Market microstructure, banks’ behaviour and interbank spreads: evidence after the crisis


We present a study of the European electronic interbank market of overnight lending (e-MID) before and after the beginning of the financial crisis. The main goal of the paper is to explain the structural changes of lending/borrowing features due to the liquidity turmoil. Unlike previous contributions that focused on banks’ dependent and macro information as explanatory variables, we address the role of banks’ behaviour and market microstructure as determinants of the credit spreads. We show that all banks experienced significant variations in their liquidity costs due to the sensitivity of interbank rates to the timing and side of trades. We argue that, while larger banks did experience better funding conditions after the crisis, this was not just a consequence of the “too big to fail” perception of the market. Larger banks have been able to play more strategically when managing their liquidity by taking advantage of the changing market microstructure.

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  1. 1.

    While our main cross-sectional regression results do not incorporate banks’ specific characteristics other than size and nationality, we perform an additional robustness check using a panel data model with time and bank fixed effects that can capture bank characteristics such as credit and liquidity risk.

  2. 2.

    Baglioni and Monticini (2013) use the main refinancing rate as reference. We choose to estimate the spread with respect to the average market rate so that the spread is not directly affected by official rates and monetary policy decisions.

  3. 3.

    Although the market is open 8 a.m.–6 p.m., in Fig. 4 we consider only the data 9 a.m.–5 p.m. because only in Greece and Portugal markets are open 8–9 a.m. and 5–6 p.m.

  4. 4.

    Temizsoy et al. (2015), performing link-level rather than bank-level regressions, and show that the effect of the microstructure variable is qualitatively the same also when controlling for the identity of the counterparty to a trade as well as when including indices of preferential lending and borrowing among the regression variables.


  1. Acharya VV, Merrouche O (2013) Precautionary hoarding of liquidity and inter-bank markets: evidence from the sub-prime crisis. Rev Finance 17(1):107–160

    Article  Google Scholar 

  2. Angelini P, Nobili A, Picillo C (2011) The interbank market after August 2007: what has changed and why? J Money Credit Bank 43(5):923–958

    Article  Google Scholar 

  3. Baglioni A, Monticini A (2008) The intraday price of money: evidence from the e-MID interbank market. J Money Credit Bank 40(7):1533–1540

    Article  Google Scholar 

  4. Baglioni A, Monticini A (2013) Why does the interest rate decline over the day? Evidence from the liquidity crisis. J Financ Serv Res 44(2):175–186

    Article  Google Scholar 

  5. Barucca P, Lillo F (2018) The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market. Comput Manag Sci 15(1):33–53

    Article  Google Scholar 

  6. Barucci E, Impenna C, Renò R (2004) The Italian overnight market: Microstructure effects, the martingale hypothesis and the payment system. In: Bagella M, Bechetti L, Hasan I, Hunter WC (eds) Monetary integration, markets and regulations—research in banking and finance, vol 4. Elsevier, Amsterdam, pp 319–360

    Google Scholar 

  7. Beaupain R, Durré A (2008) The interday and intraday patterns of the overnight market. Evidence from an electronic platform. European Central Bank Working Paper 988

  8. Beaver WH, Lambert RA, Morse D (1980) The information content of security prices. J Account Econ 2(1):3–28

    Article  Google Scholar 

  9. Berardi S, Tedeschi G (2017) From banks’ strategies to financial (in)stability. Int Rev Econ Finance 47:255–272

    Article  Google Scholar 

  10. Brousseau V, Manzanares A (2005) A look at intraday frictions in the Euro Area overnight deposit market. European Central Bank Working Paper 439

  11. Brunetti H, Harris JF, Mankad S, Michailidis G (2015) Interconnectedness in the interbank market. FEDS Working Paper 2015-090, SSRN 2674602

  12. Bushman RM, McDermott KE, Williams CD (2012) The earnings announcement premium and volume concentration. Kenan-Flagler Business School Working Paper, University of North Carolina at Chapel Hill

  13. Campbell JY (1993) Intertemporal asset pricing without consumption data. Am Econ Rev 83(3):487–512

    Google Scholar 

  14. Carletti E, Leonello A (2018) Credit market competition and liquidity crises. Rev. Finance. (In press)

    Article  Google Scholar 

  15. Cassola N, Holthausen C, Duca ML (2010) The 2007/2008 turmoil: a challenge for the integration of the Euro area money market. European Central Bank Working Paper

  16. Dagfinn R (2003) New electronic trading systems in the foreign exchange market. New Econ Handb I:471–504

    Google Scholar 

  17. Eisenschmidt J, Tapking J (2009) Liquidity risk premia in unsecured interbank money markets. European Central Bank Working Paper 1025

  18. European Central Bank (2012) Annual report, 2011.

  19. Finger K, Fricke D, Lux T (2013) Network analysis of the e-MID overnight money market: the informational value of different aggregation levels for intrinsic dynamic processes. Comput Manag Sci 10(2):187–2011

    Article  Google Scholar 

  20. Furfine CH (2000) Interbank payments and the daily federal funds rate. J Monet Econ 46(2):535–553

    Article  Google Scholar 

  21. Furfine CH (2001) Banks as monitors of other banks: evidence from the overnight federal funds market. J Bus 74(1):33–57

