- Use mechanism of “convolution”
- Use Bayesian theorem for the weight of default for each grade, i.e. the probability that a default occurred in a specific grade
- Use the binomial distribution to predict the probability that the number of defaults differs from the number of defaults in the grade
- Use then Poisson distribution to take into account the number of customers in each grade to generate a frequency distribution
- The use a convolution mode to combine the information and produce de matrix (how it is done is not clear)
- PD depend on number of customers in grades and changes over time. As such it is dynamic. How it is applied in practice is not clear
Estimation of Probability of Defaults (PD) for Low Default Portfolios: An actuarial Approach
Original by Nabil Iqbal, Syed Afraz Ali, 2012, 18 pagesThis summary note was posted on 15 January 2017, by Reinie in Credit risk Finance
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