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Kuyyamudi C, Chakrabarti AS, Sinha S. Emergence of frustration signals systemic risk. Phys Rev E 2019; 99:052306. [PMID: 31212413 DOI: 10.1103/physreve.99.052306] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Indexed: 11/07/2022]
Abstract
We show that the emergence of systemic risk in complex systems can be understood from the evolution of functional networks representing interactions inferred from fluctuation correlations between macroscopic observables. Specifically, we analyze the long-term collective dynamics in the New York Stock Exchange, the largest financial market in the world, for almost a century and show that periods marked by systemic crisis are associated with emergence of frustration. This is indicated by the loss of structural balance in the networks of interaction between stocks. Moreover, the mesoscopic organization of the networks during these periods exhibits prominent core-periphery organization. This suggests an increased degree of coherence in the collective dynamics of the system, which is reinforced by our observation of the transition to delocalization in the dominant eigenmodes when the systemic risk builds up. While frustration has been associated with phase transitions in physical systems such as spin glasses, its role as a signal for systemic risk buildup leading to severe crisis as shown here provides a novel perspective into the dynamical processes leading to catastrophic failures in complex systems.
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Affiliation(s)
- Chandrashekar Kuyyamudi
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600113, India.,Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094, India
| | | | - Sitabhra Sinha
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600113, India.,Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094, India
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Challinor AJ, Adger WN, Benton TG, Conway D, Joshi M, Frame D. Transmission of climate risks across sectors and borders. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2018; 376:20170301. [PMID: 29712795 PMCID: PMC5938635 DOI: 10.1098/rsta.2017.0301] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/19/2018] [Indexed: 05/29/2023]
Abstract
Systemic climate risks, which result from the potential for cascading impacts through inter-related systems, pose particular challenges to risk assessment, especially when risks are transmitted across sectors and international boundaries. Most impacts of climate variability and change affect regions and jurisdictions in complex ways, and techniques for assessing this transmission of risk are still somewhat limited. Here, we begin to define new approaches to risk assessment that can account for transboundary and trans-sector risk transmission, by presenting: (i) a typology of risk transmission that distinguishes clearly the role of climate versus the role of the social and economic systems that distribute resources; (ii) a review of existing modelling, qualitative and systems-based methods of assessing risk and risk transmission; and (iii) case studies that examine risk transmission in human displacement, food, water and energy security. The case studies show that policies and institutions can attenuate risks significantly through cooperation that can be mutually beneficial to all parties. We conclude with some suggestions for assessment of complex risk transmission mechanisms: use of expert judgement; interactive scenario building; global systems science and big data; innovative use of climate and integrated assessment models; and methods to understand societal responses to climate risk. These approaches aim to inform both research and national-level risk assessment.
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Affiliation(s)
- Andy J Challinor
- School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
| | - W Neil Adger
- Geography, College of Life and Environmental Sciences, University of Exeter, Rennes Drive, Exeter EX4 4RJ, UK
| | - Tim G Benton
- School of Biology, University of Leeds, Leeds LS2 9JT, UK
| | - Declan Conway
- Grantham Research Institute on Climate Change and the Environment, London School of Economics, London WC2A 2AE, UK
| | - Manoj Joshi
- Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
| | - Dave Frame
- NZ Climate Change Research Institute, Victoria University, Wellington, PO Box 600, Wellington 6012, New Zealand
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Podobnik B, Horvatic D, Lipic T, Perc M, Buldú JM, Stanley HE. The cost of attack in competing networks. J R Soc Interface 2016; 12:rsif.2015.0770. [PMID: 26490628 DOI: 10.1098/rsif.2015.0770] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Real-world attacks can be interpreted as the result of competitive interactions between networks, ranging from predator-prey networks to networks of countries under economic sanctions. Although the purpose of an attack is to damage a target network, it also curtails the ability of the attacker, which must choose the duration and magnitude of an attack to avoid negative impacts on its own functioning. Nevertheless, despite the large number of studies on interconnected networks, the consequences of initiating an attack have never been studied. Here, we address this issue by introducing a model of network competition where a resilient network is willing to partially weaken its own resilience in order to more severely damage a less resilient competitor. The attacking network can take over the competitor's nodes after their long inactivity. However, owing to a feedback mechanism the takeovers weaken the resilience of the attacking network. We define a conservation law that relates the feedback mechanism to the resilience dynamics for two competing networks. Within this formalism, we determine the cost and optimal duration of an attack, allowing a network to evaluate the risk of initiating hostilities.
