AU · rank #2 · 2026-07-21
TOI
NASDAQ · $535M (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of all factors below. | 3.093 |
|---|---|
| EPS revisions (30d) Change in consensus EPS estimate over the past 30 days ($/share). | +$0.06 |
| Net revisions (30d) Number of analysts revising upward minus downward. | 1 |
| Insider signal (90d) $235,110 across 1 unique buyers. | 3.000 |
| Analyst upside Consensus target $8.40 | +52.7% |
| Momentum acceleration 3-month minus 12-month momentum. | +44.56% |
| Analyst rating 5 = Strong Buy, 1 = Strong Sell. | 5.00 |
| Gross margin TTM | +15.1% |
| 52w high | $6.67 |
| Market cap (USD) | $535M |
The AI research card
Independent qualitative review of each pick before the order is placed. On the rare day the research service is unavailable, the paper book trades on the quant ranking alone and no card appears here.
Summary
Oncology Institute (TOI) is one of the largest value-based community oncology groups in the U.S., generating capitated Medicare Advantage revenue across five states alongside a rapidly scaling specialty pharmacy segment.
Rationale
The 52.7% analyst upside, 100% revision agreement across all four covering analysts, two target raises in 30 days, and a 77% Q1 earnings surprise collectively reinforce the analyst_upside signal as grounded in genuine fundamental inflection—41% revenue growth, a dramatically narrowed net loss, and raised FCF guidance—rather than pure sentiment drift.
Material risks
- 1Heavy reliance on CMS value-based and Medicare Advantage capitated contracts means a federal oncology payment model reset or MA rate cut could simultaneously compress revenue and margins, directly invalidating the improving EBITDA trajectory that underpins analyst target raises.
- 2The $75 million OrbiMed term loan leaves a meaningful debt load on a still-GAAP-loss-making balance sheet, and any slowdown in specialty pharmacy or capitated revenue growth could tighten liquidity before the 2031 maturity, pressuring the FCF guidance that is central to the bull case.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 1 of 3 voted to proceed.