23. Analysing credit risk Flashcards
Define credit risk
- Risk of loss due to contractual obligations not being met (in terms of quantity, quality or timing) either in part/in full whether due to inability or by decision
What are the two components
- Default risk
- Credit spread risk
Which give examples of credit risk events?
Missed payment
Financial ratio falling below some level
Legal proceedings starting against credit issuer
Present value of A falls below L because of economic factors
What are the two components of default risk
Probability of default
Loss on default
What are the 3 things that must be assessed when assessing default risk
Probability of default
Loss on default
Level and nature of interactions between credit exposures and other risks in a portfolio
Identify sources of information for credit risk
- Credit rating agencies
- Counterparty
- Publicly available data
- Proprietary databases
Outline the items that qualitative assessments of credit risk can be based on
o Nature of contract e.g. seniority of a loan
o Level and nature of security e.g. parental guarantees, collateral
o Nature of borrower e.g. industry sector / employment status
o Economic indicators
o Financial ratios
o Face to face meetings with credit issuer and/or counterparty
Outline the merits of qualitative risk assessments
Advantages:
o Range of (subjective) factors can be incorporated into assessment
Disadvantages:
o Excessive subjectivity
o Inconsistency between ratings
o Meaning of subjective ratings could change over eco cycle and/or due to changes in eco environment
o Ratings might fail to respond to changing eco cycles or circumstances of counterparty- often reluctance to change rating
List examples of quantitative credit models
- Credit scoring
- Structural models
- Reduced form models
- Credit portfolio models
- Credit exposure models
Describe credit scoring models
- Use fundamental info to get likelihood of default
- E.g.
o Empirical models
o Expert models
Outline structural models
- AKA Firm value
- Use share price and volatility
- E.g., KMV and Merton
Explain how the Merton model works
o Uses Black-Scholes option pricing theory along with equity share price volatility to get info on value of total A and value of D
o Considers total A = total E + total D
o D is zero-coupon bond redeemable at some future t
o Total A assumed to follow geometric Brownian motion (continuous-time lognormal random walk)
o Shareholders can be thought of as call option holders of total A
o If A > nominal value of D by t then D repaid and sh get residual A
o Nominal value of D is strike price of call
o If A < nominal value of D by t then sh get nothing aka call not exercised
o Equity shares are like call options and can be valued using option-pricing theory and B-S
o D valued as diff between A and E
o Equivalentlt, by Put-call parity, value of D = value of risk free bond – value of put on company’s total A
o Idea: if A increase in value, bh get same amount at maturity as holder of risk free bond
o If A<nominal value of D, equity sh default and bh lose diff between total A at redemption and nominal value of D
Outline the pros of the Merton model
Mathematically tractable using B-S option pricing results
Intuitive results, eco explanation for P(default) as based on capital structure of co and changes in co value
Can estimate appropriate credit spread for bond if unquoted or unrated
Outline the cons of the Merton model
- Assumptions of:
Frictionless markets (no transaction costs) with continuous trading
Risk free rate deterministic and constant for borrowers and lenders
X_t follows lognormal random walk with fixed growth rate and volatility independent of firm financial structure which is unrealistic assumption
Bond is zero-coupon with one defalt opportunity
Default = liquidation- can mean diff things in real life - Can only be solved when X_t and sigma are observable- impossible
- Accurate sigma estimate needed»_space; more appropriate for larger cos with frequently traded stocks
- Results sensitive to market sentiments in absence of real changes
Outline how the KMV model works
o Uses Merton’s concept: company will default first instance X_t falls below (or some B^ based on term structure of liabilities, usually 1 year L)
o Distance to Default(DD): # of std deviations company’s A must fall in value before breaching B
DD(t)=[X(t)-B]/[X(t)*σ(x)]
o Use empircal data on co defaults and how linked to DD to get P(Default)