Syndication, interconnectedness, and systemic risk

Cai, Jian; Eidam, Frederik; Saunders, Anthony; Steffen, Sascha

doi:10.1016/j.jfs.2017.12.005

Cited by 202 publications

(121 citation statements)

References 61 publications

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“…In Caballero and Simsek (2013) fire sales of assets amplify contagion effects. 3 A rapidly growing finance l terature has focused on banking networks using data at bank-level, such as overnight interbank lending (Iori, De Masi, Precup, Gabbi, & Caldarelli, 2008), stable interbank lending (e.g., Craig & von Peter, 2014;Mistrulli, 2011), and syndicated loans (e.g., Cai et al, 2011;Hale, 2012;Godlewski et al, 2012). Unlike these papers, our network is at macrolevel and incorporates different economic sectors of the economy.…”

Section: Endnotesmentioning

confidence: 99%

Interconnectedness of the banking sector as a vulnerability to crises

2018

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This paper uses macro‐network to measure the interconnectedness of the banking sector and relates it to banking crises in Europe. Beyond cross‐border financial linkages of the banking sector, the macronetwork also accounts for financial linkages to the other main financial and nonfinancial sectors within the economy. We find that a more central position of the banking sector in the macronetwork significantly increases the probability of a banking crisis. By analysing the different types of risk exposures, our evidence shows that credit is an important source of vulnerability. Finally, our early‐warning models augmented with interconnectedness measures outperform traditional models in terms of out‐of‐sample predictions.

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Section: Endnotesmentioning

confidence: 99%

Interconnectedness of the banking sector as a vulnerability to crises

2018

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“…have portfolios that overlap only partly. This does not limit itself to liquid investments but also applies to longer term and less liquid exposures such as in the syndicated loan market (Cai et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Crowded Trades, Market Clustering, and Price Instability

et al. 2020

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Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock the clustering measure captures the degree of trading overlap among any two investors in that stock. We investigate the effect of crowded trades on stock price stability and show that market clustering has a causal effect on the properties of the tails of the stock return distribution, particularly the positive tail, even after controlling for commonly considered risk drivers. Reduced investor pool diversity could thus negatively affect stock price stability. source of price instability, but also a channel of volatility spillovers, eventually resulting in correlated price jumps. In that case, market clustering would foster systemic risks. Market clustering might be an example of an existing market structure that can amplify seemingly unimportant events into wide-spread market volatility. In case market clusters coincide with otherwise interconnected institutions, for example banks, common asset devaluation can be a crucial default contagion channel, as suggested in recent interdisciplinary research (Tsatskis, 2012;Glasserman and Young, 2016;Levy-Carciente et al., 2015).Market clustering is expected to cause price shocks, because it amplifies the effect of existing sources of price fluctuations. More specifically, market clustering is expected to increase the chance of price shocks in two different situations: Firstly, when the order deluge due to the group behaviour overwhelms the supply (Stein, 2009;Braun-Munzinger et al., 2018) and, secondly, when the supply is thin due to the homogeneity of the investors' pool, i.e. a lack of liquidity at one side of the order book (Weber and Rosenow, 2006). In both situations market clustering increases the chance that the demand exceeds the supply, either in buy or sell orders.We start our investigation of the influence of trading patterns by studying the relation between market clustering and the price dynamics of individual stocks. Our market clustering measure is unique in the sense that it quantifies two aspects of group behavior: clustering and crowdedness. We define price instability as an increase of the number of sharp price fluctuations, such that the tails of the log return distribution are heavier. Specifically, we investigate whether there is a causal relation between market clustering and the skewness, kurtosis, tail indices, positive and negative outlier counts, changes in downside risk and upside gains.The analysis of trading patterns depends on the ability to distinguish to what extent the patterns are the result of higher order features like group behaviour instead of lower order properties. In this research, we represent stock trading by a complex bipartite network (a two-layer network with non-trivial topological features). The two layers are the investors and the stocks. The links between the layers are the trades during a particular time period.We use the maxi...

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“…We identify lead arrangers using the "LeadArrangerCredit" field. When it is not available, we follow the methodology of Cai, Saunders, and Steffen (2011) to identify the lead arranger(s). 8 Our findings are similar when we use a sample of observations with nonmissing net notional values, implement a Tobit model where the left censoring point is zero, and estimate a two-stage least squares regression model.…”

Section: B Endogeneity Of Cds Insurancementioning

confidence: 99%

Credit Insurance, Distress Resolution Costs, and Bond Spreads

Narayanan¹,

Uzmanoglu

2018

Financial Management

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Credit default swaps (CDS) introduce friction in debt renegotiations as they alter the incentives of creditors insured with CDS to favor bankruptcy instead of restructuring debt out of court. Such renegotiation friction can increase bond spreads by increasing distress resolution costs. Alternatively, they can decrease bond spreads by deterring the firm from strategic default. Using newly available data on firm‐level CDS positions to proxy for the extent of CDS insurance, we find that bond spreads increase with CDS insurance. Additional tests indicate that this increase is associated with the effect CDS insurance has on increasing distress resolution costs. These results, which are robust to endogeneity concerns associated with CDS insurance, provide evidence that credit insurance can affect a firm's cost of debt.

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Syndication, interconnectedness, and systemic risk

Cited by 202 publications

References 61 publications

Interconnectedness of the banking sector as a vulnerability to crises

Interconnectedness of the banking sector as a vulnerability to crises

Crowded Trades, Market Clustering, and Price Instability

Credit Insurance, Distress Resolution Costs, and Bond Spreads

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