/GARCH effects under possible deviation from normality. Since skewness is the principal cause for deviations from normality in many practical applications, e.g. finance, we study in particular skewness. We propose robust tests for normality both for NoVaS and modified NoVaS transformed and original data. Such an approach is not applicable for EGARCH, but applicable for GARCH-GJR models. A novel test procedure is proposed for the skewness in autoregressive conditional volatility models. The power of the tests is investigated with various underlying models. Applications with financial data show the applicability and the capabilities of the proposed testing procedure.
Description in English:
Description in Czech:
Year of submission:
2020
Year of transmission:
RIV identification number:
Used in projects:
Robust approach to testing for normality of error terms in econometric models
URL:
https://www.tandfonline.com/doi/full/10.1080/02664763.2019.1671323
 
Entry made by:
Markéta Hejčová, DiS.
Last change:
05/04/2020 07:04 (Markéta Hejčová, DiS.)

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Source specification:

Journal of Applied Statistics. Abingdon: ISSN 0266-4763.

Original name:
Journal of Applied Statistics
Czech name:
Written by (author):
Kind of publication:
magazine
ISSN:
0266-4763
Country of publisher:
United Kingdom of Great Britain and Northern Ireland
Place of publishing: Abingdon
Publisher:
Taylor & Francis Ltd.
URL:
https://www.tandfonline.com/loi/cjas20
Reviewed magazine: no
Original language:
English
Description in original language:
Description in English:
Description in Czech:
 
Entry made by:
Last change: 10/02/2019 13:53 (Šárka Novotná)

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