Early warning of systemic risk in global banking: eigen-pair R number for financial contagion and market price-based methods. (English) Zbl 1532.91132
Ann. Oper. Res. 330, No. 1-2, 691-729 (2023); correction ibid. 30, No. 1-2, 841 (2023).
Summary: We analyse systemic risk in the core global banking system using a new network-based spectral eigen-pair method, which treats network failure as a dynamical system stability problem. This is compared with market price-based systemic risk indexes (SRIs), viz. marginal expected shortfall (MES), delta conditional value-at-risk (Delta-CoVaR), and conditional capital shortfall measure of systemic risk (SRISK) in a cross-border setting. Unlike paradoxical market price based risk measures, which underestimate risk during periods of asset price booms, the eigen-pair method based on bilateral balance sheet data gives early-warning of instability in terms of the tipping point that is analogous to the R number in epidemic models. For this regulatory capital thresholds are used. Furthermore, network centrality measures identify systemically important and vulnerable banking systems. Market price-based SRIs are contemporaneous with the crisis and they are found to covary with risk measures like VaR and betas.
MSC:
| 91G45 | Financial networks (including contagion, systemic risk, regulation) |
| 91G70 | Statistical methods; risk measures |
Keywords:
OR in banking; global financial networks; systemic risk; early warning signals; eigen-pair analysis; statistical market price-based risk measures; paradoxical risk measuresReferences:
| [1] | Acharya, V.; Engle, R.; Richardson, M., Capital shortfall: A new approach to ranking and regulating systemic risks, American Economic Review, 102, 3, 59-64 (2012) |
| [2] | Acharya, V.; Pedersen, L.; Philippon, T.; Richardson, M., Measuring systemic risk, Review of Financial Studies, 1, 2-47 (2017) |
| [3] | Acharya, VV; Stefen, S., Analyzing systemic risk of the European banking sector. Handbook on systemic risk (2012), Cambridge: Cambridge University Press, Cambridge |
| [4] | Adrian, T., & Brunnermeier, M. (2011). CoVaR. Working Paper, Princeton University and Federal Reserve Bank of New York. |
| [5] | Adrian, T.; Shin, H., Liquidity and leverage, Journal of Financial Intermediation, 19, 3, 418-37 (2010) |
| [6] | Adrian, T.; Shin, H., Financial intermediary balance sheet management, Annual Reviews in Financial Economics, 3, 289-307 (2011) |
| [7] | Adrian, T., & Shin, H. S. (2011b). Procyclical leverage and value-at-risk. FRB of New York Staff Report (338). |
| [8] | Allen, F., Beck, T., Carletti, E., Lane, P., Schoenmaker, D., & Wolf, W. (2011). Cross-border banking in Europe: Implications for financial stability and macroeconomic policies. Centre for Economic Policy Research. |
| [9] | Alter, A.; Craig, B.; Raupach, P., Centrality-based capital allocations and bailout, IMF Working Paper, 14, 237, 1-40 (2014) |
| [10] | Anand, K.; Craig, B.; von Peter, G., Filling in the blanks: Network structure and interbank contagion, Quantitative Finance, 15, 4, 625-636 (2015) · Zbl 1398.91701 |
| [11] | Arghyrou, M.; Kontonikas, A., The EMU sovereign-debt crisis: Fundamentals, expectations and contagion, Journal of International Financial Markets, Institutions and Money, 22, 4, 658-677 (2012) |
| [12] | Arsov, I., Canetti, E., Kodres, E., & Mitra, S. (2013). “Near-Coincident” Indicators of Systemic Stress. IMF Working Paper WP/12/115. |
| [13] | Avdjiev, S., McGuire, P., & Wooldridge, P. (2015). Enhanced data to analyse international banking. BIS Quarterly Review. |
| [14] | Bardoscia, M.; Battiston, S.; Caccioli, F.; Caldarelli, G., Pathways towards instability in financial networks, Nature Communications, 8, 1-7 (2017) · doi:10.1038/ncomms14416 |
