The Interbank Market after August 2007: What Has Changed, and Why?

Angelini, Paolo; Nobili, Andrea; Picillo, Cristina

doi:10.2139/ssrn.1601845

Cited by 105 publications

(46 citation statements)

References 131 publications

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“…During the 2007-2008 financial crisis though, liquidity in the interbank market has considerably dried up, even at short maturities, and an increasing dispersion in the credit conditions of different banks has emerged. A number of studies have investigated how movements in borrowing costs depend on bank specific characteristics such as their size and creditworthiness (1,2), or on banks ability to exploit changing market microstructure conditions (3).…”

Section: Introductionmentioning

confidence: 99%

Quantifying Preferential Trading in the e-MID Interbank Market

Hatzopoulos

Iori

Mantegna³

et al. 2013

SSRN Journal

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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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Section: Introductionmentioning

confidence: 99%

Quantifying Preferential Trading in the e-MID Interbank Market

Hatzopoulos

Iori

Mantegna³

et al. 2013

SSRN Journal

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“…This makes it impossible to match e-MID trading data with balance sheet or other banks' specific data. Other studies (see Angelini et al, 2011) Another key determinant of O/N rates is the time of a transaction. While Angelini (2000) using hourly e-MID data shows no intraday pattern of interest rates, Baglioni and Monticini (2008) and Gabbi et al (2012) find a decreasing trend in the O/N rate as the trading day progresses.…”

Section: Other Control Variablesmentioning

confidence: 99%

“…Previous empirical evidence (see Angelini et al (2011), Gabrieli (2011), Gabbi (2012, Bech and Atalay (2010), Akram and Christophersen (2010) and Gabrieli (2012)) suggests that being systemically more important, in term of size or connectedness, explains part of the cross-sectional variation in banks' borrowing costs before and during the 2008 global financial crisis. Our paper contributes to the recent literature that investigates the determinants of banks' borrowing costs in unsecured money markets and how network characteristics of interbank market participants affect their funding rates.…”

Section: Introductionmentioning

confidence: 98%

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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“…The recent literature highlights the role of liquidity and credit risks in explaining interbank spreads; see, for instance, Beirne (2012), Angelini, Nobili and Picillo (2011), Michaud and Upper (2008), Schwartz (2010), Eisenschmidt and Tapking (2009) and McAndrews, Sarkar and Wang (2017). Along these lines, we introduce a novel model in which interbank risk fluctuations are driven by expected and unexpected shocks.…”

Section: Second This Article Characterises Expected Fluctuations In mentioning

confidence: 99%

Dissecting Interbank Risk

et al. 2016

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This paper analyses interbank risk using the information content of basis swap (BS) spreads, floating-to-floating interest rate swaps whose payments are associated with euro deposit rates for alternative tenors. We propose an empirical model to decompose BS quotes into expected and unexpected components. To estimate both unobservable constituents of BS spreads, we solve a signal extraction problem using a particle filter. Our empirical findings show that unexpected changes of BS spreads are linked to systemic risk. Shocks to aggregate liquidity are also important to explain regime shifts. Sovereign risk and risk aversion are relevant factors explaining expected fluctuations.

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The Interbank Market after August 2007: What Has Changed, and Why?

Cited by 105 publications

References 131 publications

Quantifying Preferential Trading in the e-MID Interbank Market

Quantifying Preferential Trading in the e-MID Interbank Market

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

Dissecting Interbank Risk

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