The Impact Of Economic And Non-economic Events On Network Structures And Dynamics Of Stock Markets

Networks are usual exhibiting tools of representing movement of people and their economic activities.Most real-world systems can be mapped as networks,that is pair wise relationship among substances from a certain collection.Naming a few networks are social networks,transport networks,biological networks,financial networks and political networks.Stock market is regarded as a complex system,where relationship among various stocks represents an intricate relationship.However,in complex systems the system comprises of non-linear interacting elements and commonly found all around us.In the last decade,many approaches have been proposed to the understanding,one of the most interesting being the complex network perspective.The aim of this dissertation is therefore to extend financial network literature by applying complex network methods and network topology measures to study the impact of various key events on the state,structure,and dynamics of stock markets.In fulfilment of the objective,the research evaluates two stock markets,from a developed country such as the London Stock Exchange,and a developing country namely the Pakistan stock exchange.The dissertation is organized in eight chapters.The initial chapters(1,2)both introduce background knowledge,research objectives,research significance,state of the art,and hypothesis development.Chapter three contains the methodology of constructing stock market network through network based methods such as: the Minimum spanning tree(MST),Threshold network(CT),and crucial network measures such as: normalized tree length(NTL),average path length(APL),modularity,diameter,along with various centrality measures used to examine the connectivity and sparsity of the network structures.Later four essays in chapters(4,5,6,7)are solely focused to empirically test the stated hypothesis by constructing stock market networks around the key economic and non-economic events,and applying network topology measures.These chapters present exclusive analysis and extends financial network literature.In the end,the summary,implications,and main conclusion will end this dissertation in Chapter 8.The main findings of this dissertation are as follows.First,the structures of FTSE 100 index show formation of two major clusters belonging to financials,and consumer services sectors,highlighting the reliance of British economy in these two sectors.The pre-Brexit referendum period tree demonstrates a less stable structure as compared to post-referendum period,and risk of affecting the Minimum spanning tree(MST)structure in the post referendum period is lower.The results further show astonishing impact in form of expansion of the tree structure after political event of Brexit.Therefore,the results support a positive impact of Brexit on FTSE 100 index companies.Second,the results show a star-like structure after the general elections of 2018 and before those in 2008,and a tree-like structure otherwise for Pakistan stock market.In addition,the sectorial centrality measures reveal economic expansion in three industrial sectors—cement,oil and gas,and fertilizers around political event of general elections of Pakistan.Moreover,a strong overall intermediary role of the fertilizer sector is observed.These results indicate a structural change in the Pakistan stock market network due to general elections.Third,the results observe 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 sub-sample results further reveal hierarchal scale-free structures and a reconfigured meta stable market structure during the post Global financial crisis 2008 period.In addition,time varying topological measures confirm the evidence of the presence of several star-like structures,shrinkage of tree length due to crisis-related shocks,and expansion in the recovery phase.Finally,the results demonstrate instability of the network structure and significant differences in the topological characteristics due to economic crisis of Pakistan.In addition,stocks from same economic sector do not tend to cluster but connect mostly with stocks of other industry sectors.Which is a reflection of different reactions of the stock market participants to the risks posed by negative macroeconomic factors inform of rapid increase in the inflation level on monthly basis,rupee depreciation,and depleting foreign exchange reserves of Pakistan.Furthermore,time varying topological property of average tree length reveals contraction of the networks due to tight correlation among stocks.Hence,these results indicate a substantial impact on the network structures of stock markets due to economic and non-economic events.Network analysis of Pakistan and London stock exchange will assist local and international investors in forming effective portfolio strategies.In addition,this dissertation will form a comparative network technique by proposing network-based methods to analyze the impact of economic and non-economic events on stock markets and suggests implications and effectiveness of the network.The comparative network approach will serve as useful tool for policymakers and regulators as they assess market stability,and formulate economic policies.