INSM (INSM)
Quantitative Summary
DeterministicFinancial health is average: Piotroski 4/9, Altman Z 8.9. Beneish M-Score of -1.96 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 this entity present a stark dichotomy between operational efficiency and profitability. While the gross margin sits at an impressive 79.7%, indicating strong pricing power or low cost of goods sold, the net margin has collapsed to -210.5%, driving both ROIC and DuPont-decomposed ROE into deeply negative territory of -52.5% and -172.8% respectively. This suggests that despite high revenue growth of 66.7% year-over-year, aggressive spending or one-time charges are erasing all bottom-line value. The Piotroski F-Score of 4/9 reflects a mixed financial health profile with neither strong deterioration nor robust improvement signals, while the Beneish M-Score of -1.96 indicates low probability of earnings manipulation; however, the negative leverage and turnover components in the DuPont analysis confirm that current equity returns are mathematically unsustainable without significant margin compression or asset base reduction.
Valuation metrics relative to historical norms or sector peers cannot be meaningfully assessed given the absence of positive net income required for standard P/E comparisons, rendering traditional multiples ineffective for determining fair value. The disconnect between explosive top-line growth and catastrophic profitability implies that current market pricing is likely extrapolating future margin expansion rather than accounting for present cash flow destruction. Without a clear path to converting these high gross margins into bottom-line earnings, any implied growth rate in a DCF model would rely heavily on speculative assumptions regarding cost structure normalization or revenue mix shifts that are not supported by the trailing twelve-month data.
Insider activity over the last 90 days reveals substantial net selling totaling $42.2 million, which introduces significant downside risk to the investment thesis regardless of future growth potential. This outflow contrasts sharply with the company's reported revenue surge, suggesting internal stakeholders may be concerned about capital allocation efficiency or long-term solvency given the negative ROIC. The combination of deteriorating profitability metrics and heavy insider distribution creates a high-risk environment where the current valuation premium is not adequately offset by fundamental quality indicators.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
Price Chart with Moving Averages
Technical Setup
AI GeneratedThe current trading price of $109.53 for INSM establishes a specific context within its recent price action, though the absence of explicit Simple Moving Average (SMA) envelope boundaries prevents a definitive calculation of immediate mean-reversion potential relative to those dynamic levels. Without knowing whether this figure sits at an extreme deviation above or below the statistical norm defined by the moving averages, it is difficult to gauge if the asset is currently overextended and primed for a pullback toward equilibrium or if it remains within its established historical range. The position's relationship to these key technical bands dictates how traders might interpret potential volatility contraction; typically, prices trading far outside such envelopes suggest higher probability of reverting to the mean, while those inside indicate continued trending behavior. Consequently, any assessment of future price movement must rely on inferred proximity rather than stated facts regarding deviation magnitude. If $109.53 represents a significant premium over recent average costs, statistical models often predict a corrective drift downward as momentum dissipates. Conversely, if this level aligns closely with the centerline or lower bounds of the envelope, it could signal sustained upward pressure or consolidation without immediate reversal signals. The data provided isolates the current valuation point but leaves the surrounding statistical context undefined, requiring further analysis to determine where the price stands relative to its recent trajectory and whether conditions favor a return to average values or continued divergence from them.
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.
Risk Profile
Sharpe = risk-adjusted return (higher is better). Max drawdown = largest peak-to-trough decline. 1,200+ trading days.
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 IBB or XBI, the fund manager is mechanically forced to buy or sell INSM shares regardless of INSM's individual fundamentals. We estimate $2.7B of passive capital is structurally linked to INSM through 8 tracked ETFs. Index rebalances and ETF creation/redemption cycles can create noticeable volume spikes unrelated to company news.
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 INSM to visualize passive redemption contagion across ETFs and collateral stocks.
If INSM (INSM) 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 1 ETFs with INSM. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 15 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
INSM Ownership Dynamics
Passive funds hold 1 in every 11 INSM shares, reducing daily market volatility.
INSM (INSM) exerts measurable gravity on the passive index market, currently representing 2.7% of the IBB (IBB) and 0.9% of the XBI (XBI). Across 15 tracked ETFs, approximately 20M shares (9.1% 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 INSM Exposure
Float lock-up computed from 15 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
INSM 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 INSM over the past year sits near $101.80 (16% of 252-day volume). The current price of $103.73 trades 1.9% 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 |
|---|---|---|---|
| 2026-05-13 | 11,691 | $116.00 | $1.4M |
| 2026-05-08 | 224,501 | $105.00 | $23.6M |
| 2026-04-20 | 139,933 | $144.48 | $20.2M |
| 2026-04-16 | 3 | $146.74 | $440.22 |
| 2026-04-09 | 358 | $160.18 | $57,344.44 |
| 2026-04-06 | 6 | $162.43 | $974.58 |
| 2026-03-23 | 7 | $136.00 | $952 |
| 2026-03-10 | 206 | $143.13 | $29,484.78 |
| 2026-03-04 | 10 | $147.00 | $1,470 |
| 2026-03-03 | 67 | $146.32 | $9,803.44 |
| 2026-02-27 | 41 | $150.00 | $6,150 |
| 2026-02-26 | 2,007 | $148.61 | $298,260.27 |
| 2026-02-23 | 421 | $164.91 | $69,427.11 |
| 2026-02-19 | 922 | $151.11 | $139,323.42 |
| 2026-02-18 | 62 | $150.52 | $9,332.24 |
| 2026-02-12 | 11,161 | $148.43 | $1.7M |
| 2026-02-11 | 1,791 | $148.55 | $266,053.05 |
| 2026-02-06 | 1,432 | $151.03 | $216,274.96 |
| 2026-02-05 | 1,412 | $152.44 | $215,245.28 |
| 2026-01-27 | 4 | $159.72 | $638.88 |
| 2026-01-26 | 362 | $156.21 | $56,548.02 |
| 2026-01-16 | 10 | $159.27 | $1,592.7 |
| 2026-01-12 | 6 | $175.97 | $1,055.82 |
| 2026-01-08 | 568 | $176.00 | $99,968 |
| 2026-01-06 | 1 | $175.20 | $175.2 |
| 2025-12-22 | 22,993 | $174.84 | $4.0M |
| 2025-12-15 | 4,886 | $197.01 | $962,590.86 |
| 2025-12-08 | 3 | $204.00 | $612 |
| 2025-12-02 | 3 | $211.41 | $634.23 |
| 2025-12-01 | 192 | $207.77 | $39,891.84 |
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.
Price Correlations
Statistical correlation of daily returns with other stocks. High correlations indicate stocks that move together; negative correlations can offer diversification.
| Peer | 252-Day (1Y) | 126-Day (6M) | Direction |
|---|---|---|---|
| WTGXX | NaN | NaN | |
| GH | 0.296 | 0.465 | Low correlation |
| BMY | 0.295 | 0.334 | Low correlation |
| IONS | 0.280 | 0.359 | Low correlation |
| NRIX | 0.258 | 0.280 | Low correlation |
| ARGX | 0.252 | 0.311 | Low correlation |
| CAH | 0.251 | 0.403 | Low correlation |
| CHRW | 0.249 | 0.386 | Low correlation |
| LLY | 0.240 | 0.111 | Low correlation |
| VRTPX | 0.239 | 0.195 | Low correlation |
Pearson correlation of daily log returns. 252d ≈ 1 trading year. Computed from price history. Not investment advice.
Compare INSM 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.