MODEL VERDICT
Alpine Income Property Trust, Inc. (PINE)
Relative Valuation•Peer multiples, Monte Carlo simulation & quality-adjusted fair value
Popular:
Composite score derived from valuation, quality, and risk factors
Quantitative model thresholds · For educational and research purposes only
Each row records the model's monthly assessment. High Conviction = the model detected notable undervaluation vs peers. Neutral = no notable divergence was found. The return column shows the actual price change over 90 days for reference. This is a quantitative observation log — not investment advice.
| Date | Assessment | Score | Price | Status | 90d Fwd Return |
|---|---|---|---|---|---|
| Feb 21, 2026 | NEUTRAL | 0.43 | $20.03 | CURRENT | -4.0% |
| Feb 14, 2026 | NEUTRAL | 0.40 | $20.53 | Below threshold | -5.2% |
Historical model observations for research purposes only. Past quantitative patterns do not predict future results. Not a recommendation to buy, sell, or hold any security.
| Methodology | Fair Value | vs Current | Weight | Quality | Status |
|---|---|---|---|---|---|
| EV/EBITDA 23 industry peers | $40.85 | +103.9% | 15% | A- | Peer Data |
| Dividend Yield 14 industry peers | $0.91 | -95.5% | 12% | B | Supplementary |
| Price / Book 23 industry peers | $35.54 | +77.4% | 8% | B | Model Driven |
| Forward P/E 22 analyst estimates | $14.22 | -29.0% | 5% | A- | Analyst Est. |
| EV To Revenue 23 industry peers | $41.51 | +107.2% | 3% | B | Data |
| Price / Sales 23 industry peers | $29.99 | +49.7% | 2% | B | Model Driven |
| Weighted Output Blended model output | $23.07 | +15.2% | 100% | 75 | UNDERVALUED |
Cross-sectional regression predicting expected multiples based on growth, margins, ROIC, and beta.
| Multiple | Avg | Median | Min | Max | Std |
|---|---|---|---|---|---|
| P/E Ratio | 69.80 | 65.64 | 8.79 | 136.27 | 52.94 |
| EV/EBIT | 45.22 | 39.99 | 12.26 | 103.45 | 30.63 |
| EV/EBITDA | 13.27 | 14.17 | 6.30 | 19.30 | 4.61 |
| P/FCF | 13.04 | 13.10 | 9.89 | 18.07 | 3.35 |
| P/FFO | 10.25 | 9.18 | 4.90 | 16.88 | 3.68 |
| P/TBV | 1.13 | 1.11 | 0.95 | 1.33 | 0.12 |
| P/B Ratio | 0.91 | 0.92 | 0.81 | 0.99 | 0.06 |
| Div Yield | 0.04 | 0.05 | 0.00 | 0.07 | 0.03 |
| P/S Ratio | 6.63 | 5.78 | 4.30 | 11.35 | 2.35 |
Based on our peer multiples analysis with 18 valuation metrics, the model estimates PINE's fair value at $23.07 vs the current price of $20.03, implying +15.2% upside potential. Model verdict: Undervalued. Confidence: 75/100. This is a quantitative estimate, not a recommendation.
The blended fair value of $23.07 is calculated using four lenses: industry median multiples (40%), historical multiples (30%), forward estimates (20%), and quality-adjusted multiples (10%). Monte Carlo simulation (10,000 iterations) gives a range of $16.93 (P10) to $24.11 (P90), with a median of $20.49.
PINE's current P/E of -91.0x compares to the industry median of 23.5x (22 peers in the group). This represents a -488.2% discount to the industry. The historical average P/E is 69.8x over 6 years. Signal: Deep Discount.
12 analysts cover PINE with a consensus rating of Buy. The consensus price target is $20.50 (range: $20.00 — $21.00), implying +2.3% upside from the current price. Grade breakdown: Strong Buy (0), Buy (10), Hold (2), Sell (0), Strong Sell (0).
The model confidence score is 75/100, based on: data completeness (22), peer quality (25), historical depth (20), earnings stability (4), and model agreement (4). Cyclicality penalty: -0 points. The model shows strong agreement across inputs.
The model flags several key risks: (1) Macro/regulatory risks are not captured in this model but remain material.
Peak earnings risk data is not available for PINE.
No. This dashboard is a quantitative research tool for educational and informational purposes only. It is not investment advice, a solicitation, or a recommendation to buy, sell, or hold any security. The operator of this platform is not a registered investment advisor (RIA), broker-dealer, or financial planner. All model outputs, fair value estimates, signals, and scenarios are the result of automated quantitative computations and should not be construed as professional financial guidance. You should consult a qualified, licensed financial advisor before making any investment decisions. Past model performance is not indicative of future results.