Globalfoundries (GFS) Return on Capital Employed [ROCE] (2021 - 2026)
Globalfoundries (GFS) recorded Return on Capital Employed [ROCE] of 5.48% in Q2 2026, up 6.66 percentage points from -1.19% a year earlier but down 0.15 percentage points from the prior quarter.
Globalfoundries (GFS) Return on Capital Employed [ROCE] (2021 - 2026) Analysis & Trends
For FY2025, Globalfoundries reported Return on Capital Employed [ROCE] of 5.46%, up 6.95 percentage points from FY2024.
- Annual Return on Capital Employed [ROCE] has a five-year change of +33.58 percentage points (FY2020 to FY2025).
- Across earlier years, Return on Capital Employed [ROCE] came in at -1.49% in FY2024 (-9.09 pp), 7.61% in FY2023 (-1.32 pp), 8.93% in FY2022 (+9.50 pp) and -0.57% in FY2021 (+27.55 pp).
- Quarterly Return on Capital Employed [ROCE] has ranged from -1.49% in Q4 2024 to 8.25% in Q1 2023 over the past five years.
- On a year-over-year basis, Return on Capital Employed [ROCE] has increased for three consecutive quarters, with an average year-over-year change of -1.44 percentage points over the last eight quarters.
- Peak year-over-year performance for Return on Capital Employed [ROCE] in the last five years was a gain of 8.79 percentage points in Q4 2022, against a drop of 9.09 percentage points in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at 5.62% (Q1 2026), 5.48% (Q4 2025) and -1.08% (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROCE (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,757.49 Bn | 5,531.65 Bn | 72.14 Bn | 80.04% |
| 2 | Taiwan Semiconductor Manufacturing | 2,520.17 Bn | 2,145.88 Bn | 27.22 Bn | 8.47% |
| 3 | Broadcom | 1,730.62 Bn | 1,656.67 Bn | 20.46 Bn | 26.30% |
| 4 | Micron Technology | 1,201.21 Bn | 1,139.97 Bn | 35.06 Bn | 60.25% |
| 5 | Advanced Micro Devices | 1,031.02 Bn | 987.76 Bn | 6.20 Bn | 9.27% |
| 6 | Asml Holding | 716.82 Bn | 672.66 Bn | 5.90 Bn | - |
| 7 | Intel | 585.95 Bn | 470.68 Bn | 6.51 Bn | -0.05% |
| 8 | Lam Research | 432.69 Bn | 409.49 Bn | 3.48 Bn | 50.54% |
| 9 | Applied Materials | 430.35 Bn | 395.79 Bn | 4.59 Bn | 28.98% |
| 10 | Globalfoundries | 26.99 Bn | 15.36 Bn | 505.00 Mn | 5.48% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.48% |
| Mar 31, 2026 | 5.62% |
| Dec 31, 2025 | 5.48% |
| Sep 30, 2025 | -1.08% |
| Jun 30, 2025 | -1.19% |
| Mar 31, 2025 | -1.48% |
| Dec 31, 2024 | -1.49% |
| Sep 30, 2024 | 5.17% |
| Jun 30, 2024 | 5.64% |
| Mar 31, 2024 | 6.40% |
| Dec 31, 2023 | 7.61% |
| Sep 30, 2023 | 7.39% |
| Jun 30, 2023 | 8.05% |
| Mar 31, 2023 | 8.25% |
| Dec 31, 2022 | 8.24% |
| Sep 30, 2022 | 7.53% |
| Jun 30, 2022 | 5.19% |
| Mar 31, 2022 | 2.15% |
| Dec 31, 2021 | -0.55% |
Globalfoundries Return on Capital Employed [ROCE] 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=return-on-capital-employed-%5Broce%5D&ticker=GFS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-capital-employed-[roce]", "ticker": "GFS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=return-on-capital-employed-%5Broce%5D&ticker=GFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();