Stefano Battiston, Guido Caldarelli, Financial Networks, In: Networks of Networks: The Last Frontier of Complexity, Springer Verlag, Berlin, p. 311 - 321, 2014. (Book Chapter)
The financial system performs vital functions for the world economy. Very often one of more aspect of this system can be described by means of a complex graph. In this chapter under the generic name of financial networks we indicate several different systems all related to the world of finance. |
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James Glattfelder, Thomas Bisig, Richard Olsen, R&D Strategy Document, Version: 1, 2014. (Technical Report)
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Tarik Roukny, Co-Pierre George, Stefano Battiston, A Network Analysis of the Evolution of the German Interbank Market, In: Discussion Paper Deutsche Bundesbank, No. 22, 2014. (Working Paper)
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Nicolo Musmeci, Stefano Battiston, Michelangelo Puliga, Andrea Gabrielli, Bootstrapping topology and systemic risk of complex network using the fitness model, Journal of Statistical Physics, Vol. 151 (3-4), 2013. (Journal Article)
In this paper we present a novel method to reconstruct global topological properties of a complex network starting from limited information. We assume to know for all the nodes a non-topological quantity that we interpret as fitness. In contrast, we assume to know the degree, i.e. the number of connections, only for a subset of the nodes in the network. We then use a fitness model, calibrated on the subset of nodes for which degrees are known, in order to generate ensembles of networks. Here, we focus on topological properties that are relevant for processes of contagion and distress propagation in networks, i.e. network density and k-core structure, and we study how well these properties can be estimated as a function of the size of the subset of nodes utilized for the calibration. Finally, we also study how well the resilience to distress propagation in the network can be estimated using our method. We perform a first test on ensembles of synthetic networks generated with the Exponential Random Graph model, which allows to apply common tools from statistical mechanics. We then perform a second test on empirical networks taken from economic and financial contexts. In both cases, we find that a subset as small as 10 % of nodes can be enough to estimate the properties of the network along with its resilience with an error of 5 %. |
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Rahul Kaushik, Stefano Battiston, Credit default swaps drawup networks: Too interconnected to be stable?, PLoS ONE, Vol. 8 (7), 2013. (Journal Article)
We analyse time series of CDS spreads for a set of major US and European institutions in a period overlapping the recent financial crisis. We extend the existing methodology of -drawdowns to the one of joint -drawups, in order to estimate the conditional probabilities of spike-like co-movements among pairs of spreads. After correcting for randomness and finite size effects, we find that, depending on the period of time, 50% of the pairs or more exhibit high probabilities of joint drawups and the majority of spread series are trend-reinforced, i.e. drawups tend to be followed by drawups in the same series. We then carry out a network analysis by taking the probability of joint drawups as a proxy of financial dependencies among institutions. We introduce two novel centrality-like measures that offer insights on how both the systemic impact of each node as well as its vulnerability to other nodes' shocks evolve in time. |
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Marco Galbiati, Danilo Delpini, Stefano Battiston, The power to control, Nature Physics, Vol. 9 (3), 2013. (Journal Article)
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Danilo Delpini, Stefano Battiston, Massimo Riccaboni, Giampaolo Gabbi, Fabio Pammolli, Guido Caldarelli, Evolution of controllability in interbank networks, Scientific Reports, Vol. 3 (1626), 2013. (Journal Article)
The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected "hub" institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies. |
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Giovanni Di Iasio, Stefano Battiston, Luigi Infante, Federico Pierobon, Capital and contagion in financial networks, In: MPRA Paper, No. 52141, 2013. (Working Paper)
We implement a novel method to detect systemically important financial institutions in a network. The method consists in a simple model of distress and losses redistribution derived from the interaction of banks' balance-sheets through bilateral exposures. The algorithm goes beyond the traditional default-cascade mechanism, according to which contagion propagates only through banks that actually default. We argue that even in the absence of other defaults, distressed-but-non-defaulting institutions transmit the contagion through channels other than solvency: weakness in their balance sheet reduces the value of their liabilities, thereby negatively affecting their interbank lenders even before a credit event occurs. In this paper, we apply the methodology to a unique dataset covering bilateral exposures among all Italian banks in the period 2008-2012. We find that the systemic impact of individual banks has decreased over time since 2008. The result can be traced back to decreasing volumes in the interbank market and to an intense recapitalization process. We show that the marginal effect of a bank's capital on its contribution to systemic risk in the network is considerably larger when interconnectedness is high (good times): this finding supports the regulatory work on counter-cyclical (macroprudential) capital buffers. |
