NNN (NNN)
Quantitative Summary
DeterministicFinancial health is average: Piotroski 5/9, Altman Z 1.1.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe capital allocation efficiency appears constrained, evidenced by a negative ROIC-WACC spread of -2.6%, indicating that current returns fail to cover the cost of capital despite an 8.8% DuPont-derived ROE driven primarily by exceptional net margins of 42.1%. This high-margin profile is supported by robust gross margins at 96.0% and reinforced by a clean Beneish M-Score of -2.61, suggesting low earnings manipulation risk; however, the Altman Z-Score of 1.1 signals elevated bankruptcy distress relative to historical norms. The Piotroski F-Score of 5/9 reflects moderate financial strength but lacks the momentum typically associated with high-quality compounders, creating a tension between strong profitability metrics and weaker balance sheet resilience or growth velocity.
Valuation sits at a forward P/E multiple of 20.3x, which must be weighed against the implied sustainability of revenue growing at only 6.6% year-over-year. While the margin expansion supports premium pricing power, the negative return on invested capital suggests that future DCF models may struggle to justify this multiple unless significant operational leverage or asset turnover improvements occur. The market appears to be pricing in a scenario where high margins offset low growth and suboptimal capital efficiency, yet the disconnect between the cost of equity (7.8%) and actual returns creates an inherent drag on intrinsic value calculations that standard multiples may not fully capture.
Insider activity over the last 90 days reveals $1,939,036 in net selling, a delta that introduces a cautionary signal regarding management's view of near-term prospects or liquidity needs. Combined with the distress indicators from the Altman score and the negative spread between return on capital and the hurdle rate, the risk-reward profile leans toward defensive positioning rather than aggressive accumulation. Investors must determine whether the 42% net margin provides sufficient buffer against the identified solvency risks and insider outflows to sustain the current valuation multiple in a tightening credit environment.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
Price Chart with Moving Averages
Quant Health Deep Dive
Profitability & Value Creation
DuPont Analysis — ROE Decomposition
Breaking down Return on Equity to see how the company generates its ROE — efficiency, margins, or leverage.
Balance Sheet Health
Insider Activity (Last 90 Days)
Open-market buys vs sells by company insiders. Source: yfinance.
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 VNQ or SDY, the fund manager is mechanically forced to buy or sell NNN shares regardless of NNN's individual fundamentals. We estimate $882M of passive capital is structurally linked to NNN through 8 tracked ETFs. Passive flows have a limited but growing influence on NNN'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 NNN to visualize passive redemption contagion across ETFs and collateral stocks.
If NNN (NNN) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies Vanguard Real Estate II Index Fund Institutional Plus Shares (VRTPX) as the most exposed collateral stock, sharing 1 ETFs with NNN. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 13 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
NNN Ownership Dynamics
ETFs with Highest NNN Exposure
Float lock-up computed from 13 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
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 |
|---|---|---|---|
| 2026-05-07 | 114 | $44.71 | $5,096.94 |
| 2026-04-30 | 200 | $43.52 | $8,704 |
| 2026-04-29 | 5,868 | $44.04 | $258,426.72 |
| 2026-04-20 | 326 | $45.14 | $14,715.64 |
| 2026-03-23 | 22 | $42.46 | $934.12 |
| 2026-02-09 | 4,477 | $42.91 | $192,108.07 |
| 2026-01-30 | 969 | $41.82 | $40,523.58 |
| 2026-01-28 | 178 | $42.17 | $7,506.26 |
| 2026-01-26 | 66 | $42.26 | $2,789.16 |
| 2026-01-08 | 14 | $40.49 | $566.86 |
| 2026-01-06 | 5,734 | $39.94 | $229,015.96 |
| 2025-12-24 | 35 | $39.05 | $1,366.75 |
| 2025-12-22 | 1,662 | $39.76 | $66,081.12 |
| 2025-12-10 | 358 | $39.29 | $14,065.82 |
| 2025-11-28 | 2 | $41.08 | $82.16 |
| 2025-11-24 | 5,537 | $40.95 | $226,740.15 |
| 2025-11-21 | 20,217 | $40.40 | $816,766.8 |
| 2025-11-20 | 439 | $40.62 | $17,832.18 |
| 2025-11-05 | 3,570 | $39.82 | $142,157.4 |
| 2025-11-03 | 90 | $40.46 | $3,641.4 |
| 2025-10-31 | 3,843 | $40.84 | $156,948.12 |
| 2025-10-28 | 75,122 | $42.20 | $3.2M |
| 2025-10-21 | 6 | $42.71 | $256.26 |
| 2025-10-09 | 274 | $42.01 | $11,510.74 |
| 2025-10-03 | 1,093 | $42.91 | $46,900.63 |
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 NNN 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.