IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v69y2020i4p711-739.html
   My bibliography  Save this article

Longitudinal networks of dyadic relationships using latent trajectories: evidence from the European interbank market

Author

Listed:
  • Federica Bianchi
  • Francesco Bartolucci
  • Stefano Peluso
  • Antonietta Mira

Abstract

Financial markets are ultimately seen as a collection of dyadic transactions. We study the temporal evolution of dyadic relationships in the European interbank market, as induced by monetary transactions registered in the electronic market for interbank deposits (e‐MID) during a period of 10 years (2006–2015). In particular, we keep track of how reciprocal exchange patterns have varied with macro events and exogenous shocks and with the emergence of the Global Financial Crisis in 2008. The approach adopted extends the model of Holland and Leinhardt to a longitudinal setting where individuals’ temporal trajectories for the tendency to connect and reciprocate transactions are explicitly modelled through splines or polynomials, and individual‐specific parameters. We estimate the model by an iterative algorithm that maximizes the log‐likelihood for every ordered pair of units. The empirical application shows that the methodology proposed may be applied to large networks and represents the process of exchange at a fine‐grained level. Further results are available in on‐line supplementary material.

Suggested Citation

  • Federica Bianchi & Francesco Bartolucci & Stefano Peluso & Antonietta Mira, 2020. "Longitudinal networks of dyadic relationships using latent trajectories: evidence from the European interbank market," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 711-739, August.
    • Handle: RePEc:bla:jorssc:v:69:y:2020:i:4:p:711-739
    DOI: 10.1111/rssc.12413
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssc.12413
    Download Restriction: no
    File URL: https://libkey.io/10.1111/rssc.12413?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
    ---><---

    References listed on IDEAS

    as
    1. Antonietta Mira, 2001. "On Metropolis-Hastings algorithms with delayed rejection," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 231-241.
    2. Affinito, Massimiliano, 2012. "Do interbank customer relationships exist? And how did they function in the crisis? Learning from Italy," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3163-3184.
    3. Acharya, Viral V. & Skeie, David, 2011. "A model of liquidity hoarding and term premia in inter-bank markets," Journal of Monetary Economics, Elsevier, vol. 58(5), pages 436-447.
    4. Daniele Durante & David B. Dunson, 2014. "Nonparametric Bayes dynamic modelling of relational data," Biometrika, Biometrika Trust, vol. 101(4), pages 883-898.
    5. Heider, Florian & Garcia-de-Andoain, Carlos & Frutos de Andres, Juan Carlos & Papsdorf, Patrick, 2016. "Stressed interbank markets: evidence from the European financial and sovereign debt crisis," Working Paper Series 1925, European Central Bank.
    6. R. Baupain & A. Durre, 2007. "The interday and intraday patterns of the overnight market : evidence from an electronic platform," Post-Print hal-00300195, HAL.
    7. Michele Tumminello & Salvatore Miccichè & Fabrizio Lillo & Jyrki Piilo & Rosario N Mantegna, 2011. "Statistically Validated Networks in Bipartite Complex Systems," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-11, March.
    8. 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.
    9. Hoff P.D. & Raftery A.E. & Handcock M.S., 2002. "Latent Space Approaches to Social Network Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1090-1098, December.
    10. Michele Manna & Carmela Iazzetta, 2009. "The topology of the interbank market: developments in Italy since 1990," Temi di discussione (Economic working papers) 711, Bank of Italy, Economic Research and International Relations Area.
    11. Drudi, Francesco & Durré, Alain & Mongelli, Francesco Paolo, 2012. "The interplay of economic reforms and monetary policy: the case of the euro area," Working Paper Series 1467, European Central Bank.
    12. Timothy Johnson, 2015. "Reciprocity as a Foundation of Financial Economics," Journal of Business Ethics, Springer, vol. 131(1), pages 43-67, September.
    13. Pavel N. Krivitsky & Mark S. Handcock, 2014. "A separable model for dynamic networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 29-46, January.
    14. Renaud Beaupain & Alain Durr�, 2011. "Inferring trading dynamics for an OTC market: the case of the euro area overnight money market," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1285-1295, October.
    15. Iori, Giulia & Mantegna, Rosario N. & Marotta, Luca & Miccichè, Salvatore & Porter, James & Tumminello, Michele, 2015. "Networked relationships in the e-MID interbank market: A trading model with memory," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 98-116.
    16. Stanley Wasserman, 1987. "Conformity of two sociometric relations," Psychometrika, Springer;The Psychometric Society, vol. 52(1), pages 3-18, March.
    17. Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2008. "Goodness of Fit of Social Network Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 248-258, March.
    18. Patrick O. Perry & Patrick J. Wolfe, 2013. "Point process modelling for directed interaction networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(5), pages 821-849, November.
    19. Francesco Drudi & Alain Durré & Francesco Paolo Mongelli, 2012. "The Interplay of Economic Reforms and Monetary Policy: The Case of the Eurozone," Journal of Common Market Studies, Wiley Blackwell, vol. 50(6), pages 881-898, November.
    20. Stanley Wasserman & Dawn Iacobucci, 1988. "Sequential social network data," Psychometrika, Springer;The Psychometric Society, vol. 53(2), pages 261-282, June.
    21. Affinito, Massimiliano & Franco Pozzolo, Alberto, 2017. "The interbank network across the global financial crisis: Evidence from Italy," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 90-107.
    22. Paolo Angelini & Andrea Nobili & Cristina Picillo, 2011. "The Interbank Market after August 2007: What Has Changed, and Why?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 923-958, August.
    23. Stanley Wasserman & Philippa Pattison, 1996. "Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 401-425, September.
    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. Diego P. Guisande & Maretno Agus Harjoto & Andreas G. F. Hoepner & Conall O’Sullivan, 2024. "Ethics and Banking: Do Banks Divest Their Kind?," Journal of Business Ethics, Springer, vol. 192(1), pages 191-223, June.
    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.

