3.1.Hull Ch 22

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Exam9
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3.1.Hull Ch 22
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2011-02-08 20:39:06
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Hull
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  1. Bond rating classification
    Bonds above BBB rating are considered investment grade, while lower rated bonds are considered speculative.
  2. 3 ways to estimate bond default probabilities
    • Historical: collect data from firms that start w/ same credit rating
    • From bond price: bond price already reflects expected loss from default. Approximate: s = h(1 - R). Exact: PV(loss) = PV(bond @ rf) - PV(bond @ y)
    • Using equity price: unless the 2 previous techniques this one is not subject to infrequently updated ratings. Instead it infers the bond price at any time from firm's stock price, where p(default) = N(-d2)
  3. 3 credit risk mitigation methods
    • Netting: net any transaction for which money is due against amts that may be owed to that same counterparty
    • Collateral requirementes: in form of cash or mktable securities
    • Downgrade trigger: certain actions occur upon credit downgrade
  4. 2 approaches to model default bond correlation
    • Structural models: correlate stochastic processes
    • Reduced form models: assume hazard rates for different companies follow a stochastic process and are correlated w/ macroeconomic variables
  5. Define copula
    Multivariate distribution of 2 or more rdm variables which are both between 0 and 1. It can be used to describe the degree to which 2 or more probabilities are dependent on each other.
  6. Gaussian Copula
    • Suppose tA and tB are the times to default
    • x = N-1[Q(t)], where Q(t) is the cum p(default)
    • Then x is a normally dist rdm var
    • The joint probability of A and B defaulting can be generated from a multivariate normal dist by calculating the prob of observing these transformed variables xA and xB from a joint standard normal dist w/ a correlation coeff ρ
    • One-factor model: xi = ai + √(1 - ai²)Zi
    • Q(T|F) = N[N-1[Q(t)] - √(ρ)F] / √(1 - ρ)
  7. Credit VaR
    • Attempts to determine a dollar amt that credit losses will not exceed w/ some high prob.
    • Time horizon is usually a year or more.
    • Gaussian copula: V(X,T) = N[N-1[Q(t)] + √(ρ)N-1(X)]/√(1-ρ)
    • Credit metrics model: use credit migration matrix to simulate credit rating changes

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