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Informed Trading in the Euro Money Market for Term Lending

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  • Paolo Zagaglia

    (Sveriges Riksbank (Modelling Division); Università di Bologna (Dipartimento di Scienze Economiche); Rimini Centre for Economic Analysis)

Abstract

I address the role of information heterogeneity in the Euro interbank market for unsecured term lending. I use high-frequency quotes of bid and ask prices to estimate probabilities of informed trading for contract maturities from one month to one year. The dataset spans from November 2000 to March 2008, and includes the relevant events that characterize the developments of the Euro area money market. I obtain four main results. First, I show that the loose supply of liquidity of the ECB has not dampened the distortions arising from asymmetric information in the unsecured money market. I also find that the probability of trading with a better informed bank is higher on days when open market operations take place, and at the end of the maintenance period. This effect has strengthened during the turmoil. The results indicate that information is segmented, in the sense that heterogenous knowledge among banks is maturity-specific. Finally, the paper presents some evidence suggesting that the risk of trading with a counterparty that enjoys an enhanced information set is priced.

Suggested Citation

  • Paolo Zagaglia, 2010. "Informed Trading in the Euro Money Market for Term Lending," Working Paper series 02_10, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:02_10
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    References listed on IDEAS

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    1. Alain Durré & Stefano Nardelli, 2008. "Volatility in the Euro area money market: effects from the monetary policy operational framework," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(4), pages 307-322.
    2. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    3. R. Baupain & A. Durre, 2007. "The interday and intraday patterns of the overnight market : evidence from an electronic platform," Post-Print hal-00300195, HAL.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Nuno Cassola & Claudio Morana, 2006. "Volatility of interest rates in the euro area: Evidence from high frequency data," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 513-528.
    6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    7. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    8. Angelo Baglioni & Andrea Monticini, 2008. "The Intraday Price of Money: Evidence from the e‐MID Interbank Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1533-1540, October.
    9. Bierens, Herman J., 1997. "Testing the unit root with drift hypothesis against nonlinear trend stationarity, with an application to the US price level and interest rate," Journal of Econometrics, Elsevier, vol. 81(1), pages 29-64, November.
    10. Francisco Alonso & Roberto Blanco, 2005. "Is the volatility of the EONIA transmitted to longer-term euro money market interest rates?," Working Papers 0541, Banco de España.
    11. Bierens, Herman J., 1997. "Nonparametric cointegration analysis," Journal of Econometrics, Elsevier, vol. 77(2), pages 379-404, April.
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    Cited by:

    1. Caterina Liberati & Massimiliano Marzo & Paolo Zagaglia & Paola Zappa, 2012. "Structural Distortions in the Euro Interbank Market: The Role of 'Key Players' during the Recent Market Turmoil," Working Paper series 57_12, Rimini Centre for Economic Analysis.

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    More about this item

    Keywords

    Market microstructure; PIN model; money markets; term structure;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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