General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

Abstract

To examine the interdependency and evolution of Pakistan's stock market, we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange (KSE-100) index. Using the minimum spanning tree network-based method, we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan. Our results reveal a star-like structure after the general elections of 2018 and before those in 2008, and a tree-like structure otherwise. We also highlight key nodes, the presence of different clusters, and compare the differences between the three elections. Additionally, the sectorial centrality measures reveal economic expansion in three industrial sectors-cement, oil and gas, and fertilizers. Moreover, a strong overall intermediary role of the fertilizer sector is observed. The results indicate a structural change in the stock market network due to general elections. Consequently, through this analysis, policy makers can focus on monitoring key nodes around general elections to estimate stock market stability, while local and international investors can form optimal diversification strategies.

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Examining Network Structures and Dynamics of World Energy Companies in Stock Markets: A Complex Network Approach

“…Particularly, with Pearson cross-correlation network method, we can perceive topological properties of the threshold network (TN), produced by assigning a value of threshold (Lin et al, 1994;Boginski et al, 2005), the asset graph (AG) , the minimum spanning tree (MST) (Mantegna, 1999;Mantegna and Stanley, 2000), and the planar maximally filtered graph (PMFG) (Tumminello et al, 2005;Song et al, 2011). Clearly, Pearson correlation-based network methods have been extensively applied to numerous financial systems (Onnela et al, 2004;Kwapień et al, 2009;Coletti, 2016;Mai et al, 2018;Zięba et al, 2019;Memon et al, 2020), and is thus used in this paper.…”

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