| [15] | Battiston, S., Caldarelli, G., D’Errico, M., & Gurciullo, S. (2016). Leveraging the network: A stress-test framework based on debtrank. Available at SSRN 2571218. · Zbl 1414.91436 |
| [16] | BCBS. (2013). Global systemically important banks: Updated assessment methodology and the higher loss. Bank for International Settlements. |
| [17] | Benoit, S., Colletaz, G., Hurlin, C., & Perignon, C. (2013). A theoretical and empirical comparison of systemic risk measures. HEC Paris Research Paper No. FIN-2014-1030. |
| [18] | Benoit, S.; Colliard, J-E; Hurlin, C.; Christophe, P., Where the risks lie: A survey on systemic risk, Review of Finance, 20, 1-59 (2016) |
| [19] | Billio, M.; Getmansky, M.; Lo, AW; Pelizzon, L., Econometric measures of connectedness and systemic risk in the finance and insurance sectors, Journal of Financial Economics, 104, 3, 535-559 (2012) |
| [20] | Borio, C.; Drehmann, M.; Alfaro, R., Toward an operational framework for financial stability: “fuzzy” measurement and its consequences: Ch. 04, Financial stability, monetary policy, and central banking, 063-123 (2011), Chile: Central Bank of Chile, Chile |
| [21] | Borio, C.; Furfine, C.; Lowe, P., “Procyclicality of the financial system and financial stability: Issues and policy options,” in marrying the macro- and micro- prudential dimensions of financial stability, BIS Papers, 1, 1-57 (2001) |
| [22] | Braouezec, Y.; Wagalath, L., Strategic fire-sales and price-mediated contagion in the banking system, European Journal of Operational Research, 274, 1180-1197 (2019) · Zbl 1431.91417 |
| [23] | Brownlees, C., & Engle, R. (2016). SRISK: A conditional capital shortfall index for systemic risk measurement. Review of Financial Studies(forthcoming). |
| [24] | Brunnermeier, MK; Cheridito, P., Measuring and allocating systemic risk, Risk, 7, 46 (2013) |
| [25] | Brunnermeier, MK; Sannikov, Y., International credit flows and pecuniary externalities, American Economic Journal: Macroeconomics, 7, 1, 297-338 (2015) |
| [26] | Bruno, V., & Shin, H. (2014). Cross-border banking and global liquidity. Monetary and Economic Department, BIS Working Papers (458). |
| [27] | Bruno, V.; Shin, HS, Cross-border banking and global liquidity, Review of Economic Studies, 82, 2, 535-564 (2015) · Zbl 1405.91505 |
| [28] | Bruno, V.; Shin, HS, Capital flows and the risk-taking channel of monetary policy, Journal of Monetary Economics, 71, 119-132 (2015) |
| [29] | Calabrese, R.; Elkink, JA; Giudici, PS, Measuring bank contagion in Europe using binary spatial regression models, Journal of the Operational Research Society, 68, 12, 1503-1511 (2017) |
| [30] | Calabrese, R.; Osmetti, SA, A new approach to measure systemic risk: A bivariate copula model for dependent censored data, European Journal of Operational Research, 279, 3, 1053-1064 (2019) · Zbl 1431.91418 · doi:10.1016/j.ejor.2019.06.027 |
| [31] | Castrén, O.; Rancan, M., Macro-networks: An application to euro area financial accounts, Journal of Banking & Finance, 46, 43-58 (2014) |
| [32] | Cerutti, E., Claessens, S., & McGuire, P. (2012). Systemic risks in global banking: What available data can tell us and what more data are needed? Technical report, National Bureau of Economic Research. |
| [33] | Chakrabarti, D.; Wang, Y.; Wang, C.; Leskovec, J.; Faloutsos, C., Epidemic thresholds in real networks, ACM Transactions on Information and System Security, 10, 4, 1:1-1:26 (2008) |
| [34] | Cont, R., Moussa, A., & Santos, E. B. (2012). Network structure and systemic risk in banking systems. In Handbook of systemic risk. Cambridge University Press. |
| [35] | Degryse, H.; Elahi, M.; Penas, MF, Cross-border exposures and financial contagion, International Review of Finance, 10, 2, 209-240 (2010) |
