Geo (GEO) Depreciation & Amortization (CF) (2009 - 2026)
Geo (GEO) reported Depreciation & Amortization (CF) of $34.2 million for Q2 2026, up 4.5% from $32.73 million a year earlier and up 1.1% from the prior quarter.
Geo (GEO) Depreciation & Amortization (CF) (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Geo's Depreciation & Amortization (CF) came in at $135.2 million, up 5.3% year-over-year; for FY2025, it came in at $132.04 million, up 4.6% from FY2024.
- Depreciation & Amortization (CF) has a five-year compound annual growth rate of -0.4% (FY2020 to FY2025).
- By year, Depreciation & Amortization (CF) came in at $126.22 million in FY2024 (+0.3%), $125.78 million in FY2023 (-5.4%), $132.93 million in FY2022 (-1.7%) and $135.18 million in FY2021 (+0.4%).
- The Q2 2026 figure ranks as the highest quarterly Depreciation & Amortization (CF) since Q1 2022.
- Year over year, Depreciation & Amortization (CF) has now increased in each of the last eight quarters, with growth averaging 4.1% over the last eight quarters.
- The high point for year-over-year Depreciation & Amortization (CF) in five years was Q4 2025 (growth of 7.4%); the low point was Q1 2023 (a decline of 11.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $33.83 million (Q1 2026), $34.13 million (Q4 2025) and $33.04 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Dep. & Amort. (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 141.87 Bn | 102.28 Bn | 6.13 Bn | 584.58 Mn |
| 2 | Cintas | 78.27 Bn | 77.46 Bn | 1.48 Bn | 81.60 Mn |
| 3 | Iron Mountain | 33.11 Bn | 32.63 Bn | 1.07 Bn | 202.85 Mn |
| 4 | APi | 17.29 Bn | 14.33 Bn | 703.00 Mn | 21.00 Mn |
| 5 | Rollins | 14.72 Bn | 14.27 Bn | 569.95 Mn | 33.61 Mn |
| 6 | Aramark | 14.39 Bn | 12.40 Bn | 430.34 Mn | 136.10 Mn |
| 7 | UL Solutions | 13.43 Bn | 12.22 Bn | 417.00 Mn | 46.00 Mn |
| 8 | Gartner | 12.17 Bn | 5.86 Bn | 1.19 Bn | 45.18 Mn |
| 9 | Rentokil Initial | 10.01 Bn | 3.35 Bn | - | - |
| 10 | Geo | 4.07 Bn | 3.68 Bn | - | 34.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 34.20 Mn |
| Mar 31, 2026 | 33.83 Mn |
| Dec 31, 2025 | 34.13 Mn |
| Sep 30, 2025 | 33.04 Mn |
| Jun 30, 2025 | 32.73 Mn |
| Mar 31, 2025 | 32.14 Mn |
| Dec 31, 2024 | 31.79 Mn |
| Sep 30, 2024 | 31.76 Mn |
| Jun 30, 2024 | 31.31 Mn |
| Mar 31, 2024 | 31.37 Mn |
| Dec 31, 2023 | 31.00 Mn |
| Sep 30, 2023 | 31.17 Mn |
| Jun 30, 2023 | 31.69 Mn |
| Mar 31, 2023 | 31.92 Mn |
| Dec 31, 2022 | 32.64 Mn |
| Sep 30, 2022 | 32.33 Mn |
| Jun 30, 2022 | 32.02 Mn |
| Mar 31, 2022 | 35.94 Mn |
| Dec 31, 2021 | 34.87 Mn |
| Sep 30, 2021 | 32.88 Mn |
Geo Depreciation & Amortization (CF) 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=depreciation-and-amortization-cf&ticker=GEO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "depreciation-and-amortization-cf", "ticker": "GEO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=depreciation-and-amortization-cf&ticker=GEO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();