PTLO (PTLO)
Quantitative Summary
DeterministicFinancial health is average: Piotroski 4/9.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
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
ETF Contagion Visualizer
Simulate a price drop in PTLO to visualize passive redemption contagion across ETFs and collateral stocks.
If PTLO (PTLO) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies Amazon.com Inc. (AMZN) as the most exposed collateral stock, sharing 1 ETFs with PTLO. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 1 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
PTLO Ownership Dynamics
ETFs with Highest PTLO Exposure
Float lock-up computed from 1 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
PTLO Capital Efficiency
How efficiently does PTLO convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.
PTLO converts -24% of its EBITDA into free cash flow, negative FCF conversion — the company is consuming cash faster than it generates EBITDA, which is unsustainable long-term. The 124% reinvestment rate signals aggressive capacity expansion.
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 |
|---|---|---|---|
| 2026-05-12 | 11,152 | $4.12 | $45,946.24 |
| 2026-05-07 | 124,842 | $4.49 | $560,540.58 |
| 2026-05-06 | 150 | $4.79 | $718.5 |
| 2026-05-05 | 842 | $5.72 | $4,816.24 |
| 2026-05-04 | 11,416 | $6.49 | $74,089.84 |
| 2026-04-20 | 1,971 | $5.91 | $11,648.61 |
| 2026-04-15 | 6,850 | $5.56 | $38,086 |
| 2026-03-27 | 64,815 | $5.38 | $348,704.7 |
| 2026-03-25 | 7,122 | $5.32 | $37,889.04 |
| 2026-03-23 | 3,693 | $5.50 | $20,311.5 |
| 2026-03-19 | 5,963 | $5.55 | $33,094.65 |
| 2026-03-17 | 3,385 | $5.65 | $19,125.25 |
| 2026-03-12 | 42,690 | $5.29 | $225,830.1 |
| 2026-03-11 | 255 | $5.04 | $1,285.2 |
| 2026-03-05 | 44,502 | $5.17 | $230,075.34 |
| 2026-03-04 | 62,165 | $5.21 | $323,879.65 |
| 2026-03-03 | 535 | $5.23 | $2,798.05 |
| 2026-02-27 | 8,215 | $5.48 | $45,018.2 |
| 2026-02-26 | 9,912 | $5.28 | $52,335.36 |
| 2026-02-25 | 940 | $5.33 | $5,010.2 |
| 2026-02-20 | 14,563 | $5.66 | $82,426.58 |
| 2026-02-17 | 25,233 | $5.40 | $136,258.2 |
| 2026-02-13 | 30,579 | $5.46 | $166,961.34 |
| 2026-02-12 | 10,675 | $5.81 | $62,021.75 |
| 2026-02-11 | 102 | $5.96 | $607.92 |
| 2026-02-10 | 20,607 | $6.06 | $124,878.42 |
| 2026-02-09 | 19,752 | $5.96 | $117,721.92 |
| 2026-02-06 | 4,901 | $5.75 | $28,180.75 |
| 2026-02-05 | 6,718 | $5.82 | $39,098.76 |
| 2026-02-04 | 26,431 | $5.61 | $148,277.91 |
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 PTLO 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.