Credit risk
What is a credit risk Definition of credit risk risk of loss resulting from the fact that a borrower or counterparty fails to fulfill its obligations under the agreed terms (because they either cannot or do not want to pay) Credit risk also includes Sovereign risk Concentration risk Settlement risk Counterparty risk
What is a credit risk What does credit risk concern: Loans and receivables (Debt) securities Guarantees issued Promises for granting a loan / undrawn credit facilities Derivatives
he most important terms Credit event Default (= fail to repay, this has nothing with a default option in I!) Credit rating migration Expected loss (EL): EL = PD LGD ED PD = probability of default LGD = loss given default ED = exposure at default RR = recovery rate (RR = 1 - LGD) Expected loss is covered by revenues (interest rate, fees) and by loan loss provisions (based on the level of expected impairment)
he most important terms Unexpected loss and credit loss distribution Unexpected loss is covered by capital
he most important terms Moody's S&P Fitch Prime aa a1 + + High grade a2 a3 - - 1 + + Upper medium grade 2 3 - - Baa1 BBB+ BBB+ Lower medium grade Baa2 BBB BBB Baa3 BBB- BBB- Ba1 BB+ BB+ Non-investment grade speculative Ba2 BB BB Ba3 BB- BB- B1 B+ B+ Highly speculative B2 B B B3 B- B- Substantial risks Caa1 CCC+ Extremely speculative Caa2 CCC Caa3 CCC- CCC In default with little prospect for recovery CC Ca C C DDD In default D DD D Source: Wikipedia
he most important terms Source: Fitch, November 2012 http://commons.wikimedia.org/wiki/file:fitch_credit_rating_of_european_countries_(cs)_november_2012.svg
Problematic issues he lack of available data (adverse selection problem) Correlations (between failures as well as between the parameters) Wrong way exposure (growing utilization of credit cards in case of an increase in PD) In case of deterioration of the situation, both the PD and LGD may worsen Concentration risk should be taken into account in the loan portfolio Systemic risk (drop in real estate prices will negatively affect the whole construction industry; the impact of changes in FX rates for exporters) Contagion risk Backtesting he loss distribution has fat tails and is not symmetric
ypes of models Structural models ssumption: the default is caused by a decrease in asset value below some threshold (i.e. the value of debt) Stochastic model of asset prices Reduced-form models he defaults are assumed to be stochastic and their distribution might depend on a number of external factors (GDP growth, inflation, unemployment, interest rates etc.) he most important models: Merton model / KMV CreditMetrics CreditRisk + CreditPortfolioView Regulatory approach (single risk factor model)
Merton model Structural model he model of PD is based on the structure of the balance sheet Basic assumptions: t = the asset value is assumed to be stochastic (geometric Brownian motion) D t = debt is represented by one zero coupon bond maturing at time, hence D t = e -r(-t) D E t = equity is the difference between assets and debt (E t = t D) Basic idea: If D, then E = D If < D, the company bankrupts and E = 0 (limited liability of stockholders). Summary: E = ( D ) +, hence equity is a call option held by the company owners, where the underlying is the company as a whole and strike price = D.
Merton model he value of assets he value of debt
Merton model Stochastic process of asset value: W t Wiener process d t = μ t + σ t dw t Consequence: ln t je z N(ln 1 2 2 t, ) 0 2 t Probability of default: P( D ) P(ln ln D ) ln D 0 1 2 2
KMV model Model used by Moody s KMV = Kealhofer, McQuown & Vašíček Several improvements of the Merton model It allows for a more complex structure of the debt hreshold for default is estimated as the short-term debt + one half of the long term debt he assumption of normal distribution is not required, Moody s uses an empirical relationship between so-called distance to default (DD) and the expected default frequency (EDF), where 1 2 ln DD D 0 2
KMV model wo issues he values of and D are only available with a low frequency (only financial/accounting statements are published). heoretically, should be a real value of assets but the only available value is the accounting value, which might differ significantly Solution: he value of parameter μ is calculated from the published financial reports he value of equity (E t ) is known daily (number of shares price) E t is the option price which can be represented by Black-Scholes formula d ln E t r( t) t ( d1, t ) e D ( d2, t ) r Iteration procedure: Calculate time series of t for the chosen initial value of σ Estimate new value of σ and repeat the iteration procedure t ( t) t 1 2 D 2 1, t, d 2, t d 1, t t
Merton / KMV model Weaknesses he default threshold is set arbitrarily he model can only by applied to companies listed and traded on an exchange he EDF value are too sensitive to changes in equity prices It is challenging to calculate the EDF without the normality of assumption (the construction of an empirical distribution faces significant data limitations) Systemic risk is not captured at all Data based on the financial statements of companies are seriously delayed and has a low frequency References diploma thesis defended on EFM. Pišková (2004): Modelovanie portfólia dlhopisov s uvažovaním rizika defaultu K. Kadlečíká (2009): Ocenenie Credit default swapov a porovnanie ich vývoja v čase finančnej krízy