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Stefano Battiston, Guido Caldarelli, Co-Pierre Georg, Robert May, Joseph Stiglitz, Complex derivatives, Nature Physics, Vol. 9 (3), 2013. (Journal Article)
The intrinsic complexity of the financial derivatives market has emerged as both an incentive to engage in it, and a key source of its inherent instability. Regulators now faced with the challenge of taming this beast may find inspiration in the budding science of complex systems. |
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James Glattfelder, Decoding Complexity: Uncovering Patterns in Economic Networks: Doctoral Thesis accepted by Swiss Federal Institute of Technology (ETH) Zurich, Switzerland, Springer, Heidelberg, 2013. (Book/Research Monograph)
Today it appears that we understand more about the universe than about our interconnected socio-economic world. In order to uncover organizational structures and novel features in these systems, we present the first comprehensive complex systems analysis of real-world ownership networks. This effort lies at the interface between the realms of economics and the emerging field loosely referred to as complexity science. The structure of global economic power is reflected in the network of ownership ties of companies and the analysis of such ownership networks has possible implications for market competition and financial stability. Thus this work presents powerful new tools for the study of economic and corporate networks that are only just beginning to attract the attention of scholars. |
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Stefano Battiston, Guido Caldarelli, Systemic Risk in Financial Networks, Journal of Financial Management, Markets and Institutions, Vol. 1 (2), 2013. (Journal Article)
Financial inter-linkages play an important role in the emergence of financial instabilities and the formulation of systemic risk can greatly benefit from a network approach. In this paper, we focus on the role of linkages along the two dimensions of contagion and liquidity, and we discuss some insights that have recently emerged from network models. With respect to the issue of the determination of the optimal architecture of the financial system, models suggest that regulators have to look at the interplay of network topology, capital requirements, and market liquidity. With respect to the issue of the determination of systemically important financial institutions the findings indicate that both from the point of view of contagion and from the point of view of liquidity provision, there is more to systemic importance than just size. In particular for contagion, the position of institutions in the network matters and their impact can be computed through stress tests even when there are no defaults in the system.topology, capital requirements, and market liquidity. With respect to the issue of the determination of systemically important financial institutions the findings indicate that both from the point of view of contagion and from the point of view of liquidity provision, there is more to systemic importance than just size. In particular for contagion, the position of institutions in the network matters and their impact can be computed through stress tests even when there are no defaults in the system. |
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Tarik Roukny, Hugues Bersini, Hugues Pirotte, Guido Caldarelli, Stefano Battiston, Default cascades in complex networks: topology and systemic risk, Scientific Reports, Vol. 3 (2759), 2013. (Journal Article)
The recent crisis has brought to the fore a crucial question that remains still open: what would be the optimal architecture of financial systems? We investigate the stability of several benchmark topologies in a simple default cascading dynamics in bank networks. We analyze the interplay of several crucial drivers, i.e., network topology, banks' capital ratios, market illiquidity, and random vs targeted shocks. We find that, in general, topology matters only--but substantially--when the market is illiquid. No single topology is always superior to others. In particular, scale-free networks can be both more robust and more fragile than homogeneous architectures. This finding has important policy implications. We also apply our methodology to a comprehensive dataset of an interbank market from 1999 to 2011. |
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Stefano Battiston, Domenico Delli Gatti, Mauro Gallegati, Bruce Greenwald, Joseph E Stiglitz, Credit Default Cascades: When Does Risk Diversification Increase Stability?, Journal of Financial Stability, Vol. 8 (3), 2012. (Journal Article)
We explore the dynamics of default cascades in a network of credit interlink-ages in which each agent is at the same time a borrower and a lender. When some counterparties of an agent default, the loss she experiences amounts to her total exposure to those counterparties. A possible conjecture in this context is that individual risk diversification across more numerous counterparties should make also systemic defaults less likely. We show that this view is not always true. In particular, the diversification of credit risk across many borrowers has ambiguous effects on systemic risk in the presence of mechanisms of loss amplifications such as in the presence of potential runs among the short-term lenders of the agents in the network. |
