Abm Industries (ABM) Accumulated Expenses (2010 - 2026)
Abm Industries (ABM) posted Accumulated Expenses of $204.5 million for fiscal Q3 2026 (quarter ended Jul 31, 2026), up 2.4% from $199.7 million a year earlier but down 1.1% from the prior quarter.
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Analysis
Abm Industries (ABM) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Oct 31, 2025), Abm Industries' Accumulated Expenses came in at $200.8 million, up 1.7% from FY2024.
- Annual Accumulated Expenses has increased for three consecutive fiscal years, with a five-year compound annual growth rate of 5.3% (FY2020 to FY2025).
- In prior fiscal years, Abm Industries' Accumulated Expenses was $197.5 million in FY2024 (+11.6%), $177 million in FY2023 (+3.3%), $171.4 million in FY2022 (unchanged) and $171.4 million in FY2021 (+10.4%).
- Quarterly Accumulated Expenses has run from a low of $169.1 million in fiscal Q1 2022 to a high of $206.8 million in fiscal Q2 2026 over five years.
- On a year-over-year basis, Accumulated Expenses increased in seven of the last eight quarters, with growth averaging 3.9%.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was fiscal Q4 2024, with growth of 11.6%; the weakest was fiscal Q1 2026, with a decline of 0.1%.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $206.8 million (Q2 2026), $202.1 million (Q1 2026) and $200.8 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Accenture | 160.61 Bn | 119.89 Bn | 6.13 Bn |
| 2 | Cintas | 89.83 Bn | 88.91 Bn | 1.55 Bn |
| 3 | Iron Mountain | 34.25 Bn | 33.44 Bn | 1.07 Bn |
| 4 | APi | 19.55 Bn | 16.77 Bn | 770.00 Mn |
| 5 | Rollins | 17.23 Bn | 16.77 Bn | 582.90 Mn |
| 6 | Gartner | 15.63 Bn | 9.33 Bn | 1.19 Bn |
| 7 | UL Solutions | 15.13 Bn | 13.89 Bn | 417.00 Mn |
| 8 | Aramark | 14.29 Bn | 12.24 Bn | 430.34 Mn |
| 9 | Rentokil Initial | 12.16 Bn | 5.68 Bn | - |
| 10 | Abm Industries | 3.20 Bn | 2.79 Bn | 286.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 204.50 Mn |
| Apr 30, 2026 | 206.80 Mn |
| Jan 31, 2026 | 202.10 Mn |
| Oct 31, 2025 | 200.80 Mn |
| Jul 31, 2025 | 199.70 Mn |
| Apr 30, 2025 | 202.40 Mn |
| Jan 31, 2025 | 202.30 Mn |
| Oct 31, 2024 | 197.50 Mn |
| Jul 31, 2024 | 191.20 Mn |
| Apr 30, 2024 | 196.30 Mn |
| Jan 31, 2024 | 190.50 Mn |
| Oct 31, 2023 | 177.00 Mn |
| Jul 31, 2023 | 177.70 Mn |
| Apr 30, 2023 | 182.10 Mn |
| Jan 31, 2023 | 175.50 Mn |
| Oct 31, 2022 | 171.40 Mn |
| Jul 31, 2022 | 172.70 Mn |
| Apr 30, 2022 | 170.30 Mn |
| Jan 31, 2022 | 169.10 Mn |
| Oct 31, 2021 | 171.40 Mn |
API Access
Abm Industries 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=ABM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "ABM", "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=ABM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();