Modeling Market Volatility in Emerging Markets: The case of Daily Data in Amman Stock Exchange 1992-2004
Raya Rousan and
Ritab Al-Khouri
International Journal of Applied Econometrics and Quantitative Studies, 2005, vol. 2, issue 4, 99-118
Abstract:
This paper attempts to investigate the volatility of the Jordanian emerging stock market using daily observations from Amman Stock Exchange Composite Index (ASE) for the period from January 1, 1992 through December 31, 2004. Preliminary analysis of the data shows significant departure from normality. Moreover, returns and residuals show a significant level of serial correlation which is related to the conditional heteroskedasticity due to the time varying volatility. These results suggest that ARCH and GARCH models can provide good approximation for capturing the characteristics of ASE. The empirical analysis supports the hypothesis of symmetric volatility; hence, both good and bad news of the same magnitude have the same impact on the volatility level. Moreover, the volatility persists in the market for a long period of time, which makes ASE market inefficient; therefore, returns can be easily predicted and forecasted.
Keywords: Stock Exchange; Modeling Volatility; Emerging Markets; Jordan (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.usc.es/economet/reviews/ijaeqs248.pdf
No
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:eaa:ijaeqs:v:2:y2005:i:4_8
Ordering information: This journal article can be ordered from
http://www.usc.es/economet/info.htm
Access Statistics for this article
More articles in International Journal of Applied Econometrics and Quantitative Studies from Euro-American Association of Economic Development
Bibliographic data for series maintained by M. Carmen Guisan ().