We compare the market pricing of euro area government bonds and the corresponding Credit Default Swaps (CDSs). In particular, we analyse the “basis” defined as the difference between the premium on the CDS and the credit spread on the underlying bond. Our sample of weekly data covers the period from January 2007 to December 2012 and contains several episodes of sovereign market distress. Overall, we observe a complex relationship between the derivatives market and the underlying cash market characterised by sizable deviations from the no-arbitrage relationship (i.e. basis equal to zero). We show that short-selling frictions explain the persistence of positive basis deviations while funding frictions explain the persistence of negative basis deviations which are observed for countries with weak public finances. Moreover, we show that the “flight-to-quality/liquidity” phenomenon in bond markets is a key driver of the large positive basis of better rated countries.

This paper studies how the Greek sovereign credit event in March 2012 impacted the credit default swap (CDS) market from market-wide and investor behaviour perspectives, using both network tools to a dataset of snapshots of the global bilateral CDS exposures and a panel analysis on CDS spreads. Regarding the CDS spreads, we find very little discernible direct impact of the Greek credit event on CDS spreads overall. This finding provides some further evidence that the Greek credit event was well anticipated by most market participants. However, we find several significant changes in the Greek CDS network structure following the credit event: the number of connections via exposures declined significantly, the directionality of the positions (net long vs net short) of the main groups of market participants reversed, while none of the non-banks returned to trade Greek CDSs until the last observation of dataset (October 2014). Regarding indirect effects to other CDS markets, we find evidence of temporary spill-over effects on CDS reference entities with credit risk associated with the risk of the Greek sovereign. In particular, the market and counterparty structures changed temporarily with all types of traders decreasing their exposures to the EU periphery sovereign reference entities and also changing their trading counterparties, while after some time, the structure of the market returned to a similar one observed before the credit event. Finally, we find some support for the bank-sovereign nexus, as there was a consistent retreat from the CDS exposures on banks in the EU periphery countries, contrary to banks residing in the other EU countries.

This paper analyses the network structure of the credit default swap (CDS) market and its determinants, using a unique dataset of bilateral notional exposures on 642 financial and sovereign reference entities. We find that the CDS network is centred around 14 major dealers, exhibits a “small world” structure and a scale-free degree distribution. A large share of investors are net CDS buyers, implying that total credit risk exposure is fairly concentrated. Consistent with the theoretical literature on the use of CDS, the debt volume outstanding and its structure (maturity and collateralization), the CDS spread volatility and market beta, as well as the type (sovereign/financial) of the underlying bond are statistically significantly related—with expected signs—to structural characteristics of the CDS market.

In this paper we compare the out-of-sample performance of two common extensions of the Black–Scholes option pricing model, namely GARCH and stochastic volatility (SV). We calibrate the three models to intraday FTSE 100 option prices and apply two sets of performance criteria, namely out-of-sample valuation errors and Value-at-Risk (VaR) oriented measures. When we analyze the fit to observed prices, GARCH clearly dominates both SV and the benchmark Black–Scholes model. However, the predictions of the market risk from hypothetical derivative positions show sizable errors. The fit to the realized profits and losses is poor and there are no notable differences between the models. Overall, we therefore observe that the more complex option pricing models can improve on the Black–Scholes methodology only for the purpose of pricing, but not for the VaR forecasts.

We use an extensive data set of bilateral credit default swap (CDS) positions to estimate the impact on collateral demand of new clearing and margin regulations. The estimated collateral demands include initial margin and the frictional demands associated with the movement of variation margin through the network of market participants. We estimate the impact on total collateral demand of more widespread initial margin requirements, increased novation of CDS to central clearing parties (CCPs), an increase in the number of clearing members, the proliferation of CCPs of both specialized and non-specialized types, collateral rehypothecation practices, and client clearing. System-wide collateral demand is increased significantly by the application of initial margin requirements for dealers, whether or not the CDS are cleared. Given these dealer-to-dealer initial margin requirements, mandatory central clearing is shown to lower, not raise, system-wide collateral demand, provided there is no significant proliferation of CCPs. Central clearing does, however, have significant distributional consequences for collateral requirements across market participants.

We develop a framework to analyse the credit default swap (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.