IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v462y2016icp134-140.html
   My bibliography  Save this article

The topology of card transaction money flows

Author

Listed:
  • Zanin, Massimiliano
  • Papo, David
  • Romance, Miguel
  • Criado, Regino
  • Moral, Santiago

Abstract

Money flow models are essential tools to understand different economical phenomena, like saving propensities and wealth distributions. In spite of their importance, most of them are based on synthetic transaction networks with simple topologies, e.g. random or scale-free ones, as the characterisation of real networks is made difficult by the confidentiality and sensitivity of money transaction data. Here, we present an analysis of the topology created by real credit card transactions from one of the biggest world banks, and show how different distributions, e.g. number of transactions per card or amount, have nontrivial characteristics. We further describe a stochastic model to create transactions data sets, feeding from the obtained distributions, which will allow researchers to create more realistic money flow models.

Suggested Citation

  • Zanin, Massimiliano & Papo, David & Romance, Miguel & Criado, Regino & Moral, Santiago, 2016. "The topology of card transaction money flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 134-140.
  • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:134-140
    DOI: 10.1016/j.physa.2016.06.091
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116303661
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2016.06.091?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hu, Mao-Bin & Jiang, Rui & Wu, Qing-Song & Wu, Yong-Hong, 2007. "Simulating the wealth distribution with a Richest-Following strategy on scale-free network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 467-472.
    2. Yougui Wang & Ning Ding & Li Zhang, 2005. "The Circulation of Money and Holding Time Distribution," Papers physics/0507147, arXiv.org.
    3. Pawel Sobkowicz, 2009. "Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-11.
    4. Wang, Yougui & Ding, Ning & Zhang, Li, 2003. "The circulation of money and holding time distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(3), pages 665-677.
    5. M.-B. Hu & W.-X. Wang & R. Jiang & Q.-S. Wu & B.-H. Wang & Y.-H. Wu, 2006. "A unified framework for the pareto law and Matthew effect using scale-free networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 53(2), pages 273-277, September.
    6. Adrian A. Dragulescu & Victor M. Yakovenko, 2002. "Statistical Mechanics of Money, Income, and Wealth: A Short Survey," Papers cond-mat/0211175, arXiv.org.
    7. Reed, William J., 2001. "The Pareto, Zipf and other power laws," Economics Letters, Elsevier, vol. 74(1), pages 15-19, December.
    8. Wu, Fang & Huberman, Bernardo A. & Adamic, Lada A. & Tyler, Joshua R., 2004. "Information flow in social groups," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 327-335.
    9. D'aniel Kondor & M'arton P'osfai & Istv'an Csabai & G'abor Vattay, 2013. "Do the rich get richer? An empirical analysis of the BitCoin transaction network," Papers 1308.3892, arXiv.org, revised Mar 2014.
    10. Dániel Kondor & Márton Pósfai & István Csabai & Gábor Vattay, 2014. "Do the Rich Get Richer? An Empirical Analysis of the Bitcoin Transaction Network," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Massimiliano Zanin & Miguel Romance & Santiago Moral & Regino Criado, 2018. "Credit Card Fraud Detection through Parenclitic Network Analysis," Complexity, Hindawi, vol. 2018, pages 1-9, May.
    2. Carolina E S Mattsson & Teodoro Criscione & Frank W Takes, 2022. "Circulation of a digital community currency," Papers 2207.08941, arXiv.org, revised Jun 2023.
    3. Mikrajuddin Abdullah, 2022. "Introducing Cashless Transaction Index based on the Effective Medium Approximation," Papers 2209.13470, arXiv.org.
    4. Iglesias Pérez, Sergio & Moral-Rubio, Santiago & Criado, Regino, 2021. "A new approach to combine multiplex networks and time series attributes: Building intrusion detection systems (IDS) in cybersecurity," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    5. Sergio Iglesias Perez & Regino Criado, 2022. "Increasing the Effectiveness of Network Intrusion Detection Systems (NIDSs) by Using Multiplex Networks and Visibility Graphs," Mathematics, MDPI, vol. 11(1), pages 1-24, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Massimiliano Zanin & David Papo & Miguel Romance & Regino Criado & Santiago Moral, 2016. "The topology of card transaction money flows," Papers 1605.04938, arXiv.org.
    2. Carlo Campajola & Marco D'Errico & Claudio J. Tessone, 2022. "MicroVelocity: rethinking the Velocity of Money for digital currencies," Papers 2201.13416, arXiv.org, revised May 2023.
    3. Li, Mu-Yao & Cai, Qing & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Exponentially decayed double power-law distribution of Bitcoin trade sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    4. Ayana T Aspembitova & Ling Feng & Lock Yue Chew, 2021. "Behavioral structure of users in cryptocurrency market," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-19, January.
    5. Alexandre Bovet & Carlo Campajola & Jorge F. Lazo & Francesco Mottes & Iacopo Pozzana & Valerio Restocchi & Pietro Saggese & Nicol'o Vallarano & Tiziano Squartini & Claudio J. Tessone, 2018. "Network-based indicators of Bitcoin bubbles," Papers 1805.04460, arXiv.org.
    6. Ke Wu & Spencer Wheatley & Didier Sornette, 2018. "Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations," Papers 1803.03088, arXiv.org, revised May 2018.
    7. Martins, Francisco Leonardo Bezerra & do Nascimento, José Cláudio, 2022. "Power law dynamics in genealogical graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    8. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    9. Nick James & Kevin Chin, 2021. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Papers 2111.11022, arXiv.org, revised Jan 2022.
    10. Jiaqi Liang & Linjing Li & Daniel Zeng, 2018. "Evolutionary dynamics of cryptocurrency transaction networks: An empirical study," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    11. Espinoza-Licona, David R. & Pérez-Sosa, Felipe A., 2019. "El bitcoin, ¿una burbuja especulativa? Análisis de la estabilidad paramétrica de series de tiempo para el periodo 2009-2018," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 14(51), pages 45-60, Segundo s.
    12. Xing, Xiaoyun & Xiong, Wanting & Chen, Liujun & Chen, Jiawei & Wang, Yougui & Stanley, H. Eugene, 2018. "Money circulation and debt circulation: A restatement of quantity theory of money," Economics Discussion Papers 2018-1, Kiel Institute for the World Economy (IfW Kiel).
    13. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    14. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
    15. Young Bin Kim & Sang Hyeok Lee & Shin Jin Kang & Myung Jin Choi & Jung Lee & Chang Hun Kim, 2015. "Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-18, August.
    16. Chengyi Tu & Paolo DOdorico & Samir Suweis, 2018. "Critical slowing down associated with critical transition and risk of collapse in cryptocurrency," Papers 1806.08386, arXiv.org, revised Nov 2019.
    17. Matthias Nadler & Fabian Schar, 2020. "Decentralized Finance, Centralized Ownership? An Iterative Mapping Process to Measure Protocol Token Distribution," Papers 2012.09306, arXiv.org.
    18. Tseng, Fang-Mei & Palma Gil, Eunice Ina N. & Lu, Louis Y.Y., 2021. "Developmental trajectories of blockchain research and its major subfields," Technology in Society, Elsevier, vol. 66(C).
    19. Yoshi Fujiwara & Rubaiyat Islam, 2021. "Bitcoin's Crypto Flow Network," Papers 2106.11446, arXiv.org, revised Jul 2021.
    20. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:134-140. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.