LIF (LIF)
Quantitative Summary
DeterministicFinancial health is average: Piotroski 5/9, Altman Z 5.9.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe fundamental economics of the equity reveal a stark divergence between high profitability and capital efficiency. While net margins at 30.8% and gross margins near 78% indicate potent pricing power or cost advantages, these are being eroded by an ROIC-WACC spread of -9.5%, signaling that returns on invested capital fall significantly short of the required hurdle rate. This inefficiency suggests a DuPont decomposition likely driven by low asset turnover rather than leverage or margin expansion alone. Despite this capital allocation weakness, financial health metrics appear robust; a Piotroski F-Score of 5/9 reflects moderate fundamental strength, while an Altman Z-Score of 5.9 places the firm well within safe territory regarding bankruptcy risk. Furthermore, a Beneish M-Score of -2.39 suggests earnings quality is likely authentic and free from aggressive manipulation.
Valuation metrics present a complex picture where current multiples diverge sharply from intrinsic value estimates. The stock trades at a P/E ratio of 23.5x, which requires context against sector averages to determine if the premium is justified by growth expectations or represents overvaluation given the negative ROIC spread. More critically, a DCF-derived fair value of $32 implies that current market pricing may be detached from fundamentals unless future cash flow assumptions incorporate significant re-rating of capital efficiency or acceleration in revenue compounding beyond historical trends. The market appears to be pricing in sustained high growth, yet this optimism conflicts with the inability of management to generate returns above the cost of equity.
No specific risk factor deltas, insider transaction data, or Fama-French alpha statistics were provided for synthesis; therefore, an assessment of recent sentiment shifts or style-based performance relative to size and value factors cannot be constructed from the available dataset. The investment thesis hinges entirely on whether management can reverse the negative ROIC-WACC spread without compromising the impressive margin profile currently driving top-line expansion.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
DCF Sandbox
InteractiveSensitivity Matrix
| TG ↓ / WACC → | 9.3% | 11.3% | 13.3% |
|---|---|---|---|
| 2% | $38 | $30 | $24 |
| 3% | $43 | $32 | $26 |
| 4% | $50 | $36 | $28 |
Center = base case. Green = >10% upside, Red = >10% downside vs —.
Pre-computed DCF: WACC=11.3%, terminal growth 3%. Fair value $32 (+0.0%). Not investment advice.
Price Chart with Moving Averages
Quant Health Deep Dive
Profitability & Value Creation
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 XSW or SLYG, the fund manager is mechanically forced to buy or sell LIF shares regardless of LIF's individual fundamentals. We estimate $141M of passive capital is structurally linked to LIF through 7 tracked ETFs. Passive flows have a limited but growing influence on LIF's daily trading dynamics.
Passive exposure = Σ (ETF AUM × stock weight in ETF) across 7 tracked ETFs. Actual passive ownership is larger (includes mutual funds). Not investment advice.
ETF Contagion Visualizer
Simulate a price drop in LIF to visualize passive redemption contagion across ETFs and collateral stocks.
If LIF (LIF) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies SANMINA CORP (SANM) as the most exposed collateral stock, sharing 2 ETFs with LIF. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 7 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
LIF Ownership Dynamics
ETFs with Highest LIF Exposure
Float lock-up computed from 7 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
LIF Capital Efficiency
How efficiently does LIF convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.
LIF converts 248% of its EBITDA into free cash flow, an exceptional conversion rate indicating an asset-light business model with minimal capital reinvestment drag. However, the ROIC-WACC spread is negative (-9.5%), 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 |
|---|---|---|---|
| 2026-05-14 | 3,447 | $40.16 | $138,431.52 |
| 2026-05-13 | 43,818 | $38.62 | $1.7M |
| 2026-05-12 | 3,696 | $43.28 | $159,962.88 |
| 2026-05-08 | 14,000 | $44.01 | $616,140 |
| 2026-05-07 | 98 | $43.38 | $4,251.24 |
| 2026-05-06 | 283 | $44.52 | $12,599.16 |
| 2026-05-05 | 2,888 | $46.28 | $133,656.64 |
| 2026-05-04 | 51,799 | $45.75 | $2.4M |
| 2026-04-28 | 252 | $44.41 | $11,191.32 |
| 2026-04-27 | 178 | $45.78 | $8,148.84 |
| 2026-04-24 | 31 | $43.82 | $1,358.42 |
| 2026-04-22 | 9,889 | $45.57 | $450,641.73 |
| 2026-04-21 | 4,537 | $48.63 | $220,634.31 |
| 2026-04-20 | 9,528 | $48.75 | $464,490 |
| 2026-04-17 | 6,146 | $46.05 | $283,023.3 |
| 2026-04-16 | 3,904 | $42.59 | $166,271.36 |
| 2026-04-15 | 9 | $39.78 | $358.02 |
| 2026-04-14 | 471 | $39.52 | $18,613.92 |
| 2026-04-13 | 6,625 | $38.10 | $252,412.5 |
| 2026-04-09 | 7,210 | $43.97 | $317,023.7 |
| 2026-04-06 | 12,055 | $40.43 | $487,383.65 |
| 2026-03-26 | 16,535 | $40.38 | $667,683.3 |
| 2026-03-25 | 20 | $40.58 | $811.6 |
| 2026-03-24 | 129,328 | $41.19 | $5.3M |
| 2026-03-23 | 2,204,495 | $39.83 | $87.8M |
| 2026-03-20 | 1,856 | $39.27 | $72,885.12 |
| 2026-03-19 | 3 | $40.70 | $122.1 |
| 2026-03-18 | 6,200 | $41.58 | $257,796 |
| 2026-03-17 | 20,244 | $41.03 | $830,611.32 |
| 2026-03-16 | 6,915 | $41.22 | $285,036.3 |
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 LIF 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.