Financial Networks, Contagion and Systemic Risk

 

 

A Systemic Risk Assessment of OTC Derivatives Reforms and Skin-in-the-game for CCPs (2017)  

 

Abstract:

The G20 OTC (over-the-counter) derivatives reforms impose large collateral/liquidity demands on clearing members of Central Counterparty (CCP) clearing platforms in the form of initial margins, variation margins and contributions to the default fund. In Heath et al. (2016), it was shown how this introduces a trade-off between liquidity risk and solvency risk with the system manifesting considerable systemic risk from these two sources of risk while CCP penetration is at current levels. We extend this analysis to include the European Market Infrastructure Regulation (EMIR) skin-in-the-game requirements for CCPs, which aim to ameliorate the contributions to the default fund by clearing members and also to prevent moral hazard problems associated with the too-interconnected-to-fail (TITF) status of CCPs as more and more derivatives are centrally cleared. We provide a systemic risk assessment of these features of the OTC derivatives reforms using network analysis based on 2015-end data on the derivatives positions for 40 globally systemically important banks (G-SIBs). 

Markose, S., Giansante, S. and Rais Shaghaghi, A. (2017). A systemic risk assessment of OTC derivatives reforms and skin‑in‑the‑game for CCPsBanque de France Financial Stability Review, no. 21.

The FSR analyses the impact of financial reforms eight years after the adoption of the G10 action plan in 2009.
From 20 April 2017, the FSR can be accessed from Banque de France’s website

                                                                                                                                                                                      

Early Warning and Systemic Risk in Core Global Banking: Balance Sheet Financial Network and Market Price-Based Methods (2017)

 

Abstract:

We analyse systemic risk in the 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. MES (Marginal Expected Shortfall), ∆CoVaR, and SRISK in a cross-border setting. Unlike paradoxical risk measures, the eigen-pair method gives early-warning of instability in terms of tipping points identified by regulatory capital thresholds and centrality measures for 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.

Markose, S., Giansante, S., Eterovic, N. and Gatkowski, M. (2017). Early Warning and Systemic Risk in Core Global Banking: Balance Sheet Financial Network and Market Price-Based MethodsSSRN Electronic Journal .

                                                                                                                                                                                      

Non-performing loans: regulatory and accounting treatments of assets (2016)

 

Abstract:

Asset quality is an essential part of sound banking. However, asset quality is difficult for banking regulators and investors to assess in the absence of a common, cross-border scheme to classify assets. Currently no standard is applied universally to classify loans, the most sizable asset on many banks’ balance sheets. As a corollary, no common definition of non-performing loans (NPLs) exists. This paper documents divergences in the definition of NPLs across countries, accounting regimes, firms and data sources. The paper’s originality is in attending to the legal, accounting, statistical, economic and strategic aspects of loan loss provisioning (LLP) and NPLs, topics that are multidisciplinary by nature but have not been dealt with in the literature in an integrated fashion before. Since the 2007 Great Financial Crisis (GFC), accounting bodies and prudential regulators are increasingly focused on early recognition of credit losses and enhanced disclosure. A common approach to NPL recognition might complement these initiatives.

Bholat, D., Lastra, R., Markose, S., Miglionico, A. and Sen, K. (2016). Non-performing loans: regulatory and accounting treatments of assets. Bank of England Staff Working Paper, No. 594.

                                                                                                                                                                                      

CCPs and Network Stability in OTC Derivatives Markets (2016)

 

Abstract:

Among the reforms to OTC derivative markets since the global financial crisis is a commitment to collateralize counterparty exposures and to clear standardized contracts via central counterparties (CCPs). The reforms aim to reduce interconnectedness and improve counterparty risk management in these important markets. At the same time, however, the reforms necessarily concentrate risk in one or a few nodes in the financial network and also increase institutions’ demand for high-quality assets to meet collateral requirements. This paper looks more closely at the implications of increased CCP clearing for both the topology and stability of the financial network. Building on Heath et al. (2013) and Markose (2012), the analysis supports the view that the concentration of risk in CCPs could generate instability if not appropriately managed. Nevertheless, maintaining CCP prefunded financial resources in accordance with international standards and dispersing any unfunded losses widely through the system can limit the potential for a CCP to transmit stress even in very extreme market conditions. The analysis uses the Bank for International Settlements Macroeconomic Assessment Group on Derivatives (MAGD) data set on the derivatives positions of the 41 largest bank participants in global OTC derivative markets in 2012.

Heath, A., Kelly, G., Manning, M., Markose, S. and Shaghaghi, A. (2016). CCPs and network stability in OTC derivatives marketsJournal of Financial Stability, 27, pp.217-233.

                                                                                                                                                                                      

Systemic risk analytics: A data-driven multi-agent financial network (MAFN) approach (2013)

 

Abstract:

Systemic risk from financial intermediaries (FIs) refers to a negative externality problem, which is rife with fallacy of composition-type errors. To ‘see’ why seemingly rational behaviour at the level of an individual FI contributes to system-wide instability is a non-trivial exercise, which requires holistic visualization and modelling techniques. Paradox of volatility inherent to market price-based measures of systemic risk has made bilateral balance sheet and off balance data between FIs and network analysis essential for systemic risk management. There is both a data and a skills gap in implementing large-scale data-driven multi-agent financial network models that can operationalize macro-prudential policy. Different designs for a Pigou-type systemic risk surcharge are discussed with special reference to the Markose eigen-pair method, which simultaneously determines the degree of instability of the network of financial flows of obligors and also the rank order in the centrality of FIs contributing to it.

