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The importance of measuring credit risk Beroepsvereniging van Beleggingsprofessionals 21 april 2008 Tom van Zalen Credit Risk Agenda • • • • What is credit risk? The importance of credit risk Modeling credit risk A link to the recent credit crunch Credit Risk 2 2 Credit Risk Agenda • What is credit risk? – Definition – Credit risk drivers – Systematic versus non-systematic risk Credit Risk • The importance of credit risk • Modeling credit risk • A link to the recent credit crunch 3 3 • Credit risk, a definition: Credit risk is the risk of loss due to a debtor's non-payment of a loan or other line of credit (either the principal or interest (coupon) or both). But also: 4 4 Credit Risk The risk of value losses following from a change in external credit factors. Credit Risk What is credit risk? • External credit factors: –Micro • Individual risk single debt instrument = status quo firm reflected in rating (and thus the credit spread) 5 Credit Risk –Macro • Collective risk fixed income portfolio = status quo economy reflected in business cycle Credit Risk What is credit risk? 5 • Micro: determinants rating: –Liability risk ~ volume debt versus equity –Asset risk ~ volume tangible or intangible –Cash flow risk ~ e.g. profitability, sales, repayment capacity Credit Risk What is credit risk? • Macro: determinants business cycle: 6 Credit Risk –Inflation and economic growth: Y = C + I + G + T • Market risk is aggregated liquidity and credit risk • Market risk is systematic or not diversifiable 6 Credit Risk What is credit risk? 225 200 175 150 125 100 Credit Risk 75 50 25 0 -25 Apr-99 Oct-99 Apr-00 Oct-00 Apr-01 AAA Oct-01 Apr-02 AA Oct-02 A Apr-03 Oct-03 Apr-04 Oct-04 BBB 7 7 Credit Risk What is credit risk? • Yield spreads largely depend upon rating, as a proxy for credit risk –Lower ratings face higher yield spreads • Convex relation: lower ratings face relative higher spreads 8 8 Credit Risk –Systematic market risk is significant • Lower ratings face relative higher non-systematic credit risk • Cyclical behaviour credit risk (credit cycles) • Counter cyclical dependence (higher correlation during crashes) Credit Risk Agenda • What is credit risk? • The importance of credit risk – Credit risk in the Euro-area – Market participants Credit Risk • Modeling credit risk • A link to the recent credit crunch 9 9 • Market funding offsets bank lending –Monetary integration = Euro ~ Liquidity • Deregulated capital of institutional investors goes Europe • Sovereigns face lower deficits due to disciplinary rules Brussels • Corporate entities go public more easy –Des-intermediation bank ~ Credit risk Credit Risk Credit risk in the Euro-area Credit Risk • Financial regulation encourages credit risk management –Central banking = Basel II / Solvency II –Accounting = IFRS 10 10 • Conclusion: Bank-orientated economy with a small financial market focused on sovereigns … becomes market-orientated economy with a large financial market focused on corporate entities. Financial Government Industrial Volume (MM) 400,000 80% 320,000 60% 240,000 40% 160,000 20% 80,000 0% 0 1998 1999 2000 2001 2002 2003 11 11 Credit Risk 100% 1997 Credit Risk Credit risk in the Euro-area • Conclusion: Introduction Euro eliminates foreign exchange risk, which has caused intensified focus upon credit risk. Diversification over rating classes has improved, although the average rating decreased and may explain higher price volatility. AAA AA A BBB Issuance (#) 400 80% 320 60% 240 40% 160 20% 80 0% 0 1998 1999 2000 2001 2002 2003 12 12 Credit Risk 100% 1997 Credit Risk Credit risk in the Euro-area • Banks (traditionally) –Pricers of risk (loan originations) –Sellers of risk (securitization = credit risk transfer of higher rated bonds) • High-rated homogeneous asset-backed securities (e.g. mortgages) • Medium-rated heterogeneous collateralized debt obligations (=tranching & structured) Credit Risk Market participants Credit Risk • Asset managers –Traders of risk –Buyers of risk (investment management) 13 13 Credit Risk Market participants • Hedge funds –Traders of risk (zero-position = arbitrage = long/short strategies) –Sellers & buyers of risk • Private equity 14 14 Credit Risk –Pricers of risk –Sellers of risk (funding using lower-rated by issuing highyield bonds) Credit Risk Market participants Buyers Traders Sellers Hedge funds Investment grade $ Premiums Institutional Instituional Investors Banks Banks $ Savings $ Investors Credit Risk Non-investment grade Private equity Private Equity Accounting “Hold-to-maturity” Trading portfolio 15 15 Credit Risk Agenda • What is credit risk? • The importance of credit risk • Modeling credit risk – Expected loss – Unexpected loss Credit Risk • A link to the recent credit crunch 16 16 • Credit risk is the probability of default (PD) of a loss given default (LGD) due to changes in external credit factors • Follows from credit loss distribution Credit Risk • Measured by: Credit Risk Modeling credit risk – Expected loss (μ) – Unexpected loss (σ) 17 17 Credit Risk Modeling credit risk- Expected loss • Credit loss distribution function Frequency UL Credit Risk SD EL Risk Capital (unexpected loss) 3 bp Economic capital Portfolio Value Expected Promised μ =EL 0 Value Value 18 18 • Expected loss – Measures the expected loss on a (portfolio of) loans given the characteristics of the counterparty and the loan conditions and the presence of collateral. – Is the μ of the credit loss distribution. – Credit spread = E[L] + liquidity spread 19 19 Credit Risk Expected loss = probability of default x loss given default E[L] = PD x LGD = % x % = % Credit Risk Modeling credit risk- Expected loss • Probability of default – Probability that a firm will default on its payment obligations (e.g. coupon payments, principal repayment) within one year. – Often follows from rating Credit Risk Modeling credit risk – Expected loss Credit Risk 20 20 14 5 GDP grow th 4 10 3 8 2 6 1 4 0 2 0 1970 -1 1975 1980 1985 1990 1995 2000 GDP Growth Unemployment Rate • Number of defaults depends on the state of the economy. 12 -2 2005 Year 8000 Besloten Venootschap One-man Business Individuals Total Credit Risk 10000 Bankruptcies • Number of defaults varies over time; 6 Unemployment Rate Credit Risk Modeling credit risk – Expected loss 6000 4000 2000 0 1970 1975 1980 1985 1990 1995 2000 Year 21 21 2005 Credit Risk Modeling credit risk – Expected loss • Loss given default – The fraction of the outstanding loan that will not be recovered once default occurred. – Influenced by: • Collateral • Guarantees Credit Risk • Value of collateral may be correlated with the occurrence of default: – Example: commercial real estate mortgages – “Haircuts” provide a correction for this issue 22 22 • Unexpected loss 23 23 Credit Risk – If the realized credit loss would always equal its expected value, then there would be no risk. – In practice however, the credit loss is stochastic in nature and thus risk arises. – The possible deviation from the expectation is risk and is measured by the standard deviation of the loss distribution. – Unexpected loss is the σ of the credit loss distribution Credit Risk Modeling credit risk – Unexpected loss • Default occurrence – Occurrence of default follows a binomial distribution: • With probability PD a default will occur • With probability 1 – PD no default will occur Credit Risk Modeling credit risk – Unexpected loss – For a portfolio with n loans, all having the same PD, the total number of defaults is distributed as follows: Credit Risk # defaults ~ Binomial(n, PD): µ = n x PD σ2 = n x PD x (1 – PD) 24 24 • Binomial distribution for different values of n: 25 25 Credit Risk • According to the central limit theorem, for large n, the binomial distribution will converge to a normal distribution. Credit Risk Modeling credit risk – Unexpected loss • Loss given default: – For a long time assumed constant due to: • Complexity reasons • Little