MODEL VERDICT
Green Plains Inc. (GPRE)
Relative Valuation•Peer multiples, Monte Carlo simulation & quality-adjusted fair value
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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 |
|---|---|---|---|---|---|
| May 1, 2026 | NEUTRAL | 0.18 | $17.76 | CURRENT | — |
| Apr 24, 2026 | NEUTRAL | 0.18 | $15.92 | CURRENT | — |
| Apr 17, 2026 | NEUTRAL | 0.18 | $14.82 | CURRENT | — |
| Apr 16, 2026 | NEUTRAL | 0.18 | $15.41 | CURRENT | — |
| Apr 10, 2026 | NEUTRAL | 0.34 | $15.23 | CURRENT | — |
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 |
|---|---|---|---|---|---|
| Forward P/E 7 analyst estimates | $5.61 | -68.4% | 20% | A- | Analyst Est. |
| Price / Free Cash Flow 4 industry peers | $11.76 | -33.8% | 15% | B+ | Peer Data |
| EV/FCF 4 industry peers | $8.69 | -51.1% | 7% | B | Model Driven |
| EV To Revenue 7 industry peers | $26.89 | +51.4% | 4% | B | Data |
| Price / Sales 7 industry peers | $33.46 | +88.4% | 3% | B | Model Driven |
| FCF Yield 4 industry peers | $9.52 | -46.4% | 1% | B | Data |
| Weighted Output Blended model output | $8.73 | -50.8% | 100% | 70 | SIGNIFICANTLY OVERVALUED |
Cross-sectional regression predicting expected multiples based on growth, margins, ROIC, and beta.
| Multiple | Avg | Median | Min | Max | Std |
|---|---|---|---|---|---|
| EV/EBITDA | 39.36 | 37.22 | 16.90 | 66.11 | 22.55 |
| P/FFO | 147.48 | 74.76 | 62.47 | 305.20 | 136.74 |
| P/TBV | 1.08 | 0.86 | 0.60 | 1.67 | 0.47 |
| P/B Ratio | 1.05 | 0.86 | 0.59 | 1.60 | 0.45 |
| Div Yield | 0.02 | 0.01 | 0.01 | 0.05 | 0.02 |
| P/S Ratio | 0.36 | 0.32 | 0.24 | 0.57 | 0.13 |
Based on our peer multiples analysis with 15 valuation metrics, the model estimates GPRE's fair value at $8.73 vs the current price of $17.76, implying -50.8% downside potential. Model verdict: Significantly Overvalued. Confidence: 70/100. This is a quantitative estimate, not a recommendation.
The blended fair value of $8.73 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 $6.59 (P10) to $10.02 (P90), with a median of $8.24.
GPRE's current P/E of -9.9x compares to the industry median of 24.9x (7 peers in the group). This represents a -139.6% discount to the industry. The historical average P/E is N/Ax over 0 years. Signal: Deep Discount.
20 analysts cover GPRE with a consensus rating of Buy. The consensus price target is $13.80 (range: $10.00 — $17.00), implying -22.3% upside from the current price. Grade breakdown: Strong Buy (0), Buy (13), Hold (6), Sell (1), Strong Sell (0).
The model confidence score is 70/100, based on: data completeness (18), peer quality (25), historical depth (20), earnings stability (5), and model agreement (2). 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 GPRE.
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.