Crane NXT (CXT) Operating Expenses (2009 - 2026)
Crane NXT (CXT) reported Operating Expenses of $139.7 million for Q2 2026, up 15.6% from $120.9 million a year earlier and up 4.5% from the prior quarter.
Crane NXT (CXT) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Crane NXT's Operating Expenses came in at $506.7 million, up 17.9% year-over-year; for FY2025, it came in at $457.1 million, up 15.3% from FY2024.
- Operating Expenses has increased for four consecutive years, though with a five-year compound annual growth rate of -8.9% (FY2020 to FY2025).
- By year, Operating Expenses came in at $396.3 million in FY2024 (+7.9%), $367.3 million in FY2023 (+13.1%), $324.9 million in FY2022 (+1.6%) and $319.7 million in FY2021 (-56.2%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q1 2022.
- Year over year, Operating Expenses has now increased in each of the last eight quarters, with growth averaging 17.2% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q1 2026 (growth of 29.9%); the low point was Q2 2022 (a decline of 58.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $133.7 million (Q1 2026), $122.6 million (Q4 2025) and $110.7 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 333.79 Bn | 305.49 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 197.60 Bn | 192.18 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 169.21 Bn | 137.30 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 152.39 Bn | 149.57 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 122.22 Bn | 120.34 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Emerson Electric | 89.77 Bn | 82.51 Bn | 2.66 Bn | 1.34 Bn |
| 7 | 3M | 84.26 Bn | 65.66 Bn | 2.68 Bn | 5.52 Bn |
| 8 | Vertiv Holdings | 79.29 Bn | 69.91 Bn | 1.23 Bn | 490.50 Mn |
| 9 | Illinois Tool Works | 77.45 Bn | 74.01 Bn | 1.90 Bn | - |
| 10 | Crane NXT | 3.27 Bn | 2.39 Bn | 208.60 Mn | 139.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 139.70 Mn |
| Mar 31, 2026 | 133.70 Mn |
| Dec 31, 2025 | 122.60 Mn |
| Sep 30, 2025 | 110.70 Mn |
| Jun 30, 2025 | 120.90 Mn |
| Mar 31, 2025 | 102.90 Mn |
| Dec 31, 2024 | 109.70 Mn |
| Sep 30, 2024 | 96.30 Mn |
| Jun 30, 2024 | 93.30 Mn |
| Mar 31, 2024 | 97.00 Mn |
| Dec 31, 2023 | 93.10 Mn |
| Sep 30, 2023 | 85.80 Mn |
| Jun 30, 2023 | 99.60 Mn |
| Mar 31, 2023 | 88.80 Mn |
| Dec 31, 2022 | 88.30 Mn |
| Sep 30, 2022 | 82.20 Mn |
| Jun 30, 2022 | 77.80 Mn |
| Mar 31, 2022 | 198.30 Mn |
| Dec 31, 2021 | -233.80 Mn |
| Sep 30, 2021 | 192.70 Mn |
Crane NXT Operating 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=operating-expenses&ticker=CXT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CXT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=CXT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();