Latham (SWIM) Change in Accured Expenses (2020 - 2026)
Latham's Change in Accured Expenses was $9.99 million in Q2 2026, up 38.5% from $7.21 million a year earlier.
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Analysis
Latham (SWIM) Change in Accured Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Latham's Change in Accured Expenses was -$716,000 through Jun 27, 2026; for FY2025, it was -$6.07 million.
- In earlier years, Change in Accured Expenses was -$1.33 million in FY2024, -$11.94 million in FY2023, -$19.42 million in FY2022 and $4.69 million in FY2021 (-77.2%).
- The Q2 2026 figure marks the highest quarterly Change in Accured Expenses since Q3 2020.
- Compared with a year earlier, Change in Accured Expenses was higher in two of the last four quarters, with growth averaging 12.7%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q3 2023 (growth of 187.4%); the worst was Q2 2022 (a decline of 91.7%).
- Per Business Quant data, SWIM's Change in Accured Expenses in the three quarters before Q2 2026 was -$2.28 million (Q1 2026), -$12.74 million (Q4 2025) and $4.32 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Trane Technologies | 98.76 Bn | 93.48 Bn | 2.26 Bn | - |
| 2 | Johnson Controls International | 87.60 Bn | 85.33 Bn | 2.47 Bn | 701.00 Mn |
| 3 | Carrier Global | 46.72 Bn | 41.03 Bn | 1.94 Bn | 280.00 Mn |
| 4 | Comfort Systems Usa | 40.67 Bn | 34.63 Bn | 934.48 Mn | 465.94 Mn |
| 5 | Otis Worldwide | 28.79 Bn | 25.20 Bn | 1.14 Bn | 49.00 Mn |
| 6 | Allegion | 15.35 Bn | 14.06 Bn | 517.50 Mn | - |
| 7 | James Hardie Industries | 15.17 Bn | 14.23 Bn | 548.70 Mn | -10.80 Mn |
| 8 | Masco | 15.15 Bn | 13.01 Bn | 868.00 Mn | 92.00 Mn |
| 9 | Carlisle Companies | 13.87 Bn | 10.22 Bn | 568.40 Mn | - |
| 10 | Latham | 778.28 Mn | 778.28 Mn | 70.08 Mn | 9.99 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 9.99 Mn |
| Mar 28, 2026 | -2.28 Mn |
| Dec 31, 2025 | -12.74 Mn |
| Sep 27, 2025 | 4.32 Mn |
| Jun 28, 2025 | 7.21 Mn |
| Mar 29, 2025 | -4.86 Mn |
| Dec 31, 2024 | -4.76 Mn |
| Sep 28, 2024 | 4.61 Mn |
| Jun 29, 2024 | 4.81 Mn |
| Mar 30, 2024 | -5.99 Mn |
| Dec 31, 2023 | -11.77 Mn |
| Sep 30, 2023 | 6.71 Mn |
| Jul 1, 2023 | -3.69 Mn |
| Apr 1, 2023 | -3.19 Mn |
| Dec 31, 2022 | -19.33 Mn |
| Oct 1, 2022 | 2.34 Mn |
| Jul 2, 2022 | 806,000.00 |
| Apr 2, 2022 | -3.23 Mn |
| Dec 31, 2021 | -5.05 Mn |
| Oct 2, 2021 | 4.19 Mn |
API Access
Latham Change in Accured Expenses 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=change-in-accured-expenses&ticker=SWIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "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=change-in-accured-expenses&ticker=SWIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();