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Uncertainty and Volatility in MENA Stock Markets During the Arab Spring

Listed author(s):
  • Al Shugaa, Ameen
  • Masih, Mansur

This paper sheds light on the economic impacts of political uncertainty caused by the civil uprisings that swept across the Arab World and have been collectively known as the Arab Spring. Measuring documented effects of political uncertainty on regional stock market indices, we examine the impact of the Arab Spring on the volatility of stock markets in eight countries in the Middle East and North Africa (MENA) region: Egypt, Lebanon, Jordon, United Arab Emirate, Qatar, Bahrain, Oman and Kuwait. This analysis also permits testing the existence of financial contagion among equity markets in the MENA region during the Arab Spring. To capture the time-varying and multi-horizon nature of the evidence of volatility and contagion in the eight MENA stock markets, we apply two robust methodologies on data from November 2008 to March 2014: MGARCH-DCC, Continuous Wavelet Transforms (CWT). Our results tend to indicate two key findings. First, the discrepancies between the volatile stock markets of countries directly impacted by the Arab Spring and the countries that were not directly impacted indicate that international investors may still enjoy portfolio diversification and investment in MENA markets. Second, the lack of financial contagion during the Arab Spring suggests that there is little evidence of cointegration among MENA markets implying the opportunities of portfolio diversification. Providing a general analysis of the economic situation and the investment climate in the MENA region during and after the Arab Spring, this study bears significant importance for the policy makers, local and international investors, and market regulators.

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File URL: https://mpra.ub.uni-muenchen.de/58867/1/MPRA_paper_58867.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 58867.

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Date of creation: 27 Aug 2014
Handle: RePEc:pra:mprapa:58867
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  1. Lean, Hooi Hooi & Teng, Kee Tuan, 2013. "Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach," Economic Modelling, Elsevier, vol. 32(C), pages 333-342.
  2. Mohamed El Hedi Arouri, 2009. "Time-varying characteristics of cross-market linkages with empirical application to Gulf stock markets," Managerial Finance, Emerald Group Publishing, vol. 36(1), pages 57-70, December.
  3. Elie I. Bouri & Georges Yahchouchi, 2014. "Do return and volatility traverse the Middle Eastern and North African (MENA) stock markets borders?," Journal of Economic Studies, Emerald Group Publishing, vol. 41(2), pages 317 - 344, March.
  4. Ramazan Genay & Faruk Seļuk & Brandon Whitcher, 2003. "Systematic risk and timescales," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 108-116.
  5. Arifovic, Jasmina & Gencay, Ramazan, 2000. "Statistical properties of genetic learning in a model of exchange rate," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 981-1005, June.
  6. Chau, Frankie & Deesomsak, Rataporn & Wang, Jun, 2014. "Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 1-19.
  7. Masih, Rumi & Masih, Abul M. M., 2001. "Long and short term dynamic causal transmission amongst international stock markets," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 563-587, August.
  8. Mohamed El Hedi Arouri, 2010. "Time-varying characteristics of cross-market linkages with empirical application to Gulf stock markets," Managerial Finance, Emerald Group Publishing, vol. 36(1), pages 57-70, February.
  9. Elie I. Bouri & Georges Yahchouchi, 2014. "Do return and volatility traverse the Middle Eastern and North African (MENA) stock markets borders?," Journal of Economic Studies, Emerald Group Publishing, vol. 41(2), pages 317-344, March.
  10. Aloui, Chaker & Hkiri, Besma, 2014. "Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis," Economic Modelling, Elsevier, vol. 36(C), pages 421-431.
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