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Loan and nonloan flows in the Australian interbank network

Author

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  • Sokolov, Andrey
  • Webster, Rachel
  • Melatos, Andrew
  • Kieu, Tien

Abstract

High-value transactions between banks in Australia are settled in the Reserve Bank Information and Transfer System (RITS) administered by the Reserve Bank of Australia. RITS operates on a real-time gross settlement (RTGS) basis and settles payments and transfers sourced from the SWIFT payment delivery system, the Austraclear securities settlement system, and the interbank transactions entered directly into RITS. In this paper, we analyse a dataset received from the Reserve Bank of Australia that includes all interbank transactions settled in RITS on an RTGS basis during five consecutive weekdays from 19 February 2007 inclusive, a week of relatively quiescent market conditions. The source, destination, and value of each transaction are known, which allows us to separate overnight loans from other transactions (nonloans) and reconstruct monetary flows between banks for every day in our sample. We conduct a novel analysis of the flow stability and examine the connection between loan and nonloan flows. Our aim is to understand the underlying causal mechanism connecting loan and nonloan flows. We find that the imbalances in the banks’ exchange settlement funds resulting from the daily flows of nonloan transactions are almost exactly counterbalanced by the flows of overnight loans. The correlation coefficient between loan and nonloan imbalances is about −0.9 on most days. Some flows that persist over two consecutive days can be highly variable, but overall the flows are moderately stable in value. The nonloan network is characterised by a large fraction of persistent flows, whereas only half of the flows persist over any two consecutive days in the loan network. Moreover, we observe an unusual degree of coherence between persistent loan flow values on Tuesday and Wednesday. We probe static topological properties of the Australian interbank network and find them consistent with those observed in other countries.

Suggested Citation

  • Sokolov, Andrey & Webster, Rachel & Melatos, Andrew & Kieu, Tien, 2012. "Loan and nonloan flows in the Australian interbank network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2867-2882.
  • Handle: RePEc:eee:phsmap:v:391:y:2012:i:9:p:2867-2882
    DOI: 10.1016/j.physa.2011.12.036
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    References listed on IDEAS

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    1. Adam B. Ashcraft & Darrell Duffie, 2007. "Systemic Illiquidity in the Federal Funds Market," American Economic Review, American Economic Association, vol. 97(2), pages 221-225, May.
    2. Iori, Giulia & Renò, Roberto & De Masi, Giulia & Caldarelli, Guido, 2007. "Trading strategies in the Italian interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 467-479.
    3. Soramäki, Kimmo & Bech, Morten L. & Arnold, Jeffrey & Glass, Robert J. & Beyeler, Walter E., 2007. "The topology of interbank payment flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 317-333.
    4. 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.
    5. Caldarelli, Guido, 2007. "Scale-Free Networks: Complex Webs in Nature and Technology," OUP Catalogue, Oxford University Press, number 9780199211517.
    6. 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;EDP Sciences, vol. 71(4), pages 523-531, October.
    7. Furfine, Craig H, 2003. " Interbank Exposures: Quantifying the Risk of Contagion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(1), pages 111-128, February.
    8. Cajueiro, Daniel O. & Tabak, Benjamin M., 2008. "The role of banks in the Brazilian interbank market: Does bank type matter?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6825-6836.
    9. Bech, Morten L. & Atalay, Enghin, 2010. "The topology of the federal funds market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5223-5246.
    10. 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.
    11. Li, Shouwei & He, Jianmin & Zhuang, Yaming, 2010. "A network model of the interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5587-5593.
    12. 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.
    13. Peter Gallagher & Jon Gauntlett & David Sunner, 2010. "Real-time Gross Settlement in Australia," RBA Bulletin, Reserve Bank of Australia, pages 61-69, September.
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    Cited by:

    1. Song, Jae Wook & Ko, Bonggyun & Cho, Poongjin & Chang, Woojin, 2016. "Time-varying causal network of the Korean financial system based on firm-specific risk premiums," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 287-302.
    2. Papadimitriou, Theophilos & Gogas, Periklis & Tabak, Benjamin M., 2013. "Complex networks and banking systems supervision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4429-4434.
    3. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.

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