1 Introduction
2 Time evolution of credit ratings
2.1 Estimation of transition probabilities
2.2 Markov chain reduction method
2.3 Conditional expected time to default
3 Data and identification of credit quality ratings
Classification symbol | Description | Assigned number (sec) |
---|---|---|
– | All nonfinancial corporate sectors of the Polish economy | 0 |
B | Mining | 1 |
C | Manufacturing | 2 |
D | Electricity, gas, and steam supply | 3 |
E | Water supply, sewerage, waste management | 4 |
F | Construction | 5 |
G | Retail trade and repairs | 6 |
H | Transportation and storage | 7 |
I | Hotels and restaurants | 8 |
J | Information and communication | 9 |
L | Real estate activities | 10 |
M | Professional, scientific, and technical activities | 11 |
N | Administrative activities | 12 |
P | Education | 13 |
Q | Health care | 14 |
R | Arts, entertainment, and recreation | 15 |
S | Other services | 16 |
4 Empirical results
4.1 Performance of corporate loans from main economic sectors
4.2 Alternative estimates of probability transition matrices
“crisis” scenario | End of sample | |
---|---|---|
GDP growth (\(x_1\)) | 1.00% | 3.94% |
Interest rate (\(x_2\)) | 6.64% | 1.65% |
Credit growth (\(x_3\)) | \(-\) 4.00% | 5.33% |
\(\mathrm{CETD}_{0.05}\)
| 4.07 | 5.95 |
\(\mathrm{CETD}_{0.10}\)
| 5.87 | 9.39 |
\(\mathrm{VaR}_{0.05}\)
| 7.00 | 10.00 |
\(\mathrm{VaR}_{0.10}\)
| 10.00 | 16.00 |
\(\mathrm{PD}(1Y) \times 100\)
| 2.72 | 1.33 |
“crisis” scenario | End of sample | |||
---|---|---|---|---|
Shocks to output growth (\(\varDelta x_1\)) | \(-\,1\) pp | 1 pp | \(-\,1\) pp | 1 pp |
\(\varDelta \mathrm{CETD}_{0.05}\)
| \(-\) 1.19 | 3.07 | \(-\)0.58 | 1.05 |
\(\varDelta \mathrm{CETD}_{0.10}\)
| \(-\) 1.65 | 5.90 | \(-\) 1.09 | 1.97 |
\(\varDelta \mathrm{VaR}_{0.05}\)
| \(-\) 2.00 | 6.00 | \(-\) 1.00 | 2.00 |
\(\varDelta \mathrm{VaR}_{0.10}\)
| \(-\) 3.00 | 12.00 | \(-\) 2.00 | 4.00 |
\(\varDelta \mathrm{PD}(1Y) \times 100\)
| 0.40 | \(-\) 0.49 | 0.21 | \(-\) 0.27 |
“crisis” scenario | End of sample | |||
---|---|---|---|---|
Shocks to interest rate (\(\varDelta x_2\)) | \(-1\) pp | 1 pp | \(-1\) pp | 1 pp |
\(\varDelta \mathrm{CETD}_{0.05}\)
| 0.00 | \(-\) 0.01 | 0.01 | \(-\) 0.03 |
\(\varDelta \mathrm{CETD}_{0.10}\)
| 0.01 | \(-\) 0.01 | \(-\) 0.61 | 0.59 |
\(\varDelta \mathrm{VaR}_{0.05}\)
| 0.00 | 0.00 | 0.00 | 0.00 |
\(\varDelta \mathrm{VaR}_{0.10}\)
| 0.00 | 0.00 | \(-\) 1.00 | 1.00 |
\(\varDelta \mathrm{PD}(1Y) \times 100\)
| 0.03 | \(-\) 0.04 | 0.08 | \(-\) 0.09 |
“crisis” scenario | End of sample | |||
---|---|---|---|---|
Shocks to credit growth (\(\varDelta x_3\)) | \(-\,5\) pp | 5 pp | \(-\,5\) pp | 5 pp |
\(\varDelta \mathrm{CETD}_{0.05}\)
| \(-\) 0.49 | 0.99 | \(-\) 0.54 | 0.49 |
\(\varDelta \mathrm{CETD}_{0.10}\)
| \(-\) 0.95 | 1.34 | \(-\) 0.41 | 0.95 |
\(\varDelta \mathrm{VaR}_{0.05}\)
| \(-\) 1.00 | 2.00 | \(-\) 1.00 | 1.00 |
\(\varDelta \mathrm{VaR}_{0.10}\)
| \(-\) 2.00 | 3.00 | \(-\) 1.00 | 2.00 |
\(\varDelta \mathrm{PD}(1Y) \times 100\)
| 0.13 | \(-\) 0.14 | 0.08 | \(-\) 0.08 |