Rogers (ROG) Operating Expenses (2010 - 2026)
Rogers' Operating Expenses was $50.2 million in Q2 2026, down 61.9% from $131.6 million a year earlier and down 6.7% from the prior quarter.
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Analysis
Rogers (ROG) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Rogers' Operating Expenses was $216.7 million through Jun 30, 2026, down 32.9% year-over-year; for FY2025, it came in at $301.8 million, up 19.7% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 6.1% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $252.1 million in FY2024 (-1.1%), $254.9 million in FY2023 (-20.5%), $320.6 million in FY2022 (+41.5%) and $226.6 million in FY2021 (+0.9%).
- The Q2 2026 figure marks the lowest quarterly Operating Expenses since Q2 2020.
- Compared with a year earlier, Operating Expenses has declined for four straight quarters, with growth averaging 5.7% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2025 (growth of 112.9%); the worst was Q2 2026 (a decline of 61.9%).
- Per Business Quant data, ROG's Operating Expenses in the three quarters before Q2 2026 was $53.8 million (Q1 2026), $56.6 million (Q4 2025) and $56.1 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Linde | 231.67 Bn | 213.25 Bn | 4.43 Bn | 928.00 Mn |
| 2 | Corning | 116.51 Bn | 109.07 Bn | 1.63 Bn | 907.00 Mn |
| 3 | Sherwin Williams | 81.70 Bn | 80.74 Bn | 3.34 Bn | 2.10 Bn |
| 4 | Air Products & Chemicals | 67.33 Bn | 62.52 Bn | 1.04 Bn | 3.15 Bn |
| 5 | LyondellBasell Industries | 41.01 Bn | 30.52 Bn | 2.04 Bn | 7.63 Bn |
| 6 | Nutrien | 33.46 Bn | 30.29 Bn | 3.25 Bn | 235.00 Mn |
| 7 | Qnity Electronics | 25.24 Bn | 22.38 Bn | 666.00 Mn | 298.00 Mn |
| 8 | Ati | 25.13 Bn | 23.15 Bn | 309.80 Mn | 99.60 Mn |
| 9 | Ppg Industries | 24.28 Bn | 16.93 Bn | 1.81 Bn | 1.15 Bn |
| 10 | Rogers | 2.48 Bn | 1.71 Bn | 70.40 Mn | 50.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 50.20 Mn |
| Mar 31, 2026 | 53.80 Mn |
| Dec 31, 2025 | 56.60 Mn |
| Sep 30, 2025 | 56.10 Mn |
| Jun 30, 2025 | 131.60 Mn |
| Mar 31, 2025 | 57.50 Mn |
| Dec 31, 2024 | 74.30 Mn |
| Sep 30, 2024 | 59.50 Mn |
| Jun 30, 2024 | 61.80 Mn |
| Mar 31, 2024 | 56.50 Mn |
| Dec 31, 2023 | 62.50 Mn |
| Sep 30, 2023 | 54.00 Mn |
| Jun 30, 2023 | 58.20 Mn |
| Mar 31, 2023 | 80.20 Mn |
| Dec 31, 2022 | 129.54 Mn |
| Sep 30, 2022 | 60.17 Mn |
| Jun 30, 2022 | 64.87 Mn |
| Mar 31, 2022 | 66.03 Mn |
| Dec 31, 2021 | 65.89 Mn |
| Sep 30, 2021 | 56.42 Mn |
API Access
Rogers 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=ROG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ROG", "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=ROG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();