Volatility modeling of Islamic stock indices returns using GARCH models

Joint Authors

Bin Labib, Bu Bakir
Sahnun, Sayyid Ahmad

Source

Revue du Chercheur

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

Economy and Commerce

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