Latest revenue
$1.31B
as of 2026-04-04
Latest net income
$247.0M
as of 2026-04-04
Net margin
18.9%
as of 2026-04-04
Community sentiment
Where do you think SNA is heading?
Keep private notes on SNA — thesis, target price, catalysts to watch.
Visible only to you. Never shared. Never used to train AI.
SNA vs S&P 500 · rebased to 100
Market data
Price feed temporarily unavailable for SNA.
What this company does
Snap-on makes professional-grade hand tools, power tools, diagnostics equipment, and shop software sold mainly to vehicle repair technicians, auto dealerships, and industrial customers. The bulk of revenue comes from product sales through its franchised mobile-van distribution network, supplemented by a financial services arm that finances tool purchases for technicians and franchisees. Q1 2026 sales rose 6% to $1.21 billion with EPS climbing to $4.69, while the company kept returning cash via a raised $2.44 dividend and ongoing buybacks.
Generated from SNA's filing dated 2024-02-16
Key risks
- Large finance receivables book: $1.87B total ($598M current + $1.27B long-term) exposes Snap-on to franchisee/technician credit losses if labor markets soften.
- Debt refinancing wall: $316.2M reclassified to current from long-term, requiring repayment or refinancing at potentially higher rates versus prior fixed coupons.
- Modest organic growth: Q1 net sales rose only 5.8% YoY ($1,207M vs $1,141M) while financial services revenue declined, signaling tool demand softness among technicians.
Generated from SNA's filing dated 2024-02-16
ActaClear Score
Computed from 5 years of SEC fundamentals + latest market data, ranked within Cutlery, Handtools & General Hardware (8 peers). 10 = best in industry, 5 = median, 0 = worst. Refreshed Jun 10, 2026.
Fair value · DCF
Methodology + caveats (click to expand)
Method. 10-year forecast of free cash flow, discounted at the company's WACC, with a Gordon-growth terminal at year 10. FCF is proxied by last fiscal-year net income (proper FCF needs CFO − CapEx by year, which we don't store yet). Beta defaults to 1.0 when not reported.
Why DCF is fragile. Treat the output as a thinking aid, not a verdict. Honest weaknesses of any DCF:
- Growth is the dominant assumption. No one can foresee 10 years of growth — small changes in the slider can double or halve fair value. The reverse-DCF readout above tells you what the market is implicitly assuming; ask yourself whether that's realistic before trusting either number.
- Terminal value dominates. In most DCFs, 60-80% of the answer comes from the terminal-value calculation — i.e., everything AFTER year 10. A 0.5pp change in terminal growth, or in WACC, can swing fair value by 20-30%.
- WACC is itself a guess. We use a textbook CAPM cost of equity (Rf 4.3%, MRP 5.5%, β from the quote) plus a 6% pretax cost of debt — none of these are the company's actual marginal financing cost.
- No moat / disruption modelling. The model assumes the company keeps earning whatever it earns today, compounding cleanly. Competitive shifts, regulatory action, and technology disruption can invalidate the forecast overnight.
- Net income ≠ free cash flow. For capex-heavy names (semis, telcos) net income overstates distributable cash. For low-capex names (software) it understates. Both reduce the precision of the FV figure.
- Reflexivity. A high stock price often becomes a self-fulfilling prophecy via better hiring, financing, and customer trust. DCF can't see this.
Take the DCF, the reverse-DCF implied growth, the historical multiples, and the community sentiment together. When they agree, conviction. When they disagree, the disagreement is the most informative thing on the page.
Historical multiples
How does SNA's current valuation compare to its own past?
P/E uses year-end weekly close ÷ (net income ÷ shares outstanding today). Held shares constant at today's count, which understates the per-share earnings improvement from buybacks over the period. PEG uses 5y revenue CAGR as a proxy for EPS growth — close, but not identical (margin expansion or dilution can drive a wedge). Best read as a comparator across companies and industries, not as a precise replica of historical multiples.