The role of bank relationships in the interbank market

Temizsoy, Asena; Iori, Giulia; Montes‐Rojas, Gabriel

doi:10.1016/j.jedc.2015.07.008

Cited by 54 publications

(54 citation statements)

References 28 publications

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“…This feedback loop makes it difficult to establish the causality of the effect. Temizsoy et al (2015) shows that such feedback effects are small. Spreads do not determine survival of a bank pair into the following months once relationship indexes are controlled for, while relationship lending has an effect on spreads.…”

Section: Econometric Modelmentioning

confidence: 95%

“…In addition to the abrupt topological change after Lehman defaults, mostly driven by precautionary liquidity hoarding, Cocco et al (2009), Affinito (2012, Brauning and Fecht (2012) and Temizsoy et al (2015) have shown that banks relied more extensively on relationship lending during the crisis, with both lenders and borrowers benefiting from close relationship both in terms to access to liquidity and funding rates. Relationship lending thus plays a positive role for financial stability and provides a measure of the level of financial substitutability of banks in the interbank market.…”

Section: Network Centrality and Interbank Marketsmentioning

confidence: 99%

“…Further details about the sample are in Temizsoy et al (2015). Figure 1 plots the evolution of spreads in our sample.…”

Section: Interest Rate Spreadsmentioning

confidence: 99%

“…Gabbi et al (2012) and Temizsoy et al (2015) have shown that due to a bid-ask spread effect, better rates are obtained, both by lenders and borrowers, when they act as quoters rather than as aggressors. A credit institution that first comes to the market with a proposal to lend or borrow is called quoter, while the bank that picks a quote and exercises a proposal is called aggressor.…”

Section: Other Control Variablesmentioning

confidence: 99%

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Network centrality and funding rates in the e-MID interbank market

Temizsoy

Iori

Montes‐Rojas

2017

Journal of Financial Stability

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This paper empirically investigates the role of banks' network centrality in the interbank market on their funding rates. Specifically we analyze transaction data from the e-MID market, the only electronic interbank market in the Euro Area and US, over the period [2006][2007][2008][2009] that encompasses the global financial crisis. We show that interbank spreads are significantly affected by both local and global measures of connectedness. The effects of network centrality increased as the financial crisis evolved. Local measures show that having more links increases borrowing costs for borrowers and reduces premia for lenders. For global network centrality, borrowers receive a significant discount if they increase their intermediation activity and become more central, while lenders pay in general a premium (i.e. receive lower rates) for centrality. This provides evidence of the 'too-interconnected-to-fail' hypothesis.

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Section: Econometric Modelmentioning

confidence: 95%

Section: Network Centrality and Interbank Marketsmentioning

confidence: 99%

“…Further details about the sample are in Temizsoy et al (2015). Figure 1 plots the evolution of spreads in our sample.…”

Section: Interest Rate Spreadsmentioning

confidence: 99%

Section: Other Control Variablesmentioning

confidence: 99%

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Network centrality and funding rates in the e-MID interbank market

Temizsoy

Iori

Montes‐Rojas

2017

Journal of Financial Stability

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“…Using the same dataset, in ref. (37) no impact of relationship lending on rates is found before the financial crisis. During the crisis though, and in particular after the Lehman Brothers collapse in September 2008, having relationships benefited both lenders and borrowers.…”

Section: Introductionmentioning

confidence: 96%

Quantifying preferential trading in the e-MID interbank market

Hatzopoulos

Iori

Mantegna

et al. 2014

Quantitative Finance

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Interbank markets allow credit institutions to exchange capital for purposes of liquidity management. These markets are among the most liquid markets in the financial system. However, liquidity of interbank markets dropped during the 2007-2008 financial crisis, and such a lack of liquidity influenced the entire economic system. In this paper, we analyze transaction data from the e-MID market which is the only electronic interbank market in the Euro Area and US, over a period of eleven years (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)). We adapt a method developed to detect statistically validated links in a network, in order to reveal preferential trading in a directed network. Preferential trading between banks is detected by comparing empirically observed trading relationships with a null hypothesis that assumes random trading among banks doing a heterogeneous number of transactions. Preferential trading patterns are revealed at time windows of 3-maintenance periods. We show that preferential trading is observed throughout the whole period of analysis and that the number of preferential trading links does not show any significant trend in time, in spite of a decreasing trend in the number of pairs of banks making transactions. We observe that preferential trading connections typically involve large trading volumes. During the crisis, we also observe that transactions occurring between banks with a preferential connection occur at larger interest rates than the complement set -an effect that is not observed before the crisis. Permanent repository link

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Interbank borrowing and lending between financially constrained banks

Dietrich

Hauck

2019

Econ Theory

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Some stylized facts about transactions among banks are not easily reconciled with coinsurance of short-term liquidity risks. In our model, interbank markets play a different role. We argue that lending to another bank can reduce a bank's overall portfolio risk through diversification. If insolvency is costly, this diversification improves the interbank lender's funding liquidity, boosting credit supply to nonbanks. However, diversification comes at an endogenous cost that depends on bank-specific factors of interbank borrower and lender. The model provides a framework for understanding the importance of interbank lending for aggregate credit supply and the stability of banking systems. The model's predictions are consistent with evidence documented in the literature that other theories cannot consistently explain.

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The role of bank relationships in the interbank market

Cited by 54 publications

References 28 publications

Network centrality and funding rates in the e-MID interbank market

Network centrality and funding rates in the e-MID interbank market

Quantifying preferential trading in the e-MID interbank market

Interbank borrowing and lending between financially constrained banks

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