A Note on Economic Equilibrium and Financial Networks

Nagurney （1999） used variational inequalities to study economic equilibrium and financial networks and applied the modified projection method to solve the problem. In this paper, we formulate the problem as a nonlinear complementarity problem. The complementarity model is just the KKT condition for the model of Nagurney （1999）. It is a simpler model than that of Nagurney （1999）. We also establish sufficient conditions for existence and uniqueness of the equilibrium pattern, which are weaker than those in Nagurney （]999）. Finally, we apply a smoothing Newton-type algorithm to solve the problem and report some numerical results.

The joint impact of bankruptcy costs, fire sales and cross-holdings on systemic risk in financial networks

The paper presents a comprehensive model of a banking system that integrates network effects,bankruptcy costs,fire sales,and cross-holdings.For the integrated financial market we prove the existence of a price-payment equilibrium and design an algorithm for the computation of the greatest and the least equilibrium.The number of defaults corresponding to the greatest price-payment equilibrium is analyzed in several comparative case studies.These illustrate the individual and joint impact of interbank liabilities,bankruptcy costs,fire sales and cross-holdings on systemic risk.We study policy implications and regulatory instruments,including central bank guarantees and quantitative easing,the significance of last wills of financial institutions,and capital requirements.

Systemic risk management and investment analysis with financial network analytics:research opportunities and challenges

Recent economic crises like the 2008 financial tsunami has demonstrated a critical need for better understanding of the topologies and various economic,social,and technical mechanisms of the increasingly interconnected global financial system.Such a system largely relies on the interconnectedness of various financial entities such as banks,firms,and investors through complex financial relationships such as interbank payment networks,investment relations,or supply chains.A network-based perspective or approach is needed to study various financial networks in order to improve or extend financial theories,as well as develop business applications.Moreover,with the advance of big data related technologies,and the availability of huge amounts of financial and economic network data,advanced computing technologies and data analytics that can comprehend such big data are also needed.We referred this approach as financial network analytics.We suggest that it will enable stakeholders better understand the network dynamics within the interconnected global financial system and help designing financial policies such as managing and monitoring banking systemic risk,as well as developing intelligent business applications like banking advisory systems.In this paper,we review the existing research about financial network analytics and then discuss its main research challenges from the economic,social,and technological perspectives.

Portfolio optimization based on network centralities:Which centrality is better for asset selection during global crises?

We construct correlation-based networks linking 86 assets(stock indices,bond indices,foreign exchange rates,commodity futures,and cryptocurrencies)and analyze the impact of asset selection on portfolio optimization using different centrality measures(including degree,eigenvector,eccentricity,betweenness,PageRank,and hybrid centralities).In times of a global crisis,peripheral assets located in cross-market networks are more suitable for investment.By comparing portfolio performance based on different centrality measures,we find that(i)hybrid,eigenvector,and PageRank centralities can best improve portfolio performance;(ii)degree centrality is suitable for larger portfolios;and(iii)eccentricity and betweenness centralities are unsuitable for network optimization portfolios.In response,we explain them based on the construction principle of centrality measures.Additionally,our optimal portfolios suggest that investors pay more attention to the role of emerging countries,which are less exposed to external shocks and whose financial markets are more likely to remain stable.

Measuring the importance of RMB in the exchange rate spill-over networks: new indices of RMB internationalisation

Using an innovative network approach,this study constructs new indices of the renminbi(RMB)internationalisation and presents strong evidence of the RMB’s growing influence globally and regionally.We identify networks of exchange rate spill-overs and examine time-varying spill-over intensities among the RMB and world major currencies of G20 members as well as currencies related to the Belt and Road Initiative(BRI).Shocks from the RMB generate intensifying spill-overs across currency networks.The role of the RMB in the networks has increased steadily over time.Our findings highlight that the RMB has become increasingly important since China has initiated the marketisation reform of its currency and proposed to build the modern Belt and Road.

Connectedness and systemic risk of the banking industry along the Belt and Road

This paper adopts the tail-event driven network(TENET)framework to explore the connectedness and systemic risk of the banking industry along the Belt and Road(B&R)based on weekly returns of 377 publicly-listed banks from 2014 to 2019.We conduct the connectedness analysis from four levels(i.e.,system,region,country and institution)and identify the systemic risk contribution of banks.We find that the dynamic total connectedness reached its peak during the outbreak of the abnormal fluctuations of Chinese stock market in 2015-2016 and its trough during the Brexit vote,and subsequently experienced several periodic fluctuations at a relatively high position.In the B&R banking system,the intra-regional tail risk spillovers are remarkably stronger than the inter-regional tail risk spillovers during the post-crisis period.In addition,the panel regressions estimated by the least squares dummy variable model show that the cross-border merger and acquisitions(M&As)and the merchandise trade export are important drivers for the tail-connectedness across the B&R countries.Our study provides regulators with insightful implications on the systemic risk supervision of the B&R banking industry.