Volatility modeling of Islamic stock indices returns using GARCH models
Joint Authors
Bin Labib, Bu Bakir
Sahnun, Sayyid Ahmad
Source
Issue
Vol. 19, Issue 1 (31 Dec. 2019), pp.551-562, 12 p.
Publisher
Kasdi Merbah University Faculty of Economics Commercial Sciences and Management Sciences
Publication Date
2019-12-31
Country of Publication
Algeria
No. of Pages
12
Main Subjects
Topics
Abstract EN
The purpose of this study is to find the GARCH specification and innovations distribution combination which best models the returns volatility of four major Islamic equity indices DJIM, S&P500 SH, FTSE SWORLD.IS and MSCI ISWD.
The conditionally heteroscedastic autoregressive models considered are GARCH, EGARCH, AGARCH, NARCH, NGARCH, GJR GARCH, APARCH and NGARCH whereas the distributions considered are the normal, student, cauchy, laplace, logistics and EVD distributions.
The study of the statistical properties of the different return series confirms that GARCH models are the most suitable for modeling purposes.
The results of the estimations suggest that the combinations offering the best volatility modeling are: NGARCH-Laplace for the DJIM, APGARCH-Laplace or AGARCH-Laplace for the S&P500 SH, GJR GARCH-Logistics for the SWORLD.IS and GJR GARCH-Student or GJR GARCH-Logistics for the MSCI ISWD.
American Psychological Association (APA)
Sahnun, Sayyid Ahmad& Bin Labib, Bu Bakir. 2019. Volatility modeling of Islamic stock indices returns using GARCH models. Revue du Chercheur،Vol. 19, no. 1, pp.551-562.
https://search.emarefa.net/detail/BIM-954674
Modern Language Association (MLA)
Sahnun, Sayyid Ahmad& Bin Labib, Bu Bakir. Volatility modeling of Islamic stock indices returns using GARCH models. Revue du Chercheur Vol. 19, no. 1 (2019), pp.551-562.
https://search.emarefa.net/detail/BIM-954674
American Medical Association (AMA)
Sahnun, Sayyid Ahmad& Bin Labib, Bu Bakir. Volatility modeling of Islamic stock indices returns using GARCH models. Revue du Chercheur. 2019. Vol. 19, no. 1, pp.551-562.
https://search.emarefa.net/detail/BIM-954674
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 561-562
Record ID
BIM-954674