Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis

Clemente, Gian Paolo; Grassi, Rosanna; Pederzoli, Chiara

doi:10.1007/s11403-019-00247-4

Cited by 16 publications

(12 citation statements)

References 47 publications

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“…These results are interesting because the equity portfolios we analyzed in this study fall within the characteristic of overlapped portfolios, confirming the existence of a channel of contagion generated by the aggregate investment behavior of the entities belonging to the network. Similar results are showed by the network literature that study the effects of the interconnectedness of financial institutions and the propagation of shocks over the systemic risk of the financial market [40,41,45]. From a policy and regulator point of view, this evidence highlights that improving the knowledge of overlapping portfolios in emerging markets, is a fundamental element to a better understanding of the risks and magnitudes of financial and economic contagions with respect to the likelihood of their occurrence and extension, and their relation to the number and density of the connections within the financial system.…”

Section: Bipartite Networksupporting

confidence: 79%

Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach

2019

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This paper studies the topology of the Chilean mutual fund industry using networks methods. With the physical positions of the local equity portfolios managed during 2003.01-2017.4, we analyze their connectivity structure in both the mutual funds’ bipartite network and their one-mode projection. We estimate network measures to examine the potential effects on the topology arising from changes in the industrial environment and changes in the mutual funds’ investment strategies in their overlapped portfolios. Our main results show that changes in the bipartite network and its one-mode projection are correlated with variables related to funds’ investment strategies and with industry-specific variables. In consequence, these elements are a new potential of disturbance in the financial network conformed by stocks and mutual funds. We contribute to the existing literature, improving the understanding of the aggregate behavior of a financial sector which despite its economic importance has attracted little attention from a systemic risk perspective.

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Section: Bipartite Networksupporting

confidence: 79%

Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach

2019

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“…Clemente et al [38] have investigated the systemic risk in the European banking system from 2003 to 2017 using market data. e evidence of systemic risk via clustering coefficients indicating the strength of interconnectedness was found during the crisis.…”

Section: Literature Reviewmentioning

confidence: 99%

Systemic Risk Assessment: Aggregated and Disaggregated Analysis on Selected Indian Banks

et al. 2021

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Exposure of the banking system to the Global Financial Crisis attracted attention to the study of riskiness and spillover. This paper studies the pattern of systemic risk and size effect in the Indian banking sector. Based on market capitalization, three public sector banks and three from the private sector were taken. Data are taken from the year 2007 to 2020. The analysis is done through quantile- CoVaR (Conditional Value at Risk) and TENET (Tail-Event-Driven Network) measure. State variables like Indian market volatility and global risk measures negatively influence the Indian banks’ returns. Liquidity risk is a crucial aspect of private banks. Public banks experience public confidence even in the distress period. Large banks like HDFC and SBI bank offer the highest degree of systemic risk contribution. The role of private banks in transmitting systemic risk has been intensifying since 2015. Small-sized banks like PNB and BOB have become significant receivers and transmitters of risk.

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“…Whichever way this is modeled, either via (i) network theory tools, or (ii) balance sheet interconnectedness among agents, the interaction among market participants represents the channel to propagate/reduce financial friction. Following the network theory approach, the papers by De Masi and Ricchiuti (2019) and Clemente et al (2019) empirically analyze the impact that recognized episodes of systemic risk, such as the Lehman failure and the sovereign debt crisis, have on the network topology of the European Foreign Direct Investment (FDI), in the first paper, and the European banking system, in the second. Although the systems are very different, both papers use a common technique.…”

Section: Essays On Instability and Financementioning

confidence: 99%

Taming financial systemic risk: models, instruments and early warning indicators

Tedeschi

Caccioli

Recchioni

2019

J Econ Interact Coord

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In recent decades, most advanced and developing economies have suffered-or are still suffering-from profound and repeated crises. The literature has reflected on the determinants of these perturbations by placing particular emphasis on the malfunctioning of either the real or financial sphere of the economy. The main research question has been to understand whether it was the real economy that perturbed finance sectors or, alternatively, the financial/credit market that depressed real production. Whatever the direction of the causality nexus and, consequently the origin of the attack, with some studies identifying the direction from real markets to financial sectors (see Bernanke and Gertler 1989;Greenwald and Stiglitz 1993;Delli Gatti et al. 2012) and others reversing it (see Christiano and Ikeda 2011;Brunnermeier et al. 2012), what is certainly undoubted is the self-reinforcing interaction between the two sectors, which translates into booms followed by busts. In light of this, part of the literature has not focused as much on the origin of crises, but rather on the mechanisms of shock propagation. In this regard, many studies have shown that a combination of forces is needed to generate shock transmission. Specifically, the literature on contagion has shown that agents' interaction and the emerging network topology are key ingredients for the spread of systemic risk (see, for instance, Lux 2016; Lux and Montagna 2017). The interaction has in fact been recognized as generating two opposing effects: risk sharing, which decreases with connectivity, and systemic risk, which in contrast, increases with linkages (see, for instance, Allen and Gale 2000; Battiston et al.

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Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis

Cited by 16 publications

References 47 publications

Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach

Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach

Systemic Risk Assessment: Aggregated and Disaggregated Analysis on Selected Indian Banks

Taming financial systemic risk: models, instruments and early warning indicators

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