| [36] | Diebold, FX; Yılmaz, K., On the network topology of variance decompositions: Measuring the connectedness of financial firms, Journal of Econometrics, 182, 1, 119-134 (2014) · Zbl 1311.91196 |
| [37] | Eisenberg, L.; Noe, TH, Systemic risk in financial systems, Management Science, 47, 2, 236-249 (2001) · Zbl 1232.91688 |
| [38] | Elad, F.; Bongbee, N., Event study on the reaction of stock returns to acquisition news, International Finance and Banking, 4, 1, 33-43 (2017) |
| [39] | Engle, R.; Jondeau, E.; Rockinger, M., Systemic risk in Europe, Review of Finance, 19, 1, 145-190 (2015) |
| [40] | Engle, R., & Sheppard, K. (2001). Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH. Working Paper UCSD 15. |
| [41] | Fagiolo, G., Clustering in complex directed networks, Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 76, 2, 1-8 (2007) |
| [42] | Feinstein, Z., Capital regulation under price impacts and dynamic financial contagion, European Journal of Operational Research, 281, 2, 449-463 (2020) · Zbl 1431.91420 · doi:10.1016/j.ejor.2019.08.044 |
| [43] | Furfine, CH, Interbank exposures: Quantifying the risk of contagion, Journal of Money, Credit and Banking, 35, 1, 111-128 (2003) |
| [44] | Gauthier, C.; Lehar, A.; Souissi, M., Macroprudential capital requirements and systemic risk, Journal of Financial Intermediation, 21, 4, 594-618 (2012) |
| [45] | Glasserman, P.; Young, HP, How likely is contagion in financial networks?, Journal of Banking & Finance, 50, 383-399 (2015) |
| [46] | Haldane, A. (2009). Rethinking the financial network. Speech delivered at the Financial Student Association, Amsterdam. |
| [47] | Hamilton, JD, A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica, 57, 357-384 (1989) · Zbl 0685.62092 |
| [48] | Hattori, M., & Suda, Y. (2007). Developments in a cross-border bank exposure “network”. In BIS (Ed.), Research on global financial stability: The use of BIS international financial statistics. CGFS Papers. Bank for International Settlements, vol. 29 (pp. 16-31). |
| [49] | Hautsch, N.; Schaumburg, J.; Schienle, M., Financial network systemic risk contributions, Review of Finance, 19, 2, 685-738 (2015) · Zbl 1417.91560 |
| [50] | Heath, A.; Kelly, G.; Manning, M.; Markose, S.; Shaghaghi, AR, CCPs and network stability in OTC derivatives markets, Journal of Financial Stability, 27, 217-233 (2016) |
| [51] | Heesterbeek, JAP; Dietz, K., The concept of \(R_o\) in epidemic theory, Statistica Neerlandica, 50, 1, 89-110 (1996) · Zbl 0854.92018 |
| [52] | IMF-BIS-FSB. (2009). Financial stability board international monetary fund-bank for international settlements (2009) guidance to assess the systemic importance of financial institutions, markets and instruments: Initial considerations. |
| [53] | Ipsen, I., & Wills, R. M. (2005). Analysis and computation of Google’s pagerank. In 7th IMACS international symposium on iterative methods in scientific computing. Toronto: Fields Institute. · Zbl 1242.65065 |
| [54] | Karolyi, G. A., Sedunov, J., & Taboada, A. G. (2017). Cross-border bank flows and systemic risk. |
| [55] | Leslé, V. L., & Avramova, S. (2012). Revisiting risk-weighted assets. IMF Working Papers WP/12/90. |
| [56] | Mackinlay, AC, Event studies in economics and finance, Journal of Economic Literature, 53, 13-39 (1997) |
| [57] | Mahdavi Ardekani, A.; Distinguin, I.; Tarazi, A., Do banks change their liquidity ratios based on network characteristics?, European Journal of Operational Research (2020) · Zbl 1441.91084 · doi:10.1016/j.ejor.2020.02.011 |
| [58] | Markose, S.; Giansante, S.; Shaghaghi, A., “Too interconnected to fail” financial network of US CDS market: Topological fragility and systemic risk, Journal of Economic Behavior and Organization, 83, 3, 627-646 (2012) |
