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Trading strategies in the overnight money market: Correlations and clustering on the e-MID trading platform

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  • Fricke, Daniel

Abstract

We analyze the correlations in patterns of trading for members of the Italian interbank trading platform e-MID. The trading strategy of a particular member institution is defined as the sequence of (intra-) daily net trading volumes within a certain semester. Based on this definition, we show that there are significant and persistent bilateral correlations between institutions’ trading strategies. In most semesters we find two clusters, with positively (negatively) correlated trading strategies within (between) clusters. We show that the two clusters mostly contain continuous net buyers and net sellers of money, respectively, and that cluster memberships of individual banks are highly persistent. Additionally, we highlight some problems related to our definition of trading strategies. Our findings add further evidence on the fact that preferential lending relationships on the micro-level lead to community structure on the macro-level.

Suggested Citation

  • Fricke, Daniel, 2012. "Trading strategies in the overnight money market: Correlations and clustering on the e-MID trading platform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6528-6542.
  • Handle: RePEc:eee:phsmap:v:391:y:2012:i:24:p:6528-6542
    DOI: 10.1016/j.physa.2012.07.045
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    References listed on IDEAS

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    6. Karl Finger & Daniel Fricke & Thomas Lux, 2013. "Network analysis of the e-MID overnight money market: the informational value of different aggregation levels for intrinsic dynamic processes," Computational Management Science, Springer, vol. 10(2), pages 187-211, June.
    7. Fricke, Daniel & Lux, Thomas, 2012. "Core-periphery structure in the overnight money market: Evidence from the e-MID trading platform," Kiel Working Papers 1759, Kiel Institute for the World Economy (IfW).
    8. Cocco, João F. & Gomes, Francisco J. & Martins, Nuno C., 2009. "Lending relationships in the interbank market," Journal of Financial Intermediation, Elsevier, vol. 18(1), pages 24-48, January.
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    Cited by:

    1. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Karl Finger & Daniel Fricke & Thomas Lux, 2013. "Network analysis of the e-MID overnight money market: the informational value of different aggregation levels for intrinsic dynamic processes," Computational Management Science, Springer, vol. 10(2), pages 187-211, June.
    3. Pecora, Nicolò & Spelta, Alessandro, 2015. "Shareholding relationships in the Euro Area banking market: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 1-12.
    4. Nicolò Pecora & Alessandro Spelta, 2016. "Discovering SIFIs in interbank communities," DISCE - Working Papers del Dipartimento di Economia e Finanza def037, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).

    More about this item

    Keywords

    Interbank market; Socio-economic networks; Community identification;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System

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