Network Analysis of Pakistan Stock Market During the Turbulence of Economic Crisis

Memon, Bilal Ahmed; Yao, Hongxing; Aslam, Faheem; Tahir, Rabia

doi:10.3846/bme.2019.11394

Cited by 16 publications

(7 citation statements)

References 44 publications

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“…The methodology of MST construction is often adopted to analyze the interdependence of stock markets (Han, 2019; Mantegna, 1999; Memon and Yao, 2019; Nguyen et al ., 2019), and this contributes to a proper visualization and better understanding. The same methodology was also adopted to analyze numerous economic and financial crises (Mahamood et al ., 2019; Majapa and Gossel, 2016; Memon et al. , 2019; Yang et al ., 2014).…”

Section: Methodsmentioning

confidence: 99%

“…Despite its complexity, network analysis method is a more appropriate way to study the behavior of stock markets than other linear approaches because of the nonlinear nature of stock returns (Han, 2019). Moreover, the use of network theory for analysis purpose becomes a more powerful tool in the period of crises, as it is capable of capturing instability and variations in the network's topological features due to crisis (Memon et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

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Temporal changes in global stock markets during COVID-19: an analysis of dynamic networks

Zaheer

Aslam

Mohmand

et al. 2022

CFRI

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PurposeCOVID-19 evolved from a local health crisis to a pandemic and affected countries worldwide accordingly. Similarly, the impacts of the pandemic on the performance of global stock markets could be time-varying. This study applies a dynamic network analysis approaches to evaluate the evolution over time of the impact of COVID-19 on the stock markets' network.Design/methodology/approachDaily closing prices of 55 global stock markets from August 1, 2019 to September 10, 2020 were retrieved. This sample period was further divided into nine subsample periods for dynamic analysis purpose. Distance matrix based on long-range correlations was calculated, using rolling window's length of 100 trading days, rolled forward at an interval of one month's working days. These distance matrices than used to construct nine minimum spanning trees (MSTs). Network characteristics were figured out, community detection and network rewiring techniques were also used for extracting meaningful from these MSTs.FindingsThe findings are, with the evolution of COVID-19, a change in co-movements amongst stock markets' indices occurred. On the 100th day from the date of reporting of the first cluster of cases, the co-movement amongst the stock markets become 100% positively correlated. However, the international investor can still get better portfolio performance with such temporal correlation structure either avoiding risk or pursuing profits. A little change is observed in the importance of authoritative node; however, this central node changed multiple times with change of epicenters. During COVID-19 substantial clustering and less stable network structure is observed.Originality/valueIt is confirmed that this work is original and has been neither published elsewhere, nor it is currently under consideration for publication elsewhere.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Temporal changes in global stock markets during COVID-19: an analysis of dynamic networks

Zaheer

Aslam

Mohmand

et al. 2022

CFRI

Self Cite

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“…We apply the algorithm in [46] to an undirected graph G = (N, E, W) in formation of the MST. Moreover, the rolling window technique is largely used in the literature to construct dynamic network [47][48][49]. While relying on complex network theory, the study connects all pairs of nodes conforming to the distance matrix D m = (d m i,j ).…”

Section: Methodsmentioning

confidence: 99%

The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

Memon

Yao

2021

Journal of Open Innovation: Technology, Market, and Complexity

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Studies examining the impact of COVID-19 using network dynamics are scant and tend to evaluate a specific local stock market. We present a thorough investigation of 58 world stock market networks using a complex network approach spanning across the uncertain times that have resulted from the coronavirus outbreak. First, we use the daily closing prices of the world stock market indices to construct dynamic complex networks and sixteen minimum spanning tree (MST) maps for the period from December 2019 to March 2021. Second, we present the topological evolution properties of time-varying MSTs by applying normalized tree length, diameter, average path length, and centrality measures. Moreover, the empirical results suggest that (1) the highest correlation among the world stock markets is observed during the first wave of the COVID-19 pandemic in the months of February–March 2020; (2) most of the MSTs appear lower in hierarchy, and many chain-like structures are formed due to the sheer impact of pandemic-related crises; (3) Germany remained a hub node in many of the MSTs; and (4) the tree severely contracted during the first wave of the COVID-19 outbreak (during the months of February and March 2020) and expanded slightly afterwards. Moreover, the results obtained from this study can be used for the development of financial stability policies and stock market regulations worldwide.

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“…Similarly, in 2020, when the COVID-19 pandemic hit Pakistan, it led to political instability as well as economic uncertainty. This caused a drop in the KSE-100 Index, which is the benchmark index of the Pakistan Stock Exchange [ 7 ]. Moreover, there have been several studies that have investigated the relationship between political instability and stock market performance in emerging economies.…”

Section: Literature Reviewmentioning

confidence: 99%

The relationship between political instability and stock market performance: An analysis of the MSCI index in the case of Pakistan

Mai,

Nawaz Saleem,

Kamran

2023

PLoS ONE

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The stock market is the barometer of the economy that reflects the overall health and direction of the economic development and is affected by different factors including social, environmental and political. It is important to investigate the effect of the political instability on the stock market performance, especially on emerging economies. Therefore, we aim to study the relationship between political instability and stock market performance in Pakistan. To meet our objectives, we used past data from 1996 to 2021. Data are collected from the DataStream data base. MSCI indices are used as the proxy for the Stock market performance of the selected country. World governance six indicators are used in the study as the explanatory variable concentrating the political instability index as the main explanatory variable. Regression analysis is used but two-way robustness analysis was done for the accuracy of the findings through GMM methods and taking GDP as another endogenous variable. Our findings shows that the political stability has significant positive impact on the stock market performance while, political instability has negative impact on stock market performance. Moreover, other governance indicators has a significant positive impact on performance. However, political instability disrupts the operations and economical activities that leads to decrease the investor confidence and also decrease the foreign investment with the increment of the risk in the country. Moreover, our study has some implications for investors to develop the diversified portfolio to minimize the risk and policy makers can increase their foreign direct investment within the economy by controlling the political instability.

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Network Analysis of Pakistan Stock Market During the Turbulence of Economic Crisis

Cited by 16 publications

References 44 publications

Temporal changes in global stock markets during COVID-19: an analysis of dynamic networks

Temporal changes in global stock markets during COVID-19: an analysis of dynamic networks

The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

The relationship between political instability and stock market performance: An analysis of the MSCI index in the case of Pakistan

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