Forecasting the Jordanian stock index: modelling asymmetric volatility and distribution effects within a GARCH framework

Heitham Al-Hajieh, Hashem AlNemer, Timothy Rodgers and Jacek Niklewski ()
Additional contact information
Jacek Niklewski: King Abdulaziz University

Copernican Journal of Finance & Accounting, 2015, vol. 4, issue 2, 9-26

Abstract: The modelling of market returns can be especially problematical in emerging and frontier financial markets given the propensity of their returns to exhibit significant non-normality and volatility asymmetries. This paper attempts to identify which representations within the GARCH family of models can most efficiently deal with these issues. A number of different distributions (normal, Student t, GED and skewed Student) and different volatility of returns asymmetry representations (EGARCH and GJR- -GARCH) are examined. Our data set consists of daily Jordanian stock market returns over the period January 2000 – November 2014. Using both the Superior Predicative Ability (SPA) and Model Confidence Set (MCS) testing frameworks it is found that using GJR-GARCH with a skewed Student distribution most accurately and efficiently forecasts Jordanian market movements. Our findings are consistent with similar research undertaken in respect to developed markets.

Keywords: GARCH, asymmetry; distributions (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://apcz.umk.pl/CJFA/article/view/CJFA.2015.013/7403 (application/pdf)

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:cpn:umkcjf:v:4:y:2015:i:2:p:9-26

Access Statistics for this article

Copernican Journal of Finance & Accounting is currently edited by Leszek Dziawgo

More articles in Copernican Journal of Finance & Accounting from Uniwersytet Mikolaja Kopernika
Bibliographic data for series maintained by Miroslawa Buczynska ().