Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis
Walid Mensi,
Aviral Tiwari and
Seong-Min Yoon
Physica A: Statistical Mechanics and its Applications, 2017, vol. 471, issue C, 135-146
Abstract:
This paper estimates the weak-form efficiency of Islamic stock markets using 10 sectoral stock indices (basic materials, consumer services, consumer goods, energy, financials, health care, industrials, technology, telecommunication, and utilities). The results based on the multifractal detrended fluctuation analysis (MF-DFA) approach show time-varying efficiency for the sectoral stock markets. Moreover, we find that they tend to show high efficiency in the long term but moderate efficiency in the short term, and that these markets become less efficient after the onset of the global financial crisis. These results have several significant implications in terms of asset allocation for investors dealing with Islamic markets.
Keywords: MF-DFA; Hurst exponent; Efficiency; Islamic stock market; Sector index; Global financial crisis (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (38)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116310123
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
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:eee:phsmap:v:471:y:2017:i:c:p:135-146
DOI: 10.1016/j.physa.2016.12.034
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().