Impact of Political Events in Democratic and Military Regimes on Pakistan Stock Exchange

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dc.contributor.author Nidal Shabbir Khan, 01-297171-015
dc.date.accessioned 2022-02-04T05:18:35Z
dc.date.available 2022-02-04T05:18:35Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/123456789/11806
dc.description Supervised by Dr. Shahzad Butt en_US
dc.description.abstract The purpose of this research paper is to examine and investigate the different political events in two major government regimes i.e. military and democratic regimes, and its effect on stock market returns from 1999 to 2017. By comparing the market efficiency in two government regime styles i.e. military and democratic, we try to determine how certain and uncertain events in both regimes effect Pakistan stock market returns and volatility. Pre event data and post event data windows are used in the study with event window of 2, 5, and 15 days. This study implies E- Garch model for examining the impact of events on Pakistan stock returns and its volatility. The empirical results show that political events of equal magnitude and intensity in both regimes have differently significant impacts on stock returns. Further this study also shows that there is a significant relationship between stock market returns/volatility and style of government. Moreover, this study also determines that stock market is inefficient for a short span of time and market recommences to its normality after 15 days of event occurrence and soon absorbs the noisy information. Findings reveal that stock market is more efficient in military regime, although events comparison to democratic regime may not be exactly equal in magnitude to those in military regime. en_US
dc.language.iso en en_US
dc.publisher Management Studies BUIC en_US
dc.relation.ispartofseries MS (Finance);MFN-T 9388
dc.subject Political Events en_US
dc.subject Democratic en_US
dc.subject Military Regimes en_US
dc.title Impact of Political Events in Democratic and Military Regimes on Pakistan Stock Exchange en_US
dc.type MS Thesis en_US


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