Rating of European sovereign bonds and its impact on credit default swaps (CDS) and government bond yield spreads Supervised by: Prof. Günther Pöll Diploma Presentation Plass Stefan B.A. 21 th October 2013 JKU Linz
Table of Contents - Structure Objectives of Diploma Thesis Objective Do Rating-Downgrades on European States have impact on Credit Default Swaps and Government Bond Yields? Theoretical Framework Theoretical Framework Ratings of dominating Credit Agencies (CRAs) Function and Rating influencing factors Credit Default Swaps (CDS) Function, Pricing and Market of Sovereign CDS (SCDS) European Government Bonds Function, Pricing and Market of Government Bonds Empirical Analysis Empirical Analysis Panel Data Description Methodical Analysis - Regression
General Connectivity Long Term Issuers Debt Rating Sovereign Credit Default Swaps (CDS) Government s Credit Standing Government Bond Yield (Spreads) Long Term Issuers Debt Rating
I. Government Issuer Ratings Main purpose: Evaluate the issuers ability and willingness to repay its debt obligations Minimizing information asymmetry and reducing information costs for potential investors Standard & Poor, Moody and Fitch covering 95% of whole rating market (measured by revenues, Year 2009) Rating of assets classes (and its issuers): Government securities (Mainly government bonds) Asset backed securities Financial Institutions Corporations Insurance Companies 10,98% 8,03% 3,78% 0,80% Government Securities Asset-Backed Securities Financial Institutions Corporations Insurance Companies 76,40% Graph: Amount of rated assets by issuer class Source: Securities and Exchange Comission (SEC), 2012
Graph: Rating Scales of S&P, Moody, Fitch Source: Afonso/Furceri/Gomez, 2012
Government Issuer Ratings Factors influencing Sovereign Credit Ratings International Organization of Securities Commissions (IOSCO) Credit Rating Agency Reform Act 2006 as Nationally recognized statistical rating organization (NRSRO) GDP per person and GDP growth rate: Level of GDP per person influences Rating of a country, the GDP growth rate indicates the strength of an economy Inflation: Level of inflation indicates structural problems in a country and its ability/willingness to pay back its debt Economic development: The future development of an economy as a mayor influence on a country s rating Balance of trade: Trade surplus and trade deficits effect ratings in a positive or negative way Default history: Defaults (partly of whole default, or negotiations about the terms of credits for the issuers) of a country have strong negative influence on a country s rating National budget balance: Budget deficits affect a country s credit rating in a negative way. Vice versa for budget surpluses.
II. Credit Default Swaps (CDS) Function and Purpose Derivative Instrument to hedge against a default of the issuer of an underlying asset OTC traded CDS on Sovereign debt are socalled Sovereign CDS (SCDS) International Swaps and Derivatives Association (ISDA) Function: Source: Noyer et al, 2010 Credit events ( ISDA Credit Definitions Source ): Failure to pay, bankruptcy, Repudiation, Restructuring, Obligation acceleration;
Credit Default Swaps Main Types of CDS Single Name CDS: CDS on an (underlying) asset of a single issuer. E.g. CDS on an Austrian bond Multi Name CDS: CDS Index: CDS on a portfolio of (underlying) assets respectively its issuers, E.g. CDS Index for European Sovereigns: Markit itraxx SovX Western Europe Index, CDX for North America; CDS Baskets: single name credit default swaps on individual assets (individual basket of assets) possibility of building individual risky basket! (mainly for trading) E.g. first-to-default swap: if one underlying asset (issuer) of the basket defaults (credit event), protection buyer receives payment for the defaulted issuer Default Correlation: The higher the default correlation between the (underlying) assets (respectively its CDS Spreads) in the basket, the higher is a possible portfolio loss
Credit Default Swaps Expected Loss/Probability of Default Main parameter of CDS pricing: Probability of default Models to calculate probability of default: E[l] Structural Models Merton, Black & Scholes Intensity based Models statistical calculation of probability of default = Expected loss (amount) LGD= Loss given default (%) rec = recovery rate (%) p(def ) = probability of default (%) l = loss (amount) E[ l] l * p( def )*(1 rec) (1 rec) LGD
Credit Default Swaps Use of CDS Hedging: Hedging against the Default of the Issuer of the Underlying (Government Bond) in the case of a credit event (which is defined by the ISDA). Trading (Speculation) naked position: Going Short on a CDS offers potential gains when the credit-worthiness (Rating) deteriorates (downgrades), vice versa when going Long on a CDS. Arbitrage (Basis Trading): The investor buys a CDS and the underlying Bond when CDS Spread and Bond Yield Spread are not equal. Buying the CDS and the underlying Bond (when the Bond Yield Spread is higher then the CDS Spread) enables to realize profit (= Basis ). Risk diversification: Buying CDS hedges against default risk. Selling CDS enables to finance the costs of buying CDS, and diversifies risk by selling CDS on issuers of other industries.
