Measuring market risk with GARCH models under Basel III: selection and application to German firms

Vatis Christian Kemezang (), André Ilaire Djou () and Ivette Gnitedem Keubeng ()
Additional contact information
Vatis Christian Kemezang: University of Douala
André Ilaire Djou: Institut Universitaire Des Grandes Écoles Des Tropiques (IUGET)
Ivette Gnitedem Keubeng: University of Dschang

SN Business & Economics, 2024, vol. 4, issue 10, 1-30

Abstract: Abstract The main objective of this study is to examine GARCH-type models in market risk assessment with a distribution of returns for German companies in the DAX 40 list. Our study contributes to three major areas. The first step was to highlight the empirically observed stylized facts in the high-frequency financial data for eight DAX 40 assets. We were able to analyze the dynamics and asymmetry of returns on high-frequency financial assets. Then, we compared the GARCH model with the EGARCH and APARCH models based on stylized facts regarding volatility behavior in high-frequency financial assets. The EGARCH model is well suited for capturing all the stylized facts of the eight financial assets. The use of high-frequency data in risk measurement provides more accurate data and adapted calculation methods. The combination of the value at risk with the EGARCH model provides a clearer idea of the potential loss and the average loss beyond a threshold and a better understanding of the degree of exposure of assets to risk. These findings suggest that EGARCH-type models allow for an accurate analysis of market risk assessment with a distribution of returns for German companies in the DAX 40 list.

Keywords: Backtesting; Financial; Risk market; Volatility (search for similar items in EconPapers)
JEL-codes: C14 E37 G01 G13 G14 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s43546-024-00699-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:snbeco:v:4:y:2024:i:10:d:10.1007_s43546-024-00699-2

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43546

DOI: 10.1007/s43546-024-00699-2

Access Statistics for this article

SN Business & Economics is currently edited by Gino D'Oca

More articles in SN Business & Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().