The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions,elevating systemic risk in financial networks.Therefore,developing strategies to alleviate this risk,with a focus ...The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions,elevating systemic risk in financial networks.Therefore,developing strategies to alleviate this risk,with a focus on non-performing assets,has become a research area of interest.Supported by policies related to the Chinese insurance market,this study proposes the establishment of a non-performing assets disposal fund backed by insurance capital.This fund will invest in the non-performing assets of financial institutions with the aim of mitigating systemic risk.Using a linear threshold model,we identify an asymptotically optimal scheme for disposing of nonperforming assets.Additionally,we construct a payment model integrated with nonperforming assets,from which we derive an optimal payment and clearing strategy.Our research also proposes a robust set of criteria to assist regulators in determining whether to use the non-performing assets disposal fund.To demonstrate the efficacy of the fund in reducing systemic risk,we conduct simulations and analyze data from the Chinese interbank financial network.Through this rigorous analysis,we confirm the role of the fund in enhancing the stability of the financial system.展开更多
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 interconnecte...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.展开更多
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...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.展开更多
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 nonlin...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.展开更多
The study of dynamic networks in computer science has become crucial, given their ever-evolving nature within digital ecosystems. These networks serve as fundamental models for various networked systems, usually chara...The study of dynamic networks in computer science has become crucial, given their ever-evolving nature within digital ecosystems. These networks serve as fundamental models for various networked systems, usually characterized by modular structures. Understanding these structures, also known as communities, and the mechanisms driving their evolution is vital, as changes in one module can impact the entire network. Traditional static network analysis falls short of capturing the full complexity of dynamic networks, prompting a shift toward understanding the underlying mechanisms driving their evolution. Graph Evolution Rules (GERs) have emerged as a promising approach, explaining how subgraphs transform into new configurations. In this paper, we comprehensively explore GERs in dynamic networks from diverse systems with a focus on the rules characterizing the formation and evolution of their modular structures, using EvoMine for GER extraction and the Leiden algorithm for community detection. We characterize network and module evolution through GER profiles, enabling cross-system comparisons. By combining GERs and network communities, we decompose network evolution into regions to uncover insights into global and mesoscopic network evolution patterns. From a mesoscopic standpoint, the evolution patterns characterizing communities emphasize a non-homogeneous nature, with each community, or groups of them, displaying specific evolution patterns, while other networks’ communities follow more uniform evolution patterns. Additionally, closely interconnected sets of communities tend to evolve similarly. Our findings offer valuable insights into the intricate mechanisms governing the growth and development of dynamic networks and their communities, shedding light on the interplay between modular structures and evolving network dynamics.展开更多
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 us...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.展开更多
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 ban...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.展开更多
基金supported by the National Social Science Fund of China(No.22BTJ027).
文摘The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions,elevating systemic risk in financial networks.Therefore,developing strategies to alleviate this risk,with a focus on non-performing assets,has become a research area of interest.Supported by policies related to the Chinese insurance market,this study proposes the establishment of a non-performing assets disposal fund backed by insurance capital.This fund will invest in the non-performing assets of financial institutions with the aim of mitigating systemic risk.Using a linear threshold model,we identify an asymptotically optimal scheme for disposing of nonperforming assets.Additionally,we construct a payment model integrated with nonperforming assets,from which we derive an optimal payment and clearing strategy.Our research also proposes a robust set of criteria to assist regulators in determining whether to use the non-performing assets disposal fund.To demonstrate the efficacy of the fund in reducing systemic risk,we conduct simulations and analyze data from the Chinese interbank financial network.Through this rigorous analysis,we confirm the role of the fund in enhancing the stability of the financial system.
基金This research was partially supported by Department of informatics,Faculty of Economics,Business Administration and Information Technology,University of Zurich.
文摘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.
文摘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.
基金Supported by the National Natural Science Foundation of China(No.11271221)
文摘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.
基金supported by the Italian Ministry of University and Research(MUR)and the European Union–NextGenerationEU in the framework of the PRIN 2022 project“AWESOME:Analysis framework for WEb3 SOcial MEdia”–CUP:I53D23003680006.
文摘The study of dynamic networks in computer science has become crucial, given their ever-evolving nature within digital ecosystems. These networks serve as fundamental models for various networked systems, usually characterized by modular structures. Understanding these structures, also known as communities, and the mechanisms driving their evolution is vital, as changes in one module can impact the entire network. Traditional static network analysis falls short of capturing the full complexity of dynamic networks, prompting a shift toward understanding the underlying mechanisms driving their evolution. Graph Evolution Rules (GERs) have emerged as a promising approach, explaining how subgraphs transform into new configurations. In this paper, we comprehensively explore GERs in dynamic networks from diverse systems with a focus on the rules characterizing the formation and evolution of their modular structures, using EvoMine for GER extraction and the Leiden algorithm for community detection. We characterize network and module evolution through GER profiles, enabling cross-system comparisons. By combining GERs and network communities, we decompose network evolution into regions to uncover insights into global and mesoscopic network evolution patterns. From a mesoscopic standpoint, the evolution patterns characterizing communities emphasize a non-homogeneous nature, with each community, or groups of them, displaying specific evolution patterns, while other networks’ communities follow more uniform evolution patterns. Additionally, closely interconnected sets of communities tend to evolve similarly. Our findings offer valuable insights into the intricate mechanisms governing the growth and development of dynamic networks and their communities, shedding light on the interplay between modular structures and evolving network dynamics.
基金supported by the National Natural Science Foundation of China(Grant nos.72271087,71871088 and 71971079)National Social Science Foundation of China(21ZDA114)+1 种基金Hunan Provincial Natural Science Foundation of China(21JJ20019)the Huxiang Youth Talent Support Program.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant nos.71871088 and 71971079 and 71850006)the National Social Science Foundation of China(Grant No.21ZDA114)the Hunan Provincial Natural Science Foundation of China(Grant No.21J20019).and the Huxiang Youth Talent Support Program,China.
文摘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.
