General election effect on the network topology of Pakistan\u2019s stock market: network-based study of a political event

Bilal Ahmed Memon,Rabia Tahir,Hongxing Yao

doi:10.1186/s40854-019-0165-x

Bilal Ahmed Memon, Rabia Tahir + Show 1 more

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https://doi.org/10.1186/s40854-019-0165-x

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Journal: Financial Innovation	Publication Date: Jan 7, 2020
Citations: 13	License type: open-access

Affiliation: Jiangsu University

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.

Highlights

Political risk is a key factor affecting the performance of a country’s financial market
Previous research proposes various methods to study the impact of elections on stock markets [e.g., GARCH and Cumulative abnormal volatility (CAV) (Białkowski et al 2008), Support vector regression (Chiu et al 2012), Cumulative average abnormal returns (CAAR) and Abnormal returns AR (Oehler et al 2013; Savita and Ramesh 2015), Regression analysis (Abidin et al 2010; Liew and Rowland 2016) Granger
Network-based methods are widely applied by researchers to study interdependency and the evolution of stock markets, such as minimum spanning tree (MST) (Mantegna 1999; Onnela et al 2003b; Zhao et al 2018; Yao and Memon 2019), threshold networks (CT) (Boginski et al 2005; Lee and Nobi 2018), planar maximally filtered graphs (PMFG) (Tumminello et al 2005; Yan et al 2015; Musmeci et al 2016), wavelet (Wang et al 2017), and multiple criteria decision making (MCDM) (Kou et al 2014)

Summary

Introduction

Political risk is a key factor affecting the performance of a country’s financial market. We extend the financial network literature by studying the impact of general elections on the network topology of Pakistan’s stock market. Network-based methods are widely applied by researchers to study interdependency and the evolution of stock markets, such as minimum spanning tree (MST) (Mantegna 1999; Onnela et al 2003b; Zhao et al 2018; Yao and Memon 2019), threshold networks (CT) (Boginski et al 2005; Lee and Nobi 2018), planar maximally filtered graphs (PMFG) (Tumminello et al 2005; Yan et al 2015; Musmeci et al 2016), wavelet (Wang et al 2017), and multiple criteria decision making (MCDM) (Kou et al 2014). This paper examines the interdependency and evolution of Pakistan’s stock market by using MST before and after the general elections of 2018, 2013, and 2008

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Results

Conclusion