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Affiliation(s)
- B Podobnik
- Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia Zagreb School of Economics and Management, 10000 Zagreb, Croatia
| | - D Horvatic
- Faculty of Natural Sciences, University of Zagreb, 10000 Zagreb, Croatia
| | - T Lipic
- Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA Rudjer Boskovic Institute, Centre for Informatics and Computing, 10000 Zagreb, Croatia
| | - M Perc
- Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia Department of Physics, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - J M Buldú
- Center for Biomedical Technology (UPM), 28223 Pozuelo de Alarcón, Madrid, Spain Complex Systems Group, Rey Juan Carlos University, 28933 Móstoles, Madrid, Spain
| | - H E Stanley
- Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
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Heiberger RH. Collective attention and stock prices: evidence from Google Trends data on Standard and Poor's 100. PLoS One 2015; 10:e0135311. [PMID: 26258498 PMCID: PMC4530949 DOI: 10.1371/journal.pone.0135311] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Accepted: 07/20/2015] [Indexed: 11/19/2022] Open
Abstract
Today´s connected world allows people to gather information in shorter intervals than ever before, widely monitored by massive online data sources. As a dramatic economic event, recent financial crisis increased public interest for large companies considerably. In this paper, we exploit this change in information gathering behavior by utilizing Google query volumes as a "bad news" indicator for each corporation listed in the Standard and Poor´s 100 index. Our results provide not only an investment strategy that gains particularly in times of financial turmoil and extensive losses by other market participants, but reveal new sectoral patterns between mass online behavior and (bearish) stock market movements. Based on collective attention shifts in search queries for individual companies, hence, these findings can help to identify early warning signs of financial systemic risk. However, our disaggregated data also illustrate the need for further efforts to understand the influence of collective attention shifts on financial behavior in times of regular market activities with less tremendous changes in search volumes.
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van Santen RA. Grundprinzipien in der Katalyse: Wie entwickelt man einen Katalysator theoretisch? Angew Chem Int Ed Engl 2014. [DOI: 10.1002/ange.201310965] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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van Santen RA. Catalytic Paradigms: A Riddle and a Puzzle. Angew Chem Int Ed Engl 2014; 53:8618-20. [DOI: 10.1002/anie.201310965] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 03/27/2014] [Indexed: 11/12/2022]
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Shaw MW, Pautasso M. Networks and plant disease management: concepts and applications. ANNUAL REVIEW OF PHYTOPATHOLOGY 2014; 52:477-93. [PMID: 25001454 DOI: 10.1146/annurev-phyto-102313-050229] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
A network is a natural structure with which to describe many aspects of a plant pathosystem. The article seeks to set out in a nonmathematical way some of the network concepts that promise to be useful in managing plant disease. The field has been stimulated by developments designed to help understand and manage animal and human disease, and by technical infrastructures, such as the internet. It overlaps partly with landscape ecology. The study of networks has helped identify likely ways to reduce the flow of disease in traded plants, to find the best sites to monitor as warning sites for annually reinvading diseases, and to understand the fundamentals of how a pathogen spreads in different structures. A tension between the free flow of goods or species down communication channels and free flow of pathogens down the same pathways is highlighted.
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Affiliation(s)
- M W Shaw
- School of Agriculture, Policy and Development, University of Reading, Whiteknights, Reading RG6 6AR, United Kingdom;
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Loepfe L, Cabrales A, Sánchez A. Towards a proper assignment of systemic risk: the combined roles of network topology and shock characteristics. PLoS One 2013; 8:e77526. [PMID: 24147017 PMCID: PMC3798718 DOI: 10.1371/journal.pone.0077526] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Accepted: 09/12/2013] [Indexed: 11/18/2022] Open
Abstract
The 2007-2008 financial crisis solidified the consensus among policymakers that a macro-prudential approach to regulation and supervision should be adopted. The currently preferred policy option is the regulation of capital requirements, with the main focus on combating procyclicality and on identifying the banks that have a high systemic importance, those that are “too big to fail”. Here we argue that the concept of systemic risk should include the analysis of the system as a whole and we explore systematically the most important properties for policy purposes of networks topology on resistance to shocks. In a thorough study going from analytical models to empirical data, we show two sharp transitions from safe to risky regimes: 1) diversification becomes harmful with just a small fraction (~2%) of the shocks sampled from a fat tailed shock distributions and 2) when large shocks are present a critical link density exists where an effective giant cluster forms and most firms become vulnerable. This threshold depends on the network topology, especially on modularity. Firm size heterogeneity has important but diverse effects that are heavily dependent on shock characteristics. Similarly, degree heterogeneity increases vulnerability only when shocks are directed at the most connected firms. Furthermore, by studying the structure of the core of the transnational corporation network from real data, we show that its stability could be clearly increased by removing some of the links with highest centrality betweeness. Our results provide a novel insight and arguments for policy makers to focus surveillance on the connections between firms, in addition to capital requirements directed at the nodes.
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Affiliation(s)
- Lasse Loepfe
- Grupo Interdisciplinar de Sistemas Complejos, Departament of Mathematics, Universidad Carlos III de Madrid, Leganés, Madrid, Spain
- * E-mail:
| | - Antonio Cabrales
- Department of Economics, University College London, London, United Kingdom
| | - Angel Sánchez
- Grupo Interdisciplinar de Sistemas Complejos, Departament of Mathematics, Universidad Carlos III de Madrid, Leganés, Madrid, Spain
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Shadbolt N, Hall W, Hendler JA, Dutton WH. Web science: a new frontier. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2013; 371:20120512. [PMID: 23419857 PMCID: PMC3575572 DOI: 10.1098/rsta.2012.0512] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Affiliation(s)
- Nigel Shadbolt
- Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.
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