LQDA (LQDA)
Quantitative Summary
DeterministicFinancial health is average: Piotroski 5/9. Beneish M-Score of 6.80 exceeds the -2.22 academic threshold — earnings quality may warrant further review.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe fundamental economics of LQDA present a stark dichotomy between explosive top-line expansion and severe profitability erosion. While revenue growth has surged 1,031.2% year-over-year, indicating massive scale-up activity or market penetration, the company is operating at a net margin of -43.5%, resulting in an ROIC of -18.4%. This negative return on invested capital suggests that current operations are burning cash rather than generating value, despite the impressive gross margin of 91.6% which implies strong pricing power or low cost-of-goods sold relative to sales. The DuPont decomposition is skewed entirely by this leverage and efficiency mismatch; without positive net income, traditional ROE drivers like turnover cannot offset the bottom-line deficit. Furthermore, while a Piotroski F-Score of 5/9 indicates moderate financial strength based on scorecard criteria, the Beneish M-Score of 6.80 raises significant red flags regarding potential earnings manipulation or aggressive accounting practices that warrant skepticism when evaluating such volatile growth figures.
Valuation metrics reflect extreme market optimism detached from current cash flow realities, with a price-to-earnings ratio soaring to 312.5x. This multiple is mathematically impossible to justify using standard DCF models given the negative net income and -18.4% ROIC, as there are no earnings to discount or stable cash flows to project. The market appears to be pricing in a hypothetical future where operating leverage instantly converts these astronomical gross margins into sustainable net profits without addressing the massive burn rate implied by the current P/E. Consequently, the valuation relies entirely on the assumption that the 103% revenue growth will translate directly into profitability within a single reporting cycle, ignoring the typical lag and capital expenditure required to support such scale-up phases in most sectors.
The risk/reward profile is heavily weighted toward downside volatility given the combination of negative returns and elevated manipulation signals. A Beneish M-Score near 7 suggests that earnings quality may be compromised, increasing the probability that reported figures do not reflect true economic performance. Additionally, a Piotroski score of only 5 indicates the company lacks several fundamental strengths such as improving profitability or decreasing leverage, which are typical characteristics of high-quality compounders. Investors must weigh whether the extraordinary revenue growth is a one-time anomaly or part of a sustainable trajectory before engaging with an asset that currently offers no margin of safety and carries significant accounting risk.
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
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 XPH or VFMO, the fund manager is mechanically forced to buy or sell LQDA shares regardless of LQDA's individual fundamentals. We estimate $30M of passive capital is structurally linked to LQDA through 4 tracked ETFs. Passive flows have a limited but growing influence on LQDA's daily trading dynamics.
Passive exposure = Σ (ETF AUM × stock weight in ETF) across 4 tracked ETFs. Actual passive ownership is larger (includes mutual funds). Not investment advice.
ETF Contagion Visualizer
Simulate a price drop in LQDA to visualize passive redemption contagion across ETFs and collateral stocks.
If LQDA (LQDA) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies Eli Lilly & Co. (LLY) as the most exposed collateral stock, sharing 2 ETFs with LQDA. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 4 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
LQDA Ownership Dynamics
Passive funds hold 1 in every 120 LQDA shares, reducing daily market volatility.
LQDA (LQDA) exerts measurable gravity on the passive index market, currently representing 2.9% of the XPH (XPH) and 0.2% of the VFMO (VFMO). Across 4 tracked ETFs, approximately 1M shares (0.8% of float) are held by passive funds and rarely trade on the open market. As passive ownership grows, index inclusion changes may increasingly drive price discovery.
ETFs with Highest LQDA Exposure
Float lock-up computed from 4 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
LQDA Institutional Volume Profile
252-day volume distribution by price level. The Point of Control (POC) marks — the price where the most institutional volume transacted — an implicit support/resistance floor.
The highest-volume price zone for LQDA over the past year sits near $23.46 (16% of 252-day volume). The current price of $55.11 trades 134.9% above this institutional floor — a sign of upside momentum, though a pullback to the POC zone is a common reversion target. The highly concentrated volume profile (16% at POC) indicates strong consensus on fair value — institutional participants have repeatedly transacted near this price.
Volume Profile computed from 252 trading days of OHLCV data. Volume allocated to price bins proportionally based on daily high-low range. 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 | 33,492 | $57.59 | $1.9M |
| 2026-05-12 | 1,020 | $53.13 | $54,192.6 |
| 2026-05-11 | 1,472 | $42.30 | $62,265.6 |
| 2026-04-24 | 1 | $37.46 | $37.46 |
| 2026-04-20 | 6,477 | $39.47 | $255,647.19 |
| 2026-04-17 | 1,407 | $41.40 | $58,249.8 |
| 2026-04-13 | 400 | $38.55 | $15,420 |
| 2026-04-06 | 581 | $37.68 | $21,892.08 |
| 2026-03-23 | 500 | $36.41 | $18,205 |
| 2026-03-18 | 198 | $36.86 | $7,298.28 |
| 2026-03-11 | 3,961 | $38.83 | $153,805.63 |
| 2026-03-10 | 1,994 | $35.87 | $71,524.78 |
| 2026-03-05 | 9,208 | $34.38 | $316,571.04 |
| 2026-03-04 | 10,373 | $31.78 | $329,653.94 |
| 2026-03-02 | 23,184 | $31.02 | $719,167.68 |
| 2026-02-25 | 2,084 | $33.57 | $69,959.88 |
| 2026-02-24 | 951 | $32.74 | $31,135.74 |
| 2026-02-23 | 21,717 | $33.59 | $729,474.03 |
| 2026-02-17 | 18 | $38.20 | $687.6 |
| 2026-02-10 | 11,242 | $42.40 | $476,660.8 |
| 2026-02-06 | 146 | $41.56 | $6,067.76 |
| 2026-02-05 | 2,000 | $44.43 | $88,860 |
| 2026-02-04 | 4,185 | $46.63 | $195,146.55 |
| 2026-01-30 | 16 | $43.06 | $688.96 |
| 2026-01-29 | 5,389 | $41.91 | $225,852.99 |
| 2026-01-27 | 25,012 | $42.21 | $1.1M |
| 2026-01-26 | 29,782 | $40.59 | $1.2M |
| 2026-01-23 | 8,689 | $41.07 | $356,857.23 |
| 2026-01-22 | 7,188 | $39.99 | $287,448.12 |
| 2026-01-20 | 143,155 | $37.93 | $5.4M |
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 LQDA to Peers
Quant metrics computed deterministically from financial statements and price data. Updated: 2026-06-02.
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.