A complex networks based analysis of jump risk in equity returns: An evidence using intraday movements from Pakistan stock market

Faheem Aslam, Yasir T. Muhammad, Saqib Aziz*, Jamal Ouenniche

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We employ a multi-stage methodology combining complex network analytics and financial risk modelling to unveil the correlation structures amongst the price jump risks of companies forming the KSE-100 index in Pakistan. We identify the most influential companies in terms of jump risk, and identify communities — clusters of companies with similar price movement characteristics or with highly correlated price jumps. We find that equities in Pakistan stock market experience jumps in different time periods that are correlated to varying degrees within and across industries resulting in 19 different communities, four of which are strongly connected. While Oil & Gas, Cement and Banking sectors exhibit a significant representation of firms in communities, the automobile industry, however, seems to play an important role in risk propagation. These results provide an interesting insight to investors and other stakeholders from an emerging market viewpoint identifying the major sectors driving the volatility of KSE-100 index.

Original languageEnglish
Article number100418
Pages (from-to)1-11
JournalJournal of Behavioral and Experimental Finance
Volume28
Early online date2 Nov 2020
DOIs
Publication statusPublished - Dec 2020

Keywords

  • complex network analysis
  • intraday returns
  • jump risk
  • realised jumps
  • realised volatility

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