商业信贷风险参数计算(PDF 74页)

Abstract
Under the Basel II regime, banks can choose among different approaches to
measure the regulatory capital to underpin their risky assets. From the point
of view of the amount of capital required, the Retail IRB Approach can be very
advantageous. To satisfy its requirements, banks have to estimate sensible values
for the risk parameters Probability of Default (PD) and Loss Given Default (LGD)
on the basis of their own default and loss data. In part due to the segmentation
rules particular to the Retail IRB Approach, this is very difficult, and the simple
calculation of relative frequencies will not do in general – the sample data do not
allow one to make a sensible distinction between the structure of the default and
loss densities and the randomness of the sample data, as we see in this thesis;
all methods we derive for computing risk parameters are developed using real
bank data.
We describe a method to estimate PD using the construction of a Lorenz curve
based on scoring results. While Lorenz curves usually are means to compute
efficiency ratios, we show how a Lorenz curve can serve as a vehicle to define the
borderline between structure and randomness. Values for PD can be obtained
from it in a direct way. What makes it specifically suitable for this purpose
are some invariancy properties; we show this in general and by way of sample
data of a real retail portfolio. We further compare this method to multivariate
methods, and propose a multi-component system to balance the complementary
advantages and disadvantages of both approaches.
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