MODEL VERDICT
Americold Realty Trust, Inc. (COLD) — Relative Valuation
Peer multiples, Monte Carlo simulation & quality-adjusted fair value
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Peer multiples, Monte Carlo simulation & quality-adjusted fair value
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 28, 2026 | MODERATE | 0.66 | $13.39 | CURRENT | — |
| Feb 21, 2026 | MODERATE | 0.66 | $13.41 | CURRENT | — |
| Feb 14, 2026 | MODERATE | 0.69 | $12.36 | CURRENT | — |
| Feb 11, 2026 | MODERATE | 0.69 | $12.87 | CURRENT | — |
| Jan 11, 2026 | MODERATE | 0.69 | $13.28 | Pending | -4.0% |
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 18 industry peers | $3.09 | -76.9% | 15% | A- | Peer Data |
| Price / Book 23 industry peers | $21.22 | +58.5% | 8% | B | Model Driven |
| EV To Revenue 20 industry peers | $101.55 | +658.4% | 3% | B | Data |
| Price / Sales 20 industry peers | $80.12 | +498.4% | 2% | B | Model Driven |
| Weighted Output Blended model output | $41.20 | +207.7% | 100% | 72 | SIGNIFICANTLY UNDERVALUED |
Cross-sectional regression predicting expected multiples based on growth, margins, ROIC, and beta.
| Multiple | Avg | Median | Min | Max | Std |
|---|---|---|---|---|---|
| EV/EBIT | 151.92 | 129.48 | 59.29 | 302.59 | 94.24 |
| EV/EBITDA | 28.70 | 26.87 | 20.06 | 48.00 | 9.23 |
| P/FFO | 90.04 | 29.59 | 14.54 | 476.24 | 170.40 |
| P/TBV | 4.01 | 4.17 | 2.88 | 5.24 | 0.75 |
| P/B Ratio | 2.16 | 2.04 | 1.26 | 3.52 | 0.69 |
| Div Yield | 0.03 | 0.03 | 0.02 | 0.04 | 0.01 |
| P/S Ratio | 2.87 | 3.12 | 1.41 | 3.89 | 0.84 |
Based on our peer multiples analysis with 11 valuation metrics, the model estimates COLD's fair value at $41.20 vs the current price of $13.39, implying +207.7% upside potential. Model verdict: Significantly Undervalued. Confidence: 72/100. This is a quantitative estimate, not a recommendation.
The blended fair value of $41.20 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 $12.21 (P10) to $154.28 (P90), with a median of $53.71.
COLD's current P/E of -33.5x compares to the industry median of 27.2x (15 peers in the group). This represents a -222.9% discount to the industry. The historical average P/E is N/Ax over 0 years. Signal: Deep Discount.
19 analysts cover COLD with a consensus rating of Buy. The consensus price target is $14.11 (range: $11.00 — $18.00), implying +5.4% upside from the current price. Grade breakdown: Strong Buy (0), Buy (10), Hold (8), Sell (1), Strong Sell (0).
The model confidence score is 72/100, based on: data completeness (18), peer quality (25), historical depth (20), earnings stability (5), 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 COLD.
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.