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Stefano Battiston, Domenico Delli Gatti, Mauro Gallegati, Bruce Greenwald, Joseph E Stiglitz, Liaisons Dangereuses: Increasing Connectivity, Risk Sharing, and Systemic Risk, Journal of Economic Dynamics and Control, Vol. 36 (8), 2012. (Journal Article)
The recent financial crisis poses the challenge to understand how systemic risk arises endogenously and what architecture can make the financial system more resilient to global crises. This paper shows that a financial network can be most resilient for intermediate levels of risk diversification, and not when this is maximal, as generally thought so far. This finding holds in the presence of the financial accelerator, i.e. when negative variations in the financial robustness of an agent tend to persist in time because they have adverse effects on the agent's subsequent performance through the reaction of the agent's counterparties. |
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Stefano Battiston, I Bordino, G Caldarelli, M Cristelli, A Ukkonen, I Weber, Web Search Queries Can Predict Stock Market Volumes, PLoS ONE, Vol. 7 (7), 2012. (Journal Article)
We live in a computerized and networked society where many of our actions leave a digital trace and affect other people’s actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www. |
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James Glattfelder, Decoding Complexity: The Organizing Principles Behind our Economy, In: The Montréal Review, p. online, 1 April 2012. (Newspaper Article)
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Stefano Battiston, M Puliga, R Kaushik, P Tasca, G Caldarelli, DebtRank: Too Central to Fail? Financial Networks, the FED and Systemic Risk, Scientific Reports, Vol. 2, 2012. (Journal Article)
Systemic risk, here meant as the risk of default of a large portion of the financial system, depends on the network of financial exposures among institutions. However, there is no widely accepted methodology to determine the systemically important nodes in a network. To fill this gap, we introduce, DebtRank, a novel measure of systemic impact inspired by feedback-centrality. As an application, we analyse a new and unique dataset on the USD 1.2 trillion FED emergency loans program to global financial institutions during 2008–2010. We find that a group of 22 institutions, which received most of the funds, form a strongly connected graph where each of the nodes becomes systemically important at the peak of the crisis. Moreover, a systemic default could have been triggered even by small dispersed shocks. The results suggest that the debate on too-big-to-fail institutions should include the even more serious issue of too-central-to-fail. |
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Stefano Battiston, F E Walter, M Yildirim, F Schweitzer, Moving recommender systems from on-line commerce to retail stores, Information Systems and e-Business Management, Vol. 10 (3), 2012. (Journal Article)
The increasing diversity of consumers’ demand, as documented by the debate on the long tail of the distribution of sales volume across products, represents a challenge for retail stores. Recommender systems offer a tool to cope with this challenge. The recent developments in information technology and ubiquitous computing makes it feasible to move recommender systems from the on-line commerce, where they are widely used, to retail stores. In this paper, we aim to bridge the management literature and the computer science literature by analysing a number of issues that arise when applying recommender systems to retail stores: these range from the format of the stores that would benefit most from recommender systems to the impact of coverage and control of recommender systems on customer loyalty and competition among retail stores. |
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Stefano Battiston, Michael D König, M Napoletano, F Schweitzer, The efficiency and stability of R&D networks, Games and Economic Behavior, Vol. 75 (2), 2012. (Journal Article)
We investigate the efficiency and stability of R&D networks in a model with network-dependent indirect spillovers. We show that the efficient network structure critically depends on the marginal cost of R&D collaborations. When the marginal cost is low, the complete graph is efficient, while high marginal costs imply that the efficient network is asymmetric and has a nested structure. Regarding the stability of network structures, we show the existence of both symmetric and asymmetric equilibria. The efficient network is stable for small industry size and small cost. In contrast, for large industry size, there is a wide region of cost in which the efficient network is not stable. This implies a divergence between efficiency and stability in large industries. |
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Stefano Battiston, S Cincotti, D Sornette, P Treleaven, G Caldarelli, C Hommes, A Kirman, An economic and financial exploratory, European Physical Journal. Special Topics, Vol. 214 (1), 2012. (Journal Article)
This paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs. |
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