信用风险模型(PPT 57页)

Conditional Vs Currently, most models are unconditional (independent from the state of Unconditional economy). Using these models, risk can understated or overstated depending
on the location within the business cycle?
Adapted from “Credit Risk Modelling: Current Practices and Applications”, April 1999, by Basle Committee on Banking Supervision
default (LGD) sensitivity analysis with respect to LGD. Lack of historical data to validate
currently used models.
Risk ratings, In determining EDF and migration probabilities, Internal rating systems may
Note: Some adjustments are made to collateralized/guaranteed loans to OECD governments, banks, and sec Model Vs Credit Risk Models
Current Issues in Credit Risk Modelling
Topic Loss given
Parameter Specification Issues/Concerns LGD is random; hence, a distribution is needed to represent LGD. Lack of
The capital requirement to cover unexpected loss decreases rapidly as the number of counterparties becomes larger.
Unexpected loss
8%
Assumption: All loans are of equal size, and correlations between different counterparties are 0.15.
Current Issues in Credit Risk Modelling
Topic Credit spreads
Parameter Specification Issues/Concerns For Mark-to-Market models, how much spread should be used to value loans at each credit rating? Are the forward spreads (based on today yield curve) a good approximation of the future spreads? How is "liquidity" element of credit spreads taken into account?
BIS Regulatory Model Vs Credit Risk Models
Default correlations can have significant impact on portfolio potential loss. KMV finds that correlations typically lie in the range 0.002 to 0.15.
Computational Some models are computationally intensive. requirement
Adapted from “Credit Risk Modelling: Current Practices and Applications”, April 1999, by Basle Committee on Banking Supervision
Exposure levels Different instruments (especially market driven instruments) have different levels of risk exposure (e.g. swaps vs loans). Estimates are made to make different instruments comparable. The accuracy of estimates is questionable.
Probability
No agreement on the "family" of distributions to use. Loss distribution is not
density function normal; it empirically has "fatter tails".
Correlation of How should co-movement among rating migrations and defaults be modeled? credit events Implicit or explicit?
Risk drivers
When does default actually occur? In the threshold models, what observable variable should be used to represent "ability to pay"?
Model concept Is the model that starts from a pool of similar loans or obligors realistic? Pooled data usually hide "credit specific" risks.
expected default not be accurate or have enough history. EDF and migration probabilities of
frequency
publicly traded bonds may not be accurate for bank credits. Most systems
BIS Risk-Based Capital Requirements
All private-sector loans (uncollateralized) are subjected to an 8 percent capital reserve requirement, irrespective of the size of the loan, its maturity, and the credit quality of the borrowing counterparty.
Credit Risk Models - Credit Risk+ - Credit Metrics - KMV - Other similar models
BIS Regulatory Model Vs Credit Risk Models
Disadvantages of BIS Regulatory Model 1. Does not capture credit-quality differences among
3.54%
1
16
# of counterparties
Current Issues in Credit Risk Modelling
Topic Definition of risk
Conceptual Issues/Concerns Should credit risk include only default or both default and rating migrations? Is there a material difference between the default mode and the mark-to-market mode models?
BIS Regulatory Model Vs Credit Risk Models
Big difference in probability of default exists across different credit qualities.
Credit Rating Probability of Default
(EDF), and combine EDF and LGD.
migration
probabilities
Migration and Is it reasonable to use equity information to estimate correlations for bank
default
credits? Lack of historical data to validate models used to estimate this
correlations parameter.
Adapted from “Credit Risk Modelling: Current Practices and Applications”, April 1999, by Basle Committee on Banking Supervision
8%
8%
8% 8%
Correlation = 1 Correlation = 0.15