How do rating agencies measure rating migration over time?

Question

AcadiFi · Accepted Answer

A rating transition matrix is a square table showing the probability that an issuer at rating X today will be at rating Y one year later. Rows sum to 100%.

Sample one-year transition matrix (illustrative, not actual S&P data):

| From \ To | AAA | AA | A | BBB | BB | B | CCC | D |
|---|---|---|---|---|---|---|---|---|
| AAA | 90.0% | 9.0% | 0.6% | 0.1% | 0.2% | 0.0% | 0.0% | 0.0% |
| AA | 0.6% | 90.5% | 7.9% | 0.6% | 0.1% | 0.1% | 0.0% | 0.0% |
| A | 0.1% | 2.2% | 91.3% | 5.4% | 0.5% | 0.3% | 0.1% | 0.1% |
| BBB | 0.0% | 0.3% | 5.3% | 87.6% | 5.0% | 1.1% | 0.3% | 0.3% |
| BB | 0.0% | 0.1% | 0.4% | 6.0% | 81.0% | 9.0% | 1.5% | 1.1% |
| B | 0.0% | 0.1% | 0.2% | 0.4% | 5.9% | 78.0% | 9.0% | 4.8% |
| CCC | 0.0% | 0.0% | 0.1% | 0.3% | 0.8% | 7.5% | 60.0% | 27.0% |

Key FRM observations:

1. Diagonal dominance — most issuers stay at the same rating (80-90% for IG).
2. Investment grade is sticky — AAA rarely moves more than one notch.
3. Speculative grade is volatile — CCC has a 27% one-year default probability.
4. Default column shows cumulative PD — squaring the matrix gives two-year PD, cubing gives three-year, etc.

Use cases: calibrating credit VaR models, pricing rating-triggered covenants, and regulatory PD floors under Basel IRB.

How do rating agencies measure rating migration over time?

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