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

  • Fricke, Daniel

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.

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File URL: http://www.sciencedirect.com/science/article/pii/S0378437112007145
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Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 391 (2012)
Issue (Month): 24 ()
Pages: 6528-6542

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Handle: RePEc:eee:phsmap:v:391:y:2012:i:24:p:6528-6542
Contact details of provider: Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

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  1. Livan, Giacomo & Alfarano, Simone & Scalas, Enrico, 2011. "The fine structure of spectral properties for random correlation matrices: an application to financial markets," MPRA Paper 28964, University Library of Munich, Germany.
  2. Thomas Lux, Daniel Fricke, 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.
  3. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "Network topology of the interbank market," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 677-684.
  4. G. De Masi & G. Iori & G. Caldarelli, 2006. "A fitness model for the Italian Interbank Money Market," Papers physics/0610108, arXiv.org.
  5. 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.
  6. Iori, G. & Masi, G. D. & Precup, O. V. & Gabbi, G. & Caldarelli, G., 2005. "A network analysis of the Italian oversight money market," Working Papers 05/05, Department of Economics, City University London.
  7. Ilija I. Zovko & J. Doyne Farmer, 2007. "Correlations and clustering in the trading of members of the London Stock Exchange," Papers 0709.3261, arXiv.org.
  8. F. Kyriakopoulos & S. Thurner & C. Puhr & S. W. Schmitz, 2009. "Network and eigenvalue analysis of financial transaction networks," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 71(4), pages 523-531, October.
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