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Extracting the multi-timescale activity patterns of online financial markets

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  • Teruyoshi Kobayashi
  • Anna Sapienza
  • Emilio Ferrara

Abstract

Online financial markets can be represented as complex systems where trading dynamics can be captured and characterized at different resolutions and time scales. In this work, we develop a methodology based on non-negative tensor factorization (NTF) aimed at extracting and revealing the multi-timescale trading dynamics governing online financial systems. We demonstrate the advantage of our strategy first using synthetic data, and then on real-world data capturing all interbank transactions (over a million) occurred in an Italian online financial market (e-MID) between 2001 and 2015. Our results demonstrate how NTF can uncover hidden activity patterns that characterize groups of banks exhibiting different trading strategies (normal vs. early vs. flash trading, etc.). We further illustrate how our methodology can reveal "crisis modalities" in trading triggered by endogenous and exogenous system shocks: as an example, we reveal and characterize trading anomalies in the midst of the 2008 financial crisis.

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  • Teruyoshi Kobayashi & Anna Sapienza & Emilio Ferrara, 2018. "Extracting the multi-timescale activity patterns of online financial markets," Papers 1802.07405, arXiv.org, revised Apr 2018.
  • Handle: RePEc:arx:papers:1802.07405
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    References listed on IDEAS

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    1. Charles D. Brummitt & Teruyoshi Kobayashi, 2015. "Cascades in multiplex financial networks with debts of different seniority," Papers 1501.05400, arXiv.org, revised May 2015.
    2. Fabio Caccioli & Paolo Barucca & Teruyoshi Kobayashi, 2018. "Network models of financial systemic risk: a review," Journal of Computational Social Science, Springer, vol. 1(1), pages 81-114, January.
    3. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    4. Teruyoshi Kobayashi & Taro Takaguchi, 2017. "Significant ties: Identifying relationship lending in temporal interbank networks," Discussion Papers 1717, Graduate School of Economics, Kobe University.
    5. Markus K. Brunnermeier, 2009. "Deciphering the Liquidity and Credit Crunch 2007-2008," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 77-100, Winter.
    6. de Masi, G. & Iori, G. & Caldarelli, G., 2006. "A fitness model for the Italian interbank money market," Working Papers 06/08, Department of Economics, City University London.
    7. Iori, Giulia & De Masi, Giulia & Precup, Ovidiu Vasile & Gabbi, Giampaolo & Caldarelli, Guido, 2008. "A network analysis of the Italian overnight money market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 259-278, January.
    8. R. Baupain & A. Durre, 2007. "The interday and intraday patterns of the overnight market : evidence from an electronic platform," Post-Print hal-00300195, HAL.
    9. Franklin Allen & Elena Carletti, 2010. "An Overview of the Crisis: Causes, Consequences, and Solutions-super-," International Review of Finance, International Review of Finance Ltd., vol. 10(s1), pages 1-26.
    10. Teruyoshi Kobayashi & Taro Takaguchi, 2017. "Social dynamics of financial networks," Papers 1703.10832, arXiv.org, revised May 2017.
    11. Gai, Prasanna & Haldane, Andrew & Kapadia, Sujit, 2011. "Complexity, concentration and contagion," Journal of Monetary Economics, Elsevier, vol. 58(5), pages 453-470.
    12. Kobayashi, Teruyoshi & Takaguchi, Taro, 2018. "Identifying relationship lending in the interbank market: A network approach," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 20-36.
    13. Teruyoshi Kobayashi & Kohei Hasui, 2013. "Efficient immunization strategies to prevent financial contagion," Papers 1308.0652, arXiv.org, revised Dec 2013.
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    Cited by:

    1. Anastasios Demertzidis, 2019. "Interbank transactions on the intraday frequency: -Different market states and the effects of the financial crisis-," MAGKS Papers on Economics 201932, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

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