effect to loss distribution compared to uncertainty in the default event. – Random variable with values: 0% < LGD < 100% Credit Risk • Is modeled using a Beta distribution: Credit Risk Modeling credit risk – Unexpected loss – Distribution can be bound between two points – Distribution can have a wide range of shapes 26 26 • Beta distribution: – Two shape parameters: α and β – B(α,β) Credit Risk Modeling credit risk – Unexpected loss Credit Risk 27 27 • Credit loss distribution: from a single loan to a portfolio of loans. – E[L] is additive – U[L] is not! Correlations need to be taken into account. Credit Risk Modeling credit risk – Unexpected loss – Consider a portfolio that contains two loans, x & y with corresponding portfolio weights wx and wy: Credit Risk 2 σportfolio x2σ 2x y2σ 2y 2 x yσ xσ yρxy 28 28 Credit Risk Agenda • What is credit risk? • The importance of credit risk • Modeling credit risk • A link to the recent credit crunch Credit Risk – Structured finance – Correlations 29 29 • Structured finance – Pooling of assets and the subsequent sale to investors of tranched claims on the cash flows backed by these pools. – Key aspect of tranching: • Create one or more classes of securities whose rating is higher than the average rating of the underlying asset pool. 30 30 Credit Risk – Characterized by: • Pooling of assets • De-linking of credit risk • Tranching of liabilities Credit Risk A link to the recent credit crunch • A structured finance transaction in figure: Senior Funds SPV Funds Originator Credit Risk A link to the recent credit crunch Mezzanine Traded assets Assets Liabilities Tranches Investors • The original credit risk is distributed in the economy and crops up everywhere. 31 31 Credit Risk Junior • Tranching is made possible by imperfect correlation between the assets in the original asset pool. • A diversified pool of risky assets is expected to have a relatively predictable return pattern. – E[L] of original asset pool = E[L] of total tranched pool – U[L] of original asset pool = U[L] of total tranched pool • E[L] and U[L] are portioned and attributed to the different classes in the tranched pool. 32 32 Credit Risk • Tranched pool is structured in such a way that: Credit Risk A link to the recent credit crunch Last loss Lower Lowest risk expected yield First loss Higher Highest risk expected yield BB BB BB BB BB BB BB BB BB AAA / AA BB BB BB BB BB BB BB Pool of mortgage loans AA / A BBB/ BB BB / B Unrated Source: CSMA 33 33 Credit Risk BB BB Credit Risk A link to the recent credit crunch Credit Risk A link to the recent credit crunch • It’s all about correlations!! I Credit Risk 34 34 • Yield spreads (Jan ‘04 – Jan ‘08): Credit crunch 1.500 Madrid bombings 1.250 1.000 Credit Risk A link to the recent credit crunch 0.750 Credit Risk 0.500 0.250 0.000 -0.250 sprBBB 35 Jan-08 sprA Jul-07 Jan-07 sprAA Jul-06 Jan-06 Jul-05 Jan-05 Jul-04 Jan-04 sprAAA 35 • Yield return correlations: 0.300 1.000 0.900 0.250 0.800 0.700 Credit Risk A link to the recent credit crunch 0.200 0.600 0.150 0.500 0.100 0.300 0.200 0.050 0.100 0.000 0.000 Nov-07 (AA,BBB) May-07 Nov-06 May-06 Nov-05 May-05 (AA,A) vol (DJ Eurostoxx 50) 36 36 Credit Risk 0.400 • What happened? – US economy tightened and housing prices declined – Correlation between high rating yield returns and the market volatility is always close to one ~ AAA/AA can serve as a proxy for the riskiness of the market. – Correlation between individual loans must then also increase. – Credit risk in pool based on assumed low correlations ~ credit risk is underestimated! 37 37 Credit Risk – Correlation between high rated (= market) and lower rated was low but started to increase. Credit Risk A link to the recent credit crunch • Could the recent credit crunch have been prevented with adequate credit risk management? • Lessons learned: – Don’t trust on historical correlations only – Use dynamic / stress correlations Credit Risk A link to the recent credit crunch Credit Risk 38 38