HLN (HLN)

Market Cap
P/E Ratio
Beta
Dividend Yield
Piotroski 8/9

Quantitative Summary

Deterministic

Strong operational fundamentals (Piotroski 8/9).

Generated deterministically from quant metrics and financial statements. Not a recommendation.

Algorithmic Teardown

AI-Generated

The capital allocation efficiency of HLN presents a distinct dichotomy between high profitability per dollar of sales and modest return on invested capital. While the Piotroski F-Score of 8/9 signals robust fundamental strength with minimal financial distress risk, the ROIC-WACC spread remains constrained at 7.1%, suggesting that growth in operating income has not yet translated into proportionate value creation relative to total capital deployed. This tension is further illuminated by the DuPont decomposition: a commanding net margin of 15.1% and gross margin exceeding 64% are offset by low asset turnover of 0.34x, indicating that earnings generation relies heavily on leverage rather than operational velocity or inventory efficiency. The equity multiplier of 1.98x confirms this capital structure dependence, where the ROE of 10.1% is driven primarily by financial leverage and pricing power rather than high asset productivity.

Valuation metrics suggest the market assigns a premium to these margin characteristics despite recent revenue contraction. Although specific historical or sector benchmarks are unavailable in the provided data, the DCF model implies an intrinsic fair value of $4, which serves as a critical anchor against current trading levels if growth assumptions hold steady. The negative 1.8% year-over-year revenue growth introduces uncertainty regarding future margin sustainability and top-line expansion potential, challenging the optimistic growth rate inputs required to justify a price significantly above the DCF floor. Consequently, the disconnect between strong balance sheet health and flat-to-negative sales trajectory creates ambiguity around whether current pricing adequately compensates for stagnation or undervalues the high-margin asset base.

Insider activity over the last ninety days remains neutral with zero net flow, offering no directional signal from management regarding capital deployment or confidence in near-term catalysts. In the absence of insider buying to offset revenue headwinds, the risk profile leans toward valuation sensitivity rather than fundamental deterioration; however, the lack of positive internal conviction combined with shrinking revenues suggests that any upside is contingent on a re-rating of growth expectations rather than immediate operational improvement. The investment case rests entirely on whether the market can reconcile the high-quality earnings generation with the inability to expand sales volume sufficiently to boost ROIC above its current 7.1% level.

Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.

DCF Sandbox

Interactive

Sensitivity Matrix

TG ↓ / WACC →8%10%12%
2%$5$3$3
3%$6$4$3
4%$7$5$3

Center = base case. Green = >10% upside, Red = >10% downside vs .

Pre-computed DCF: WACC=10.0%, terminal growth 3%. Fair value $4 (+0.0%). Not investment advice.

Price Chart with Moving Averages

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SMA 50 SMA 200

Quant Health Deep Dive

8/9
Piotroski F-Score
Strong — high operational efficiency and profitability signals

Profitability & Value Creation

64.2%
Gross Margin
15.1%
Net Margin
7.1%
ROIC
-1.8%
Revenue Growth (YoY)
+15.6%
Earnings Growth (YoY)
2.2B
Free Cash Flow
28%
FCF Payout Ratio

✅ Conservative payout — room for dividend increases.

DuPont Analysis — ROE Decomposition

Breaking down Return on Equity to see how the company generates its ROE — efficiency, margins, or leverage.

15.1%
Net Profit Margin
NI ÷ Revenue
×
0.34x
Asset Turnover
Revenue ÷ Assets
×
1.98x
Equity Multiplier
Assets ÷ Equity
=
10.1%
Return on Equity
✅ ROE driven primarily by strong profit margins — a sign of pricing power.

Balance Sheet Health

0.98x
Debt / Equity
0.92x
Current Ratio
7.2x
Interest Coverage
2.2x
Net Debt / EBITDA
2.9B
EBITDA

Underwater (Drawdown from Peak)

How far below the all-time high the price has been over time. Deeper = more pain for holders.

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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.

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Rolling Beta Market (β = 1.0)

Fundamentals

Forward P/E
PEG Ratio
Price/Book
Avg Volume
52W High
52W Low
52W Range Position

Passive Flow Attribution

ETF Draft Effect
$1.2B
Tracked Passive Exposure
8
ETFs Holding HLN
0.10%
Avg Weight in ETFs
$1.2T
Total ETF AUM

When investors buy or sell ETFs like VGK or VSGX, the fund manager is mechanically forced to buy or sell HLN shares regardless of HLN's individual fundamentals. We estimate $1.2B of passive capital is structurally linked to HLN 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 HLN to visualize passive redemption contagion across ETFs and collateral stocks.

HLN Shock
-0%
Est. Passive Redemption
$0
Systemic Risk
STABLE
HLNEpicenterVXUSETFVEAETFVEUETF2330UnknownASMLLow Risk005930UnknownAZNLow RiskNOVNUnknown
HLN Price Drop (%)0

If HLN (HLN) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies Taiwan Semiconductor Manufacturing Co. Ltd. (2330) as the most exposed collateral stock, sharing 2 ETFs with HLN. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.

Contagion model based on shared ETF exposure and constituent weights across 8 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.

HLN Ownership Dynamics

Ticker
HLN

Float lock-up computed from 8 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).

HLN Capital Efficiency

How efficiently does HLN convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.

Free Cash Flow
$2.2B
EBITDA
$2.9B
FCF Conversion
78%
Reinvestment Rate
22%
78% of EBITDA → Free Cash
0% (cash burn)25% (low)50% (efficient)100% (pure cash)

HLN converts 78% of its EBITDA into free cash flow, an exceptional conversion rate indicating an asset-light business model with minimal capital reinvestment drag.

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.

DateFailed SharesClose PriceNotional Value
2026-05-13381$9.10$3,467.1
2026-05-121,301,224$8.98$11.7M
2026-05-11396,113$9.11$3.6M
2026-05-08201,161$9.30$1.9M
2026-05-062,426$9.17$22,246.42
2026-04-30101,242$9.30$941,550.6
2026-04-285,358$9.49$50,847.42
2026-04-22774$9.53$7,376.22
2026-04-134$9.84$39.36
2026-04-104$10.01$40.04
2026-04-0272,980$9.97$727,610.6
2026-03-31955$10.00$9,550
2026-03-3061,357$9.80$601,298.6
2026-03-26734$9.74$7,149.16
2026-03-20181,772$10.23$1.9M
2026-03-1971,954$10.31$741,845.74
2026-03-18454$10.60$4,812.4
2026-03-1733,447$10.46$349,855.62
2026-03-1385,407$10.07$860,048.49
2026-03-114,381$10.17$44,554.77
2026-03-10361,453$10.26$3.7M
2026-03-06118,181$10.33$1.2M
2026-03-0566,912$10.47$700,568.64
2026-03-046,628$10.61$70,323.08
2026-03-0318,185$10.87$197,670.95
2026-02-26857$10.44$8,947.08
2026-02-24973,972$11.08$10.8M
2026-02-2397,433$11.27$1.1M
2026-02-20306,675$11.11$3.4M
2026-02-1936$11.22$403.92

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 HLN 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.