MODEL VERDICT
AbCellera Biologics Inc. (ABCL) — Relative Valuation
Peer multiples, Monte Carlo simulation & quality-adjusted fair value
Popular:
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 | NEUTRAL | 0.14 | $3.61 | CURRENT | — |
| Feb 21, 2026 | NEUTRAL | 0.13 | $3.04 | CURRENT | — |
| Feb 14, 2026 | NEUTRAL | 0.13 | $3.10 | CURRENT | — |
| Feb 11, 2026 | NEUTRAL | 0.13 | $3.16 | CURRENT | — |
| Jan 11, 2026 | MODERATE | 0.67 | $4.37 | Pending | -26.3% |
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 To Revenue 130 industry peers | $2.29 | -36.6% | 4% | B | Data |
| Price / Sales 130 industry peers | $2.31 | -36.0% | 3% | B | Model Driven |
| Weighted Output Blended model output | $2.98 | -17.5% | 100% | 53 | OVERVALUED |
Cross-sectional regression predicting expected multiples based on growth, margins, ROIC, and beta.
| Multiple | Avg | Median | Min | Max | Std |
|---|---|---|---|---|---|
| P/E Ratio | 46.49 | 29.79 | 20.26 | 89.42 | 37.48 |
| EV/EBIT | 30.70 | 18.55 | 12.71 | 60.85 | 26.28 |
| EV/EBITDA | 30.71 | 18.57 | 11.56 | 62.00 | 27.33 |
| P/FCF | 453.59 | 24.45 | 15.58 | 1320.74 | 750.98 |
| P/FFO | 42.86 | 26.66 | 16.64 | 85.26 | 37.06 |
| P/TBV | 4.62 | 2.35 | 0.89 | 15.48 | 5.58 |
| P/AFFO | 53.27 | 40.54 | 26.81 | 92.46 | 34.63 |
| P/B Ratio | 3.85 | 2.01 | 0.82 | 12.75 | 4.56 |
| P/S Ratio | 25.17 | 21.75 | 6.57 | 45.41 | 16.82 |
Based on our peer multiples analysis with 5 valuation metrics, the model estimates ABCL's fair value at $2.98 vs the current price of $3.61, implying -17.5% downside potential. Model verdict: Overvalued. Confidence: 53/100. This is a quantitative estimate, not a recommendation.
The blended fair value of $2.98 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 $1.72 (P10) to $4.49 (P90), with a median of $3.06.
ABCL's current P/E of -7.4x compares to the industry median of 21.4x (48 peers in the group). This represents a -134.4% discount to the industry. The historical average P/E is 46.5x over 3 years. Signal: Deep Discount.
11 analysts cover ABCL with a consensus rating of Buy. The consensus price target is $20.17 (range: $5.00 — $34.00), implying +458.7% upside from the current price. Grade breakdown: Strong Buy (0), Buy (9), Hold (2), Sell (0), Strong Sell (0).
The model confidence score is 53/100, based on: data completeness (6), peer quality (25), historical depth (16), earnings stability (4), and model agreement (2). Cyclicality penalty: -0 points. The model shows moderate 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 ABCL.
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.