    Article  Google Scholar 

  22. Furfine CH (2002) The interbank market during a crisis. Eur Econ Rev 46(4–5):809–820

    Article  Google Scholar 

  23. Gabbi G (2005) Semi-correlations as a tool for geographical and sector asset allocation. Eur J Finance 11(3):271–281

    Article  Google Scholar 

  24. Gabrieli S (2012) Too-interconnected versus too-big-to-fail: banks’ network centrality and overnight interest rates. Banque de France Working Paper 398

  25. Galbiati M, Delpini D, Battiston S (2013) The power to control. Nat Phys 9(3):126–128

    Article  Google Scholar 

  26. Gale D, Yorulmazer T (2011) Liquidity hoarding. Federal Reserve Bank of New York Working Paper 488

  27. Gaspar V, Quiros GP, Mendizabal HR (2008) Interest rate dispersion and volatility in the market for daily funds. Eur Econ Rev 52(3):413–440

    Article  Google Scholar 

  28. George TJ, Kaul G, Nimalendran M (1991) Estimation of the bid-ask spread and its components: a new approach. Rev Financ Stud 4(4):623–656

    Article  Google Scholar 

  29. Hamilton J (1996) The daily market for federal funds. J Econ Dyn Control 104(1):26–56

    Google Scholar 

  30. Heider F, Hoerova M, Holthausen C (2015) Liquidity hoarding and interbank market spreads: the role of counterparty risk. J Financ Econ 118(2):336–354

    Article  Google Scholar 

  31. Hess AC, Frost PA (1982) Tests for price effects of new issues of seasoned securities. J Finance 37(1):11–25

    Article  Google Scholar 

  32. Iazzetta C, Manna M (2009) The topology of the interbank market: developments in Italy since 1990. Bank of Italy Working Paper 711

  33. Iori G, Renò R, de Masi G, Caldarelli G (2006) Trading strategies in the Italian interbank market. Phys A Stat Mech Appl 376(1):467–479

    Google Scholar 

  34. Iori G, De Masi G, Ovidiu VP, Gabbi G, Caldarelli G (2008) A network of the Italian overnight money market. J Econ Dyn Control 32(1):259–278

    Article  Google Scholar 

  35. Iori G, Mantegna RN, Marotta L, Micciché S, Porter J, Tumminello M (2015a) Networked relationships in the e-MID interbank market: a trading model with memory. J Econ Dyn Control 50(C):98–116

    Article  Google Scholar 

  36. Iori G, Kapar B, Olmo J (2015b) Bank characteristics and the interbank money market: a distributional approach. Stud Nonlinear Dyn Econom 19(3):249–283

    Google Scholar 

  37. Iori G, Politi M, Germano G, Gabbi G (2015c) Banks’ strategies and cost of money: effects of the financial crisis on the European electronic overnight interbank market. J Financ Manag Mark Inst 3(2):179–202

    Google Scholar 

  38. Karpoff JM (1987) The relation between price changes and trading volume: a survey. J Financ Quant Anal 22(1):109–126

    Article  Google Scholar 

  39. Kraus A, Stoll HR (1972) Price impacts of block trading on the New York Stock Exchange. J Finance 27(3):569–588

    Article  Google Scholar 

  40. Lamont O, Frazzini A (2007) The earnings announcement premium and trading volume. NBER Working Paper 13090

  41. Michaud F-L, Upper C (2008) What drives interbank rates? Evidence from the Libor panel. BIS Quarterly Review, March

  42. Rosu I (2009) A dynamic model of the limit order book. Rev Financ Stud 22(11):4601–4641

    Article  Google Scholar 

  43. Scholes MS (1972) The market for securities: substitution versus price pressure and the effects of information on share prices. J Bus 45(2):179–211

    Article  Google Scholar 

  44. Schwarz K (2018) Mind the gap: disentangling credit and liquidity in risk spreads. Working Paper, Wharton School

  45. Tedeschi G, Recchioni MC, Berardi S (2018) An approach to identifying micro behavior: how banks strategies influence financial cycles. J Econ Behav Organ. (in press)

    Article  Google Scholar 

  46. Temizsoy A, Iori G, Montes-Rojas G (2015) The role of bank relationships in the interbank market. J Econ Dyn Control 59:118–141

    Article  Google Scholar 

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Funding was provided by European Union (Grant No. 255987) and, for the Systemic Risk Centre, by the Economic and Social Research Council (ESRC, Grant No. ES/K002309/1).

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Correspondence to Giampaolo Gabbi.

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Regression results

Regression results

See Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 and 13.

Table 2 Descriptive statistics
Table 3 t-test p values for Table 2
Table 4 Pooled OLS results for borrowers
Table 5 Fixed-effect model for borrowers
Table 6 Pooled OLS results for different groups of borrowers
Table 7 Pooled OLS results for a.m./p.m. volume imbalance for borrowers
Table 8 Pooled OLS results for quoter/aggressor volume imbalance for borrowers
Table 9 Pooled OLS results for lenders
Table 10 Fixed-effect model results for lenders
Table 11 Pooled OLS results for different groups of lenders
Table 12 Pooled OLS results for a.m./p.m. volume imbalance ratio for lenders
Table 13 Pooled OLS results for quoter/aggressor volume imbalance for lenders

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Kapar, B., Iori, G., Gabbi, G. et al. Market microstructure, banks’ behaviour and interbank spreads: evidence after the crisis. J Econ Interact Coord 15, 283–331 (2020).

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  • Interbank lending
  • Market microstructure
  • Subprime crisis
  • Liquidity management