SPX Technologies (SPXC) Accumulated Expenses (2009 - 2026)
SPX Technologies (SPXC) posted Accumulated Expenses of $194.7 million for Q3 2026, up 11.9% from $174 million a year earlier and up 6.2% from the prior quarter.
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Analysis
SPX Technologies (SPXC) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, SPX Technologies' Accumulated Expenses came in at $185.2 million, up 8.4% from FY2024.
- Annual Accumulated Expenses has increased for three consecutive years, though with a five-year compound annual growth rate of -2.2% (FY2020 to FY2025).
- In prior years, SPX Technologies' Accumulated Expenses was $170.8 million in FY2024 (+1.4%), $168.5 million in FY2023 (+13.9%), $148 million in FY2022 (-32.1%) and $217.9 million in FY2021 (+5.5%).
- The Q3 2026 figure stands as the highest quarterly Accumulated Expenses since Q4 2021.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last 12 quarters, with growth averaging 9.5% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q1 2025, with growth of 15.2%; the weakest was Q4 2022, with a decline of 32.1%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $183.4 million (Q2 2026), $159.8 million (Q1 2026) and $185.2 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Trane Technologies | 90.38 Bn | 85.00 Bn | 2.38 Bn |
| 2 | Johnson Controls International | 84.95 Bn | 82.68 Bn | 2.47 Bn |
| 3 | Carrier Global | 46.14 Bn | 40.52 Bn | 1.90 Bn |
| 4 | Comfort Systems Usa | 37.91 Bn | 31.87 Bn | 934.48 Mn |
| 5 | Otis Worldwide | 30.83 Bn | 27.22 Bn | 1.16 Bn |
| 6 | Masco | 17.16 Bn | 14.96 Bn | 720.00 Mn |
| 7 | James Hardie Industries | 17.03 Bn | 16.09 Bn | 548.70 Mn |
| 8 | Allegion | 16.42 Bn | 15.05 Bn | 548.20 Mn |
| 9 | Carlisle Companies | 15.76 Bn | 12.66 Bn | 494.90 Mn |
| 10 | SPX Technologies | 7.68 Bn | 6.87 Bn | 279.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 183.40 Mn |
| Mar 28, 2026 | 159.80 Mn |
| Dec 31, 2025 | 185.20 Mn |
| Sep 27, 2025 | 174.00 Mn |
| Jun 28, 2025 | 166.20 Mn |
| Mar 29, 2025 | 145.40 Mn |
| Dec 31, 2024 | 170.80 Mn |
| Sep 28, 2024 | 160.60 Mn |
| Jun 29, 2024 | 150.70 Mn |
| Mar 30, 2024 | 126.20 Mn |
| Dec 31, 2023 | 168.50 Mn |
| Sep 30, 2023 | 147.10 Mn |
| Jul 1, 2023 | 131.20 Mn |
| Apr 1, 2023 | 121.30 Mn |
| Dec 31, 2022 | 148.00 Mn |
| Oct 1, 2022 | 194.60 Mn |
| Jul 2, 2022 | 182.70 Mn |
| Apr 2, 2022 | 177.40 Mn |
| Dec 31, 2021 | 217.90 Mn |
| Oct 2, 2021 | 240.60 Mn |
API Access
SPX Technologies Accumulated 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=accumulated-expenses&ticker=SPXC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "SPXC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=SPXC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();