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Media type:
E-Article
Title:
On the Statistical GARCH Model for Managing the Risk by Employing a Fat-Tailed Distribution in Finance
Contributor:
Long, H. Viet;
Jebreen, H. Bin;
Dassios, I.;
Baleanu, D.
Published:
MDPI AG, 2020
Published in:
Symmetry, 12 (2020) 10, Seite 1698
Language:
English
DOI:
10.3390/sym12101698
ISSN:
2073-8994
Origination:
Footnote:
Description:
The Conditional Value-at-Risk (CVaR) is a coherent measure that evaluates the risk for different investing scenarios. On the other hand, since the extreme value distribution has been revealed to furnish better financial and economical data adjustment in contrast to the well-known normal distribution, we here employ this distribution in investigating explicit formulas for the two common risk measures, i.e., VaR and CVaR, to have better tools in risk management. The formulas are then employed under the generalized autoregressive conditional heteroskedasticity (GARCH) model for risk management as our main contribution. To confirm the theoretical discussions of this work, the daily returns of several stocks are considered and worked out. The simulation results uphold the superiority of our findings.