Campbell–thompson (C-T) test results for in-sample and out-of-sample forecasts: ADL-MIDAS with green innovation versus AR benchmark
| ADL-MIDAS (PCR) vs AR | ADL-MIDAS (TCR) vs AR | |||||||
|---|---|---|---|---|---|---|---|---|
| In-sample | Out-of-Sample | In-sample | Out-of-sample | |||||
| h = 4 | h = 8 | h = 12 | h = 4 | h = 8 | h = 12 | |||
| Communication service | 0.6678 | 0.7145 | 0.7337 | 0.8248 | 0.6224 | 0.6735 | 0.6952 | 0.7995 |
| Consumer discretionary | 0.5232 | 0.5205 | 0.4693 | 0.4902 | 0.5699 | 0.5512 | 0.4926 | 0.5125 |
| Consumer staple | 0.6291 | 0.6029 | 0.5790 | 0.6416 | 0.6318 | 0.5893 | 0.5250 | 0.5956 |
| Energy | 0.0366 | 0.0402 | 0.1477 | 0.1128 | 0.0881 | 0.0890 | 0.1900 | 0.1569 |
| Financial | 0.0852 | 0.0773 | 0.1091 | 0.1216 | 0.0932 | 0.0984 | 0.1050 | 0.1176 |
| Health care | 0.7336 | 0.7419 | 0.7537 | 0.7590 | 0.7487 | 0.7462 | 0.7569 | 0.7621 |
| Industrial | 0.5061 | 0.4924 | 0.3874 | 0.3829 | 0.5584 | 0.5385 | 0.4327 | 0.4285 |
| Information technology | 0.7759 | 0.7754 | 0.7504 | 0.7901 | 0.7749 | 0.7756 | 0.7589 | 0.7972 |
| Material | 0.4217 | 0.4185 | 0.4020 | 0.5288 | 0.4773 | 0.4664 | 0.4291 | 0.5501 |
| Real estate | 0.9903 | 0.9911 | 0.9920 | 0.9924 | 0.9901 | 0.9902 | 0.9913 | 0.9918 |
| Utility | −2.6369 | −2.1915 | −2.2121 | −2.1011 | −1.7606 | −1.4225 | −1.6233 | −1.3344 |
| ADL-MIDAS (PCR) vs AR | ADL-MIDAS (TCR) vs AR | |||||||
|---|---|---|---|---|---|---|---|---|
| In-sample | Out-of-Sample | In-sample | Out-of-sample | |||||
| h = 4 | h = 8 | h = 12 | h = 4 | h = 8 | h = 12 | |||
| Communication service | 0.6678 | 0.7145 | 0.7337 | 0.8248 | 0.6224 | 0.6735 | 0.6952 | 0.7995 |
| Consumer discretionary | 0.5232 | 0.5205 | 0.4693 | 0.4902 | 0.5699 | 0.5512 | 0.4926 | 0.5125 |
| Consumer staple | 0.6291 | 0.6029 | 0.5790 | 0.6416 | 0.6318 | 0.5893 | 0.5250 | 0.5956 |
| Energy | 0.0366 | 0.0402 | 0.1477 | 0.1128 | 0.0881 | 0.0890 | 0.1900 | 0.1569 |
| Financial | 0.0852 | 0.0773 | 0.1091 | 0.1216 | 0.0932 | 0.0984 | 0.1050 | 0.1176 |
| Health care | 0.7336 | 0.7419 | 0.7537 | 0.7590 | 0.7487 | 0.7462 | 0.7569 | 0.7621 |
| Industrial | 0.5061 | 0.4924 | 0.3874 | 0.3829 | 0.5584 | 0.5385 | 0.4327 | 0.4285 |
| Information technology | 0.7759 | 0.7754 | 0.7504 | 0.7901 | 0.7749 | 0.7756 | 0.7589 | 0.7972 |
| Material | 0.4217 | 0.4185 | 0.4020 | 0.5288 | 0.4773 | 0.4664 | 0.4291 | 0.5501 |
| Real estate | 0.9903 | 0.9911 | 0.9920 | 0.9924 | 0.9901 | 0.9902 | 0.9913 | 0.9918 |
| Utility | −2.6369 | −2.1915 | −2.2121 | −2.1011 | −1.7606 | −1.4225 | −1.6233 | −1.3344 |
Note(s): The C–T test results are based on the forecast performance comparison of the unrestricted ADL-MIDAS-based predictive model as against the AR process. Hypothetically, a positive C-T statistic or value implies that the unrestricted ADL-MIDAS based predictive model outperforms the AR process and the reverse holds if the statistic is negative
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