    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. Morteza Alaeddini & Philippe Madiès & Paul J. Reaidy & Julie Dugdale, 2023. "Interbank money market concerns and actors’ strategies—A systematic review of 21st century literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 573-654, April.
    2. Burcu Kapar & Giulia Iori & Giampaolo Gabbi & Guido Germano, 2020. "Market microstructure, banks’ behaviour and interbank spreads: evidence after the crisis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 283-331, January.
    3. Linardi, Fernando & Diks, Cees & van der Leij, Marco & Lazier, Iuri, 2020. "Dynamic interbank network analysis using latent space models," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    4. Alessandro Ferracci & Giulio Cimini, 2021. "Systemic risk in interbank networks: disentangling balance sheets and network effects," Papers 2109.14360, arXiv.org, revised Sep 2022.
    5. 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.
    6. Zappa, Paola & Vu, Duy Q., 2021. "Markets as networks evolving step by step: Relational Event Models for the interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    7. Cornelius Fritz & Michael Lebacher & Göran Kauermann, 2020. "Tempus volat, hora fugit: A survey of tie‐oriented dynamic network models in discrete and continuous time," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 275-299, August.
    8. 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).
    9. Iori, Giulia & Mantegna, Rosario N. & Marotta, Luca & Miccichè, Salvatore & Porter, James & Tumminello, Michele, 2015. "Networked relationships in the e-MID interbank market: A trading model with memory," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 98-116.
    10. Edoardo Rainone, 2017. "Pairwise trading in the money market during the European sovereign debt crisis," Temi di discussione (Economic working papers) 1160, Bank of Italy, Economic Research and International Relations Area.
    11. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.
    12. Lee, Jihui & Li, Gen & Wilson, James D., 2020. "Varying-coefficient models for dynamic networks," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    13. Sadamori Kojaku & Giulio Cimini & Guido Caldarelli & Naoki Masuda, 2018. "Structural changes in the interbank market across the financial crisis from multiple core-periphery analysis," Papers 1802.05139, arXiv.org.
    14. Piero Mazzarisi & Paolo Barucca & Fabrizio Lillo & Daniele Tantari, 2017. "A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market," Papers 1801.00185, arXiv.org.
    15. Saroyan, Susanna, 2024. "Counterparty choice, maturity shifts and market freezes: Lessons from the European interbank market," Journal of Economic Dynamics and Control, Elsevier, vol. 160(C).
    16. Teague R. Henry & Kathleen M. Gates & Mitchell J. Prinstein & Douglas Steinley, 2020. "Modeling Heterogeneous Peer Assortment Effects Using Finite Mixture Exponential Random Graph Models," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 8-34, March.
    17. Temizsoy, Asena & Iori, Giulia & Montes-Rojas, Gabriel, 2017. "Network centrality and funding rates in the e-MID interbank market," Journal of Financial Stability, Elsevier, vol. 33(C), pages 346-365.
    18. Beaupain, Renaud & Durré, Alain, 2016. "Excess liquidity and the money market in the euro area," Journal of Macroeconomics, Elsevier, vol. 47(PA), pages 33-44.
    19. Teague R. Henry & David Banks & Derek Owens-Oas & Christine Chai, 2019. "Modeling Community Structure and Topics in Dynamic Text Networks," Journal of Classification, Springer;The Classification Society, vol. 36(2), pages 322-349, July.
    20. Massimiliano Affinito & Matteo Piazza, 2021. "Always Look on the Bright Side? Central Counterparties and Interbank Markets during the Financial Crisis," International Journal of Central Banking, International Journal of Central Banking, vol. 17(1), pages 231-283, March.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jorssc:v:69:y:2020:i:4:p:711-739. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.