Smith A O (AOS) EBITDA (2010 - 2026)
Smith A O's EBITDA was $192.1 million in Q2 2026, down 15.1% from $226.3 million a year earlier but up 3.4% from the prior quarter.
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Analysis
Smith A O (AOS) EBITDA (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Smith A O's EBITDA was $761.1 million through Jun 30, 2026, down 3.2% year-over-year; for FY2025, it was $813.1 million, up 4.5% from FY2024.
- EBITDA shows a five-year compound annual growth rate of 9.3% (FY2020 to FY2025).
- In earlier years, EBITDA was $778 million in FY2024 (-4.8%), $816.9 million in FY2023 (+11.1%), $735.6 million in FY2022 (+7.0%) and $687.4 million in FY2021 (+32.1%).
- Quarterly EBITDA has moved between $167.7 million (Q3 2022) and $227.1 million (Q2 2024) over five years.
- Compared with a year earlier, EBITDA was higher in two of the last eight quarters, with an average decline of 4.7%.
- The best year-over-year quarter for EBITDA over five years was Q1 2022 (growth of 28.6%); the worst was Q2 2026 (a decline of 15.1%).
- Per Business Quant data, AOS's EBITDA in the three quarters before Q2 2026 was $185.7 million (Q1 2026), $186.1 million (Q4 2025) and $197.2 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 99.46 Bn | 94.20 Bn | 2.26 Bn | 1.33 Bn |
| 2 | Johnson Controls International | 90.06 Bn | 87.82 Bn | 2.47 Bn | 1.15 Bn |
| 3 | Comfort Systems Usa | 58.26 Bn | 53.51 Bn | 844.23 Mn | 601.28 Mn |
| 4 | Carrier Global | 45.22 Bn | 39.85 Bn | 1.94 Bn | 1.14 Bn |
| 5 | Otis Worldwide | 24.48 Bn | 21.09 Bn | 1.14 Bn | 617.00 Mn |
| 6 | James Hardie Industries | 14.69 Bn | 13.43 Bn | 548.70 Mn | 386.50 Mn |
| 7 | Masco | 13.29 Bn | 11.40 Bn | 868.00 Mn | - |
| 8 | Allegion | 13.08 Bn | 11.79 Bn | 517.50 Mn | 290.40 Mn |
| 9 | Carlisle Companies | 12.82 Bn | 9.17 Bn | 568.40 Mn | 401.20 Mn |
| 10 | Smith A O | 7.66 Bn | 6.91 Bn | 387.80 Mn | 192.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 192.10 Mn |
| Mar 31, 2026 | 185.70 Mn |
| Dec 31, 2025 | 186.10 Mn |
| Sep 30, 2025 | 197.20 Mn |
| Jun 30, 2025 | 226.30 Mn |
| Mar 31, 2025 | 203.50 Mn |
| Dec 31, 2024 | 175.40 Mn |
| Sep 30, 2024 | 181.00 Mn |
| Jun 30, 2024 | 227.10 Mn |
| Mar 31, 2024 | 212.10 Mn |
| Dec 31, 2023 | 205.60 Mn |
| Sep 30, 2023 | 200.70 Mn |
| Jun 30, 2023 | 223.30 Mn |
| Mar 31, 2023 | 206.10 Mn |
| Dec 31, 2022 | 200.10 Mn |
| Sep 30, 2022 | 167.70 Mn |
| Jun 30, 2022 | 185.70 Mn |
| Mar 31, 2022 | 182.10 Mn |
| Dec 31, 2021 | 196.30 Mn |
| Sep 30, 2021 | 181.70 Mn |
API Access
Smith A O EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=AOS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "AOS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=AOS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();