Latham (SWIM) Total Liabilities (2020 - 2026)
Latham's Total Liabilities was $448.94 million in Q2 2026, up 6.0% from $423.71 million a year earlier but down 2.3% from the prior quarter.
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Analysis
Latham (SWIM) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Latham came in at $417.36 million, up 2.5% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 2.7% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $406.99 million in FY2024 (-6.6%), $435.8 million in FY2023 (-10.5%), $486.89 million in FY2022 (+10.4%) and $440.84 million in FY2021 (+20.8%).
- Quarterly Total Liabilities has moved between $398.25 million (Q3 2021) and $554.61 million (Q1 2023) over five years.
- Compared with a year earlier, Total Liabilities has increased for three straight quarters, with growth averaging 0.6% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2022 (growth of 32.3%); the worst was Q1 2024 (a decline of 24.8%).
- Per Business Quant data, SWIM's Total Liabilities in the three quarters before Q2 2026 was $459.7 million (Q1 2026), $417.36 million (Q4 2025) and $436.07 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 104.14 Bn | 98.86 Bn | 2.26 Bn | 15.28 Bn |
| 2 | Johnson Controls International | 91.59 Bn | 89.32 Bn | 2.47 Bn | 25.24 Bn |
| 3 | Comfort Systems Usa | 49.30 Bn | 44.56 Bn | 844.23 Mn | 5.27 Bn |
| 4 | Carrier Global | 46.68 Bn | 40.99 Bn | 1.94 Bn | 23.90 Bn |
| 5 | Otis Worldwide | 27.65 Bn | 24.06 Bn | 1.14 Bn | 16.90 Bn |
| 6 | James Hardie Industries | 15.30 Bn | 14.37 Bn | 548.70 Mn | 6.95 Bn |
| 7 | Masco | 14.84 Bn | 12.70 Bn | 868.00 Mn | 5.77 Bn |
| 8 | Carlisle Companies | 13.70 Bn | 10.04 Bn | 568.40 Mn | 4.62 Bn |
| 9 | Allegion | 13.58 Bn | 12.29 Bn | 517.50 Mn | 3.24 Bn |
| 10 | Latham | 743.63 Mn | 743.63 Mn | 70.08 Mn | 448.94 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 448.94 Mn |
| Mar 28, 2026 | 459.70 Mn |
| Dec 31, 2025 | 417.36 Mn |
| Sep 27, 2025 | 436.07 Mn |
| Jun 28, 2025 | 423.71 Mn |
| Mar 29, 2025 | 443.44 Mn |
| Dec 31, 2024 | 406.99 Mn |
| Sep 28, 2024 | 436.76 Mn |
| Jun 29, 2024 | 421.90 Mn |
| Mar 30, 2024 | 416.84 Mn |
| Dec 31, 2023 | 435.80 Mn |
| Sep 30, 2023 | 472.79 Mn |
| Jul 1, 2023 | 484.94 Mn |
| Apr 1, 2023 | 554.61 Mn |
| Dec 31, 2022 | 486.89 Mn |
| Oct 1, 2022 | 522.47 Mn |
| Jul 2, 2022 | 527.31 Mn |
| Apr 2, 2022 | 534.76 Mn |
| Dec 31, 2021 | 440.84 Mn |
| Oct 2, 2021 | 398.25 Mn |
API Access
Latham Total Liabilities 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=total-liabilities&ticker=SWIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "SWIM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=SWIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();