Mid Penn Bancorp, Inc.
MPB scores 56.7 on the Conservative profile, blending a fundamental score (80% weight, emphasizing quality and stability (84% of fundamental weight)) with a machine-learning signal (20% weight) trained on 82 features across 30 years of data.
Net penalties of -15.0 points significantly impact the ranking. Without these adjustments, MPB would rank considerably higher.
These features are direct inputs to the machine learning model. The model was trained on these signals alongside 100 features (including 12 momentum/technical indicators) to produce the ML percentile score.
| Stock | Score | P/E | Rev Growth | Margin | Mkt Cap |
|---|---|---|---|---|---|
| MPB | 56.7 | 13.9 | 6.6% | 16.2% | $780M |
| CME | 84.9 | 27.2 | 9.9% | 57.5% | $109.0B |
| CINF | 82.3 | 10.7 | 11.4% | 18.9% | $25.4B |
| ACT | 82.0 | 8.9 | 2.4% | 54.6% | $6.0B |
| SEIC | 80.9 | 14.0 | 10.7% | 27.3% | $9.6B |
| TROW | 79.3 | 10.1 | 3.1% | 28.5% | $20.5B |
| FHB | 78.3 | 11.8 | 3.2% | 24.2% | $3.3B |
| MCHB | 77.7 | 0.0 | 123.7% | 23.2% | $3.4B |
| TRMK | 75.6 | 11.9 | 34.8% | 19.3% | $2.7B |
| BCAL | 74.3 | 9.9 | 26.2% | 27.1% | $613M |
| NMIH | 73.9 | 7.7 | 8.4% | 55.1% | $3.0B |
| FFIN | 73.2 | 18.8 | 11.7% | 30.7% | $4.8B |
| TW | 73.1 | 30.0 | 18.9% | 39.6% | $24.8B |
| VCTR | 73.1 | 18.3 | 8.8% | 32.3% | $4.9B |
| VLY | 72.4 | 12.5 | -2.2% | 17.1% | $7.5B |
| QQQX | 72.3 | 10.4 | 48.6% | 257.3% | $1.4B |
| Sector Average | 45.8 | 49.4 | 13.4% | -2.8% | — |
This stock has limited trading volume and/or float. Institutional investors may face difficulty entering or exiting positions without significant price impact. A post-hoc penalty has been applied to the composite score (this is not a backtested model factor — it is a practical tradability overlay).
| Year | Low | High | Range | Status |
|---|---|---|---|---|
| 2021 | $23.52 | $33.89 | 36.1% | Wide |
| 2022 | $24.81 | $34.99 | 34% | Moderate |
| 2023 | $18.25 | $32.61 | 56.5% | Wide |
| 2024 | $19.20 | $33.87 | 55.3% | Wide |
| 2025 | $22.50 | $33.24 | 38.5% | Wide |
Scores are generated by a multi-stage ML pipeline combining fundamental analysis, ensemble predictions, and structural risk signals. All data is for research purposes only and does not constitute financial advice. Past performance does not guarantee future results.