SIG (SIG)
Quantitative Summary
DeterministicFinancial health metrics are strong: Piotroski 7/9, Altman Z 3.1 (above 3.0 safe zone threshold).
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe capital allocation efficiency reveals a distinct divergence between return on invested capital and equity returns, suggesting that high leverage is the primary driver of shareholder yield rather than organic operational prowess. While the ROIC-WACC spread sits at 10%, indicating robust underlying asset productivity relative to the cost of capital, the DuPont decomposition exposes this strength as heavily reliant on an Equity Multiplier of 3.09x; the low net margin of 4.3% and modest asset turnover of 1.17x constrain pure earnings power per dollar of sales. This structural reliance on debt is corroborated by a Piotroski F-Score of 7/9, signaling strong fundamental stability absent major deterioration, yet paired with an Altman Z-Score of 3.1 that places the firm in the "grey zone" between safety and distress. Furthermore, the negative Beneish M-Score of -2.55 suggests low probability of earnings manipulation, reinforcing confidence in the reported financial trajectory despite revenue growth stagnating at just 1.6% year-over-year.
Valuation metrics present a compelling discrepancy between current market pricing and intrinsic value estimates derived from discounted cash flow analysis. The stock trades at a P/E ratio of 11.7x, which appears compressed relative to its implied growth potential when weighed against a DCF fair value of $94; this suggests the market may be discounting future cash flows more aggressively than current fundamentals justify or that it is pricing in significant downside risk not fully captured by static multiples. The gap between the current trading price and the calculated fair value implies either an undervaluation opportunity based on conservative modeling assumptions or a premium to safety margins that requires confirmation through sustained earnings acceleration before the market re-rates the equity.
Risk assessment highlights a notable divergence between insider behavior and broader technical indicators, warranting cautious scrutiny of near-term sentiment. Despite the solid Piotroski score and low manipulation risk, the net selling activity by insiders totaling $622,720 over the last 90 days introduces a counter-narrative to the otherwise healthy balance sheet metrics. This insider outflow could signal management's expectation that current valuation levels do not fully reflect future operational headwinds or capital return constraints, adding a layer of skepticism to the bullish case derived solely from fundamental quality scores and DCF valuations.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
DCF Sandbox
InteractiveSensitivity Matrix
| TG ↓ / WACC → | 8% | 10% | 12% |
|---|---|---|---|
| 2% | $110 | $86 | $72 |
| 3% | $125 | $94 | $76 |
| 4% | $147 | $104 | $82 |
Center = base case. Green = >10% upside, Red = >10% downside vs —.
Pre-computed DCF: WACC=10.0%, terminal growth 3%. Fair value $94 (+0.0%). Not investment advice.
Price Chart with Moving Averages
Quant Health Deep Dive
Profitability & Value Creation
✅ 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.
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 XRT or SLYV, the fund manager is mechanically forced to buy or sell SIG shares regardless of SIG's individual fundamentals. We estimate $151M of passive capital is structurally linked to SIG through 8 tracked ETFs. Passive flows have a limited but growing influence on SIG'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 SIG to visualize passive redemption contagion across ETFs and collateral stocks.
If SIG (SIG) 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 SIG. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 11 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
SIG Ownership Dynamics
ETFs with Highest SIG Exposure
Float lock-up computed from 11 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
SIG Capital Efficiency
How efficiently does SIG convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.
SIG converts 79% 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.
| Date | Failed Shares | Close Price | Notional Value |
|---|---|---|---|
| 2026-05-13 | 13,270 | $80.35 | $1.1M |
| 2026-05-08 | 2,049 | $87.99 | $180,291.51 |
| 2026-05-06 | 9,436 | $81.99 | $773,657.64 |
| 2026-05-01 | 69 | $89.03 | $6,143.07 |
| 2026-04-29 | 8 | $87.09 | $696.72 |
| 2026-04-13 | 8 | $93.63 | $749.04 |
| 2026-04-10 | 9,959 | $93.06 | $926,784.54 |
| 2026-03-30 | 4,249 | $84.04 | $357,085.96 |
| 2026-03-27 | 31 | $87.92 | $2,725.52 |
| 2026-03-23 | 25,508 | $89.05 | $2.3M |
| 2026-03-20 | 1,684 | $89.56 | $150,819.04 |
| 2026-03-19 | 456 | $78.77 | $35,919.12 |
| 2026-03-18 | 1,080 | $84.96 | $91,756.8 |
| 2026-03-12 | 144 | $85.48 | $12,309.12 |
| 2026-03-05 | 11 | $95.70 | $1,052.7 |
| 2026-03-04 | 16 | $97.13 | $1,554.08 |
| 2026-02-25 | 8,773 | $97.03 | $851,244.19 |
| 2026-02-20 | 531 | $95.07 | $50,482.17 |
| 2026-02-18 | 15,413 | $95.61 | $1.5M |
| 2026-02-13 | 48 | $89.35 | $4,288.8 |
| 2026-02-12 | 7,512 | $92.35 | $693,733.2 |
| 2026-02-05 | 77 | $94.49 | $7,275.73 |
| 2026-02-04 | 9 | $91.23 | $821.07 |
| 2026-02-02 | 380 | $92.27 | $35,062.6 |
| 2026-01-29 | 2,987 | $91.71 | $273,937.77 |
| 2026-01-23 | 981 | $92.43 | $90,673.83 |
| 2026-01-21 | 1,186 | $93.44 | $110,819.84 |
| 2026-01-20 | 562 | $95.16 | $53,479.92 |
| 2026-01-14 | 11 | $88.41 | $972.51 |
| 2026-01-13 | 11 | $86.13 | $947.43 |
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 SIG 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.