GTLS (GTLS)
Quantitative Summary
DeterministicFinancial health is average: Piotroski 5/9, Altman Z 1.7.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe capital allocation efficiency for GTLS is severely compromised, as evidenced by a negative ROIC-WACC spread of -9.2%, indicating that the company currently destroys value relative to its cost of equity. This fundamental weakness persists despite a Piotroski F-Score of 5/9 and a Beneish M-Score of -2.46 suggesting low earnings manipulation risk, while the Altman Z-Score of 1.7 flags potential distress in balance sheet solvency. The DuPont decomposition reveals a stark contrast between robust gross margins at 33.7% and negligible net profitability at just 0.9%, driven by minimal revenue growth of only 2.5% year-over-year, which fails to generate the leverage or turnover required to sustain shareholder returns.
Valuation metrics present extreme dissonance with underlying operational performance, as the current price-to-earnings ratio stands at an anomalous 626.7x compared to a DCF-derived fair value of $40 per share. This massive disparity implies that market pricing is detached from intrinsic value calculations based on projected cash flows and growth assumptions inherent in the discounted model. The elevated multiple suggests investors may be anticipating significant future earnings acceleration or qualitative catalysts not yet reflected in current financial statements, creating a scenario where price sensitivity to any downside revision would be magnified by the lack of near-term profit generation.
While specific risk factor deltas regarding Fama-French alpha or insider trading activity were not provided in the dataset to synthesize a precise risk-reward profile, the combination of negative economic spread and distressed Altman metrics introduces substantial downside volatility potential. The divergence between high gross margins and low net income further complicates the investment thesis, as cost structure inefficiencies continue to erode top-line gains without corresponding leverage improvements.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
DCF Sandbox
InteractiveSensitivity Matrix
| TG ↓ / WACC → | 10.5% | 12.5% | 14.5% |
|---|---|---|---|
| 2% | $58 | $32 | $15 |
| 3% | $72 | $40 | $20 |
| 4% | $90 | $50 | $26 |
Center = base case. Green = >10% upside, Red = >10% downside vs —.
Pre-computed DCF: WACC=12.5%, terminal growth 3%. Fair value $40 (+0.0%). Not investment advice.
Price Chart with Moving Averages
Quant Health Deep Dive
Profitability & Value Creation
✅ Conservative payout — room for dividend increases.
Balance Sheet Health
Earnings Surprise History
EPS estimates vs actuals for the most recent reported quarters. Source: yfinance.
Underwater (Drawdown from Peak)
How far below the all-time high the price has been over time. Deeper = more pain for holders.
Rolling 60-Day Beta vs S&P 500 (VOO)
How the stock's sensitivity to market moves changes over time. β > 1 = more volatile than the market.
Fundamentals
Passive Flow Attribution
ETF Draft EffectWhen investors buy or sell ETFs like MDYG or VBK, the fund manager is mechanically forced to buy or sell GTLS shares regardless of GTLS's individual fundamentals. We estimate $582M of passive capital is structurally linked to GTLS through 8 tracked ETFs. Passive flows have a limited but growing influence on GTLS's daily trading dynamics.
Passive exposure = Σ (ETF AUM × stock weight in ETF) across 8 tracked ETFs. Actual passive ownership is larger (includes mutual funds). Not investment advice.
ETF Contagion Visualizer
Simulate a price drop in GTLS to visualize passive redemption contagion across ETFs and collateral stocks.
If GTLS (GTLS) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies FLEX LTD (FLEX) as the most exposed collateral stock, sharing 2 ETFs with GTLS. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 9 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
GTLS Ownership Dynamics
ETFs with Highest GTLS Exposure
Float lock-up computed from 9 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
GTLS Capital Efficiency
How efficiently does GTLS convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.
GTLS converts 34% of its EBITDA into free cash flow, a moderate conversion rate — significant EBITDA is consumed by capital expenditures, working capital changes, or interest payments. The 66% reinvestment rate signals aggressive capacity expansion. However, the ROIC-WACC spread is negative (-9.2%), suggesting reinvested capital is destroying shareholder value.
Capital efficiency = Free Cash Flow ÷ EBITDA. Reinvestment = (EBITDA − FCF) ÷ EBITDA. Metrics from latest annual filings. Not investment advice.
Fails-to-Deliver (FTD) History
SEC-reported settlement failures. Elevated FTDs can indicate high short-selling pressure, operational settlement issues, or naked shorting activity.
| Date | Failed Shares | Close Price | Notional Value |
|---|---|---|---|
| 2026-05-06 | 22 | $207.75 | $4,570.5 |
| 2026-04-27 | 828 | $207.85 | $172,099.8 |
| 2026-04-21 | 21,929 | $208.13 | $4.6M |
| 2026-04-09 | 2,674 | $207.76 | $555,550.24 |
| 2026-03-26 | 19 | $207.24 | $3,937.56 |
| 2026-03-25 | 75 | $207.05 | $15,528.75 |
| 2026-03-11 | 49 | $206.81 | $10,133.69 |
| 2026-03-10 | 8,035 | $207.20 | $1.7M |
| 2026-02-23 | 201 | $207.17 | $41,641.17 |
| 2026-02-04 | 249 | $207.40 | $51,642.6 |
| 2026-02-03 | 86 | $207.45 | $17,840.7 |
| 2026-01-20 | 375 | $207.41 | $77,778.75 |
| 2026-01-13 | 114 | $206.71 | $23,564.94 |
| 2026-01-07 | 118 | $206.25 | $24,337.5 |
| 2025-12-29 | 646 | $205.85 | $132,979.1 |
| 2025-12-24 | 601 | $205.97 | $123,787.97 |
| 2025-12-23 | 6 | $205.90 | $1,235.4 |
| 2025-12-22 | 1,046 | $205.91 | $215,381.86 |
| 2025-12-18 | 429 | $205.61 | $88,206.69 |
| 2025-12-15 | 11 | $205.78 | $2,263.58 |
| 2025-12-12 | 11 | $205.60 | $2,261.6 |
| 2025-12-10 | 125 | $205.40 | $25,675 |
| 2025-12-04 | 1,311 | $204.96 | $268,702.56 |
| 2025-12-02 | 202 | $204.04 | $41,216.08 |
| 2025-12-01 | 205 | $203.95 | $41,809.75 |
| 2025-11-25 | 4 | $203.85 | $815.4 |
| 2025-11-24 | 735 | $203.50 | $149,572.5 |
| 2025-11-21 | 4 | $203.41 | $813.64 |
| 2025-11-17 | 79 | $203.54 | $16,079.66 |
| 2025-11-14 | 79 | $203.52 | $16,078.08 |
Source: SEC Regulation SHO FTD data. Data is reported with a ~30 day delay. High FTD quantities relative to average daily volume may indicate settlement stress.
Compare GTLS to Peers
Quant metrics computed deterministically from financial statements and price data. Updated: N/A.
SecuritiesDB provides programmatic data aggregation for informational purposes only. None of the metrics, summaries, or algorithmic flags constitute a recommendation to buy or sell any security.