The Coronavirus (COVID-19) outbreak has become one of the biggest threats to the global economy and financial markets. This study aims to analyze the effects of COVID-19 on 56 global stock indices from October 15, 2019 to August 7, 2020 by using a complex network method. Furthermore, the change of the network structure is analyzed in depth by dividing the stock markets into developed, emerging and frontier markets. The findings reveal a structural change in the form of node changes, reduced connectivity and significant differences in the topological characteristics of the network, due to COVID-19. A contagion effect is also identified in the network structure of emerging markets, with the nodes behaving synchronously. The findings also reveal substantial clustering and homogeneity in the world stock market network, based on geographic positioning. Besides, the number of positive correlations in the global stock indices increased during the outbreak. The stock markets of France and Germany seem to be the most relevant developed markets, while Taiwan and Slovenia have this relevance in emerging and frontier markets. The findings of this study help regulators and practitioners to design important strategies in the light of varying stock market dynamics during COVID-19.

We studied the cross-correlations in the daily closing prices of 181 stocks listed on the Pakistan stock exchange (PSX) covering a time period of 2007–2017 to compute the threshold networks and minimum spanning trees. In addition to the full sample analysis, our study uses three subsamples to examine the structural change and topological evolution before, during, and after the global financial crisis of 2008. We also apply Shannon entropy on the overall sample to measure the volatility of individual stocks. Our results find substantial clustering and a crisis-like less stable overall market structure, given the external and internal events of terrorism, political, financial, and economic crisis for Pakistan. The subsample results further reveal hierarchal scale-free structures and a reconfigured metastable market structure during a postcrisis period. In addition, time varying topological measures confirm the evidence of the presence of several star-like structures, the shrinkage of tree length due to crisis-related shocks, and an expansion in the recovery phase. Finally, changes of the central node of minimum spanning trees (MSTs), the volatile stock recognition using Shannon entropy, and the topology of threshold networks will help local and international investors of Pakistan Stock Exchange limited (PSX) to manage their portfolios or regulators to monitor the important nodes to achieve stability and to predict an upcoming crisis.

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This study analyzes the relationship between agricultural foreign direct investment (FDI) and food security on Belt and Road Initiative (BRI) countries in a panel framework over the period 2006–2015 using correlation analysis, the specific-effect model, and the 2SLS technique. The study aims to: first, analyze the correlation between agricultural FDI and food security for each country, individually; then, investigate whether there is a direct relationship, using the specific-effect model. Finally, by taking one step further, this study uses the 2SLS method to determine whether there is an indirect relationship through agricultural productivity. Our results show that the sampled countries have clear differences in the direction of the relationship between food security and agricultural FDI. But, in general, the agricultural FDI has a positive direct and indirect effect on food security; this effect is seen clearly when the country attracts agricultural FDIs steadily.

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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Purpose -the purpose of this study is to analyse the impact of the recent economic crisis on the network topology structure of Pakistan stock market. Since stock market is considered a core financial market for the development of an economy, it is often used as benchmark to measure a country`s progress. Policymakers often forecast tendency of share prices, that is dependent on several foreign and local macroeconomic factors. Therefore, the aim of this study is to investigate how rising inflation, higher interest rates, and trade and budgetary deficits affect the network structure of blue-chip 96 companies listed on the Karachi stock exchange (KSE-100) index of Pakistan stock market.Research methodology -this study follows the methodology proposed by Mantegna and Stanley and uses cross-correlation in the daily closing price of KSE 100 Index companies to compute Minimum spanning tree (MST) structures. Additionally, we also apply time-varying topological property of average tree length to extract dynamic features of the MST networks.Findings -we construct eight monthly MSTs that show the instability of the network structure and significant differences in the topological characteristics due to economic crisis of Pakistan. Furthermore, the time-varying topological property of average tree length reveals contraction of the networks due to tight correlation among stocks.Research limitations -this study focuses on correlation-based network construction of MST. The scope of the study can be widened by constructing partial correlation-based MSTs and comparison of different networks structures accordingly.Practical implications -the network properties and findings of this paper will help policymakers and regulators in setting right policies, regulatory framework, and risk management for the stock market.Originality/Value -no previous studies have performed MST based network analysis examining macroeconomic events. Therefore, we fill the research gap and thoroughly analyse structural change and dynamics of Pakistan stock market during the turbulence of current economic crisis of Pakistan.