| [59] | Markose, S.; Giansante, S.; Shaghaghi, AR, A systemic risk assessment of OTC derivatives reforms and skin-in-the-game for CCPs, Banque de France Financial Stability Review, 21, April, 111-126 (2017) |
| [60] | Markose, S. M. (2012). Systemic risk from global financial derivatives: A network analysis of contagion and its mitigation with super-spreader tax. IMF Working Paper (12/282). |
| [61] | Markose, SM, Systemic risk analytics: A data-driven multi-agent financial network (MAFN) approach, Journal of Banking Regulation, 14, 3-4, 285-305 (2013) |
| [62] | May, RM, Will a large complex system be stable?, Nature, 238, 5364, 413-414 (1972) |
| [63] | May, RM, Stability and complexity in model ecosystems (1974), Princeton: Princeton University Press, Princeton |
| [64] | Minoiu, C., Kang, C., Subrahmanian, V., & Berea, A. (2013). Does financial connectedness predict crises? IMF Working Papers WP/13/267. · Zbl 1398.91690 |
| [65] | Minoiu, C.; Reyes, JA, A network analysis of global banking: 1978-2009, Journal of Financial Stability, 9, 2, 168-184 (2013) |
| [66] | Minsky, H., Stabilizing an unstable economy (1986), Yale: Yale University Press, Yale |
| [67] | Mistrulli, PE, Assessing financial contagion in the interbank market: Maximum entropy versus observed interbank lending patterns, Journal of Banking & Finance, 35, 5, 1114-1127 (2011) |
| [68] | Newman, M., Networks: An introduction (2010), Oxford: Oxford University Press, Oxford · Zbl 1195.94003 |
| [69] | Page, L.; Brin, S., The anatomy of a large-scale hypertextual Web search engine, Computer Networks, 30, 107-117 (1998) |
| [70] | Saramäki, J.; Kivelä, M.; Onnela, JP; Kaski, K.; Kertész, J., Generalizations of the clustering coefficient to weighted complex networks, Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 75, 2, 2-5 (2007) |
| [71] | Savona, R., Hedge fund systemic risk signals, European Journal of Operational Research, 236, 282-291 (2014) · Zbl 1338.91162 |
| [72] | Schularick, M.; Taylor, AM, Credit booms gone bust: Monetary policy, leverage cycles, and financial crises, 1870-2008, American Economic Review, 102, 2, 1029-61 (2012) |
| [73] | Simaan, M.; Gupta, A.; Kar, K., Filtering for risk assessment of interbank network, European Journal of Operational Research, 280, 1, 279-294 (2020) · Zbl 1431.91423 |
| [74] | Soramäki, K.; Bech, M.; Arnold, J.; Glass, R.; Beyeler, W., The topology of interbank payment flows, Physica A, 379, 1, 317-333 (2007) |
| [75] | Torri, G.; Giacometti, R.; Paterlini, S., Robust and sparse banking network estimation, European Journal of Operational Research, 270, 1, 51-65 (2018) · Zbl 1403.91394 · doi:10.1016/j.ejor.2018.03.041 |
| [76] | van den Driessche, P., Reproduction numbers of infectious disease models, Infectious Disease Modelling, 2, 288-303 (2017) |
| [77] | von Mises, R.; Pollaczek-Geiringer, H., Praktische verfahren der gleichungsauflösung, ZAMM - Zeitschrift für Angewandte Mathematik und Mechanik, 9, 152-164 (1929) · JFM 55.0305.01 |
| [78] | Von Peter, G. (2007). International banking centres: A network perspective. BIS Quarterly Review. |
| [79] | Wang, Y., Chakrabarti, D., Wang, C., & Faloutsos, C. (2003). Epidemic spreading in real network: An eigenvalue viewpoint. In 22nd International symposium on reliable distributed systems (SRDS’03) (pp. 25-34). Los Alamitos, CA: IEEE Computer Society. |
| [80] | Ye, W.; Liu, X.; Miao, B., Measuring the subprime crisis contagion: Evidence of change point analysis of copula functions, European Journal of Operational Research, 22, 96-103 (2012) · Zbl 1253.91186 |
| [81] | Ye, W.; Luo, K.; Liu, X., Time-varying quantile association regression model with applications to financial contagion and VaR, European Journal of Operational Research, 256, 1015-1028 (2017) · Zbl 1394.62152 |
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