Markose, S. (2013). Systemic risk analytics: A data-driven multi-agent financial network (MAFN) approachJournal of Banking Regulation Special Issue on Regulatory Data and Systemic Risk Analytics, 14(3-4), pp.285-305

                                                                                                                                                                                      

The following two papers set out the eigen-pair (the dominant eigen-value and corresponding eigen-vector centrality) analysis to quantify systemic risk or instability from large financial networks and determine the contribution to systemic risk by financial intermediaries.

 

Too interconnected to fail’ financial network of US CDS market: Topological fragility and systemic risk (2012)

 

Abstract:

A small segment of credit default swaps (CDS) on residential mortgage backed securities (RMBS) stand implicated in the 2007 financial crisis. The dominance of a few big players in the chains of insurance and reinsurance for CDS credit risk mitigation for banks’ assets has led to the idea of too interconnected to fail (TITF) resulting, as in the case of AIG, of a tax payer bailout. We provide an empirical reconstruction of the US CDS network based on the FDIC Call Reports for off balance sheet bank data for the 4th quarter in 2007 and 2008. The propagation of financial contagion in networks with dense clustering which reflects high concentration or localization of exposures between few participants will be identified as one that is TITF. Those that dominate in terms of network centrality and connectivity are called ‘super-spreaders’. Management of systemic risk from bank failure in uncorrelated random networks is different to those with clustering. As systemic risk of highly connected financial firms in the CDS (or any other) financial markets is not priced into their holding of capital and collateral, we design a super-spreader tax based on eigenvector centrality of the banks which can mitigate potential socialized losses.

Markose, S., Giansante, S. and Shaghaghi, A. (2012). ‘Too interconnected to fail’ financial network of US CDS market: Topological fragility and systemic riskJournal of Economic Behavior & Organization, 83(3), pp.627-646

http://www.sciencedirect.com/science/article/pii/S0167268112001254

                                                                                                                                                                                      

Systemic Risk from Global Financial Derivatives : A Network Analysis of Contagion and Its Mitigation with Super-Spreader Tax (2012)

 

Abstract:

Financial network analysis is used to provide firm level bottom-up holistic visualizations of interconnections of financial obligations in global OTC derivatives markets. This helps to identify Systemically Important Financial Intermediaries (SIFIs), analyse the nature of contagion propagation, and also monitor and design ways of increasing robustness in the network. Based on 2009 FDIC and individually collected firm level data covering gross notional, gross positive (negative) fair value and the netted derivatives assets and liabilities for 202 financial firms which includes 20 SIFIs, the bilateral flows are empirically calibrated to reflect data-based constraints. This produces a tiered network with a distinct highly clustered central core of 12 SIFIs that account for 78 percent of all bilateral exposures and a large number of  financial intermediaries (FIs) on the periphery. The topology of the network results in the “Too- Interconnected-To-Fail” (TITF) phenomenon in that the failure of any member of the central tier will bring down other members with the contagion coming to an abrupt end when the ‘super-spreaders’ have demised. As these SIFIs account for the bulk of capital in the system, ipso facto no bank among the top tier can be allowed to fail, highlighting the untenable implicit socialized guarantees needed for these markets to operate at their current levels. Systemic risk costs of highly connected SIFIs nodes are not priced into their holding of capital or collateral. An eigenvector centrality based ‘super-spreader’ tax has been designed and tested for its capacity to reduce the potential socialized losses from failure of SIFIs.

Markose, S. (2012). Systemic Risk from Global Financial Derivatives : A Network Analysis of Contagion and Its Mitigation with Super-Spreader TaxIMF Working Paper, No. 12/282.

                                                                                                                                                                                      

“Multi-Agent Financial Network (MAFN) Model of US Collateralized Debt Obligations (CDO): Regulatory Capital Arbitrage, Negative CDS Carry Trade and Systemic Risk Analysis”

 

Sheri, M, Bewaji, O & Giansante, S 2012, Multi-agent financial network (MAFN) model of US collateralized debt obligations (CDO): regulatory capital arbitrage, negative CDS carry trade and systemic risk analysis. in B Alexandrova-Kabadjova, S Martinez-Jaramillo, L Garcia-Almanza & E Tsang (eds), Simulation in Computational Finance and Economics: Tools and Emerging Applications. IGI Global. DOI: 10.4018/978-1-4666-2011-7

http://www.essex.ac.uk/economics/discussion-papers/Papers-text/dp714.pdf

Economics Department Discussion Paper, No. 714, May 2012

 

Chapter in Simulation in Computational Finance and Economics: Tools and Emerging Applications   Editor(s):  Alexandrova-Kabadjova B., S. Martinez-Jaramillo, A. L. Garcia-Almanza, E. Tsang, IGI Global, August 2012.

Markose, S.M, S. Giansante, M. Gatkowski and A. R. Shaghagi, “Too Interconnected To Fail: Financial contagion and systemic risk In network Model of CDS and other credit enhancement obligations of US banks”, Economics Department, University of Essex, DP 683, 2010 Feb http://www.essex.ac.uk/economics/discussion-papers/Papers-text/dp683.pdf

 

Papers in preparation:

 

Multi-agent Financial Network Models and Systemic Risk Management: A New Complexity Perspective Sheri Markose
First draft 2010 November.

 

Pigou Tax of Systemic Important Financial Intermediaries In Financial Networks: An Empirical Application of Systemic Risk Monitoring and Governance
Sheri Markose
, University of Essex, UK;  Simone GiansanteUniversity of Bath, UK  (Presented at the Workshop Twenty Years after Cadbury, Ten Years after Sarbanes-Oxley:
Challenges of Corporate Governance, 24-25 June 2013 , Bath Management School)
Discussant:  G. Nathan Dong, Columbia University, USA –

 

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