The role of the CDS market in pricing Eurozone sovereign risk Richard Portes London Business School and CEPR The Debt Crisis in the Eurozone Reykjavik University 7-8 October 2011
Road map Background and objectives Procedure and literature Analytical framework Data and period Cointegration tests VECM (vector error correction model) Conclusions Alternative hypothesis
CDS pricing CDS contract: insurance against deterioration of the credit standing of a bond issuer – ‘credit protection’ Spread (insurance premium) prices credit risk So does price of bond (spread between yield and riskless rate) We expect to see close relation between the two spreads – no-arbitrage condition (Duffie 1999)…
…but maybe not Different markets, different market participants Different maturities: CDS contract on bond typically won’t have same term as bond itself CDS not only a hedge on underlying bond – since 2002-03, CDS market dominated by speculation (‘naked CDS’), in which buyer does not hold underlying bond Buying naked CDS similar to short-selling underlying bond, but easier, and no capital risk CDS spread must at least set floor under reference entity’s borrowing costs
Our aims Test long-term accuracy of credit risk pricing in CDS market Investigate price discovery relationship: which market leads? These are limited objectives – there are bigger issues at stake – but first one wants to see how the data behave
Procedure ADF tests on spread series If spreads cointegrated of order one, then use Johansen test to determine if bond yield spread and CDS premia move together in long run If cointegration, then estimate VECM to establish price discovery leadership Also do Granger causality tests between the two series
Literature Most papers study corporate bonds and CDS on them Of the few studies on CDS on sovereign bonds, most focus on emerging markets Only two papers on EU sovereign bond CDS Fontana-Schneider (2010) look at 10 EU countries over 2006-2010, focusing on determinants of difference between the two spreads , split sample between pre- and post-crisis Arce et al . (2011) seek evidence of market frictions that impede arbitrage Methodologically closes to us are Zhu (2006), Ammer and Cai (2007), Blanco et al . (2005)
Pricing framework Reduced form approach With no transaction costs, should have perfect arbitrage between risky bond, riskless bond, CDS Yield of risk-free bond should equal difference between yield of corresponding risky bond and cost of credit protection as percentage of risky bond nominal value (CDS spread): E.g. if risk-free bond yield exceeds difference between risky bond yield and CDS spread, then buy risk-free bond, short risky bond, sell protection in CDS market
The bond-CDS bas asis Difference between CDS spread and bond yield spread on same reference entity With perfect arbitrage Note: this assumes no counterparty risk (can credit protection seller pay off after credit event? recall AIG) – but that seems to have surprisingly little effect on spreads in practice (Arce et al. ) Note: strong demand from credit protection buyers would push basis up
Basis trades Basis positive if risk premium (spread) on risky bond is ‘too low’ or CDS spread is ‘too high’ So short risky bond – but rigidities in cash market may slow arbitraging If basis negative, then short risk-free bond, normally easier (market more liquid) So might expect basis usually positive Various factors might drive basis up or down
CDS market ‘protection buyer’ pays fixed periodic premium to ‘protection seller’ Premium expressed in bp of reference asset’s nominal value Outstanding gross notional value of CDS contracts at 31 August 2011 was $15 trn, with 2,156,591 trades At end-2007, share of sovereign CDS was 5%, of which 90% were in EM But by May 2010, sovereign segment was 15% Main sellers are investment banks (8 dominate market), main buyers are hedge funds
Data Source: CMA Period: 30 Jan 2004 – 11 Mar 2011 (data for some countries available earlier, but some appear to be unreliable, and we chose to have identical periods for all countries) 6 countries: Austria, Belgium, Greece, Ireland, Italy, Portugal Daily data on 5-year maturity (most liquid market segment), average spreads across dealers Bond yield data from Datastream Risk-free benchmark taken as 5-yr German govt bond
Structural break? Stationary model with structural break could be confused with unit root model (Perron 1989) Unit root tests may be unreliable with structural break Nonstationarity affects results of tests for structural break (Perron 2005) Our sample period longer than other studies – splitting it would eliminate that advantage and reduce power of tests Testing for structural break would require taking account of multiple possible break points – e.g. August 2007, September 2008, spring 2010 And our results on full sample seem fairly well-determined
Cointegration tests ADF does not reject unit root hypothesis for both CDS and bond spreads for each country Equilibrium theory requires cointegration between the two spreads – otherwise deviations from equilibrium will not be temporary We estimate where If credit spreads equal in equilibrium, then cointegrating vector might be [1,-1] with α = 0
But if cointegration with α ≠ 0, β ≠ 1, then we conclude that the two markets may price credit risk differently in the short run but move together in the long run – and this is what we find for all countries Standard Johansen test without assuming structural breaks may cause over-rejection of cointegration – but in our data, no cointegration is rejected for each country, suggesting that structural breaks do not pose a problem
VECM Which market leads in price discovery? VEC representation models changes in each spread as function of (a) deviation from cointegration relationship (b) lagged values of changes in both spreads Coefficient on deviation term is speed of adjustment If both those coefficients are significant, we infer that there is significant price interaction, and relative size of coefficients reflects relative importance in price discovery If one market always lags the other, then coefficient in market that leads price discovery should be 0
VECM results Austria, Belgium, Greece, Italy: price discovery is 2-way, with CDS market more important Ireland and Portugal: credit risk is priced in CDS market first But there are short-term pricing discrepancies They are persistent: estimated adjustment coefficients suggest only 2% of price discrepancy is eliminated within 2 days Gonzalo-Granger (1995) measure of relative contribution of each market to price discovery suggests that on average, CDS market leads Granger causality tests not very powerful but generally confirm these results
Conclusions CDS and bond spreads appear to be equal in long run, as theory suggests But in short run there is substantial and persistent divergence And even if CDS market prices risk ‘correctly’ in long run, that does not mean that credit risk as priced by either market reflects ‘fundamentals’ CDS market usually leads bond market in price discovery, possibly because it is more liquid But there is 2-way causality
An alternative hypothesis CDS market may lead in price discovery because changes in CDS prices affect fundamentals that drive bond spreads If CDS spread affects cost of funding – as it must – then rise in spread will not merely signal but will cause deterioration in credit quality (Portes 2010) Need dynamic model with multiple equilibria
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