How Does Risk Flow in the Credit Default Swap Market?

Abstract

We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 − 2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.

Corporate payments networks and credit risk rating

“…In other cases, as in the seminal paper [14], even if the theoretical framework applies to single firms, the empirical part focuses on the aggregate, sector network, due to lack of more granular data. The use of payments as a proxy of interactions between economic entities is not new and has been investigated mainly for banks [15][16][17][18][19] in the context of systemic risk studies, where, however, other choices to characterise interactions are possible [20][21][22][23]. Apparently much less is known about the payment network between firms, mostly because of lack of data.…”

Default Ambiguity: Credit Default Swaps Create New Systemic Risks in Financial Networks

“…If we had instead only considered the writer-holder relationships, all of our counterexamples in Section 3 would have looked like simple acyclic graphs and we would only have captured one of the three dependencies arising from a CDS. Our insights may help bring about a paradigm shift in the literature on systemic risk in CDS markets, where so far, either some of the network effects were ignored or the reference entities were aggregated (Markose, Giansante and Shaghaghi, 2012;Brunnermeier, Clerc and Scheicher, 2013;D'Errico et al, 2017).…”

“…A large part of the CDS market is made up of CDSs where the reference entity is itself a financial institution. 4 An analysis of CDS transaction data by D'Errico et al (2017) has shown that the financial institutions (including reference entities) in the CDS market are tightly connected, implying the presence of circular relationships involving holders, writers, and reference entities.…”

Mapping the Interconnectedness between EU Banks and Shadow Banking Entities

“…New regulatory data through the AIFMD, the European Market Infrastructure Regulation (EMIR) and the Securities Financing Transaction Regulation (SFTR) can allow for a more detailed assessment of the interconnectedness of banks and shadow banking entities in a number of markets. These data can also be used to monitor the use of synthetic leverage by non-bank financial institutions and allow for the mapping of linkages between banks and non-banks in derivative markets (Abad et al, 2016;D'Errico et al, 2016).…”