Credit Default Swaps The market for SCDS Credit Default Swaps (CDS) - Notional Amounts Outstanding in Billions USD Main Counterparties of CDS in 2010: 35.000 30.000 25.000 20.000 15.000 10.000 5.000-25,00% 20,00% 15,00% 10,00% 5,00% 0,00% Rank Counterparty 1 JP Morgan Chase 2 Goldman Sachs 3 Bank of America 4 Morgan Stanley 5 Barclays 6 Deutsche Bank 7 UBS 8 Citigroup 9 BNP Paribas 10 Credit Suisse Multi name total (linke Achse) Single name total (linke Achse) Single name sovereign (linke Achse) Single name sovereign in % of Singe name total (rechte Achse) Source: Fitch Ratings, 2011 Graph: Credit Default Swaps (CDS) Notional Amounts Outstanding Source: BIS, 2006-2013, IMF, 2013
in % of GDP in % of GDP III. European Government Bonds Function and Purpose Main purpose of Government Bonds: Financing Public investments, Health costs, infrastructure projects, etc. Government Financial Balances and Marketable Gross Borrowing Requirements 30,00% 0,00% 25,00% 20,00% 15,00% 10,00% 5,00% -1,00% -2,00% -3,00% -4,00% -5,00% -6,00% -7,00% -8,00% 0,00% -9,00% 2007 2008 2009 2010 2011 2012 2013 Central government marketable gross borrowing in OECD countries (linke Achse) Central government marketable gross borrowing in euro area (linke Achse) General government financial balance to GDP ratios in euro area (rechte Achse) General government financial balance to GDP ratios in OECD countries (rechte Achse) Source: OECD - Sovereign borrowing outlook, 2013
European Government Bonds Pricing / YTM 90% of all Government Bonds in 2013 are plain vanilla bonds (estimation of OECD, 2013) Empirical analysis deals with YTM (yield to maturity) of Government Bonds Typical price calculation for a plain vanilla bond: P 0 C (1 r) C (1 r) Par value relation (plain vanilla bond): 2 C (1 r) 3... C M (1 r) N Par value relation P M C M 1 *[ (1 r r YTM YTM ) n ] (1 1 r YTM ) N P M r C = Price YTM= Yield to maturity = Notional Amount = Coupon payment (in % of Notional amount Coupon interest rate)
Bond Yield in % European Government Bonds Yield and Rating Rating and Yields for Greece, Portugal, Spain, Ireland and Italy in 2012: Rating and corresponding Yields of selceted Euopean States 18 16 14 12 10 BB+ BB Ba3 BBB BBB- BBB+ Ba1 A- BBB+ Baa2 Moody's Fitch S&P 8 10 YR yields 6 4 CCC 3M T-Bill yields 2 C 0 Greece Portugal Spain Ireland Italy Source: OECD, 2013
IV. Empirical Analysis Does a Rating downgrade (of a country) effect the CDS premium and Bond Yield (Spread) of the sample? Sample: 27 EU-Member countries Observation period: 15.09.2008 (Lehman Brothers bankruptcy) 30.06.2013 Used data: Sources: CDS premiums for the selected time period (5-day week) Government Bond Yield Spreads (Benchmark: Germany) for the selected time period (5-day week) Standard & Poor s Capital IQ for CDS premiums (e.g. Ticker for Austria CDS premium: IQT46195000) Reuters for Bond Yields (e.g. Ticker for Bond Yield Austria: AT10YT=RR) Ratings History of each country: Reuters Debt Structure Long Term Debt Issuer Ratings
Empirical Analysis Data Data preparation: CDS premiums: Using daily average CDS premiums for all 27 EU member countries, scaling of all ratings into numbers (e.g. S&P s AAA Rating equals 17, AA+ = 16, ) Bond Yield Spreads: Using daily average Bond Yield Spreads (Benchmark German Bond Yields), scaling of all ratings into numbers (e.g. S&P s AAA Rating equals 17, AA+ = 16, ) Methodology: High correlation of CDS and Bonds (Spreads) across countries (Longstaff et al, 2011) Linear OLS Time Series Regression for ± 2 days (before and after) = 5 days sample at a rating downgrade announcement Regression Model: y = c + t*x + ε Time Series Regression Software: EViews 6
Empirical Analysis Statistical Prerequisites for Regression 1. Prerequisite: Errors ε is normally distributed Zero hypothesis: Errors are normally distributed zero hypothesis not rejected 2. Prerequisite: No systematic Error ε E( ) Zero hypothesis: systematic errors are approximately zero zero hypothesis not rejected 0
Empirical Analysis Statistical Prerequisites for Regression 3. Prerequisite: 2 Var const. Errors ε are homoscedastic (white noise) Zero hypothesis: Homoscedasticity in the errors zero hypothesis not rejected 4. Prerequisite: Errors are not correlated i j Zero hypothesis: Errors are normally distributed zero hypothesis not rejected
Empirical Analysis Regression Results Rating Announcement Effects on CDS Spreads and Bond Yield Spreads over Germany for all 27 EU-Member Countries Change in bp per day Median Average Credit Default Swap Spreads (10Y) over Germany* -0.7910-1.7067 Standard & Poor s -1.5975-3.8360 Moody s -0.7910-1.6386 Fitch s 0.8940 0.3546 Change in % per day Median Average Bond Yield Spreads (10Y) over Germany** -0.0162-0.0006 Standard & Poor s 0.0192 0.0060 Moody s -0.0236-0.0076 Fitch s -0.0162-0.0003 Observation Period: ± 2 days before & after Downgrade Announcement * No data available for Luxembourg, Malta, Cyprus ** No data available for Luxembourg, Malta, Cyprus, Estonia Data: Significance at 90% Confidence Interval Data Sources: S&P Capital IQ, Thomson Reuters