Realloys (ALOY) Return on Capital Employed [ROCE] (2015 - 2026)
Realloys (ALOY) recorded Return on Capital Employed [ROCE] of -76.60% in Q2 2026, up 9.07 percentage points from -85.67% a year earlier and up 16.42 percentage points from the prior quarter.
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Analysis
Realloys (ALOY) Return on Capital Employed [ROCE] (2015 - 2026) Analysis & Trends
For FY2025, Realloys reported Return on Capital Employed [ROCE] of -9.06%, up 50.12 percentage points from FY2024.
- Annual Return on Capital Employed [ROCE] has a four-year change of +61.57 percentage points (FY2021 to FY2025).
- Across earlier years, Return on Capital Employed [ROCE] came in at -59.18% in FY2024 (+50.06 pp), -109.24% in FY2023 (-32.06 pp), -77.18% in FY2022 (-6.56 pp) and -70.62% in FY2021.
- Quarterly Return on Capital Employed [ROCE] has ranged from -300.89% in Q1 2023 to -8.57% in Q4 2025 over the past five years.
- On a year-over-year basis, Return on Capital Employed [ROCE] rose in four of the last eight quarters, with an average year-over-year change of +2.92 percentage points.
- Peak year-over-year performance for Return on Capital Employed [ROCE] in the last five years was a gain of 242.56 percentage points in Q1 2024, against a drop of 253.25 percentage points in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at -93.02% (Q1 2026), -8.57% (Q4 2025) and -56.36% (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROCE (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 453.55 Bn | 422.61 Bn | 1.64 Bn | 28.02% |
| 2 | Oracle | 430.98 Bn | 303.54 Bn | - | 9.81% |
| 3 | Sap Se | 256.23 Bn | 177.31 Bn | 8.40 Bn | 33.74% |
| 4 | Salesforce | 193.08 Bn | 148.96 Bn | 8.70 Bn | 10.68% |
| 5 | ServiceNow | 138.94 Bn | 117.40 Bn | 2.82 Bn | 10.59% |
| 6 | Automatic Data Processing | 102.51 Bn | 84.63 Bn | 2.51 Bn | -46.62% |
| 7 | Intuit | 75.44 Bn | 54.79 Bn | 3.44 Bn | 21.09% |
| 8 | Relx | 60.79 Bn | 57.76 Bn | - | - |
| 9 | Strategy | 56.32 Bn | 49.31 Bn | 81.55 Mn | -68.70% |
| 10 | Realloys | 558.51 Mn | 558.51 Mn | 475,000.00 | -76.60% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -76.60% |
| Mar 31, 2026 | -93.02% |
| Dec 31, 2025 | -8.57% |
| Sep 30, 2025 | -56.36% |
| Jun 30, 2025 | -85.67% |
| Mar 31, 2025 | -70.35% |
| Dec 31, 2024 | -58.51% |
| Sep 30, 2024 | -53.57% |
| Jun 30, 2024 | -64.27% |
| Mar 31, 2024 | -58.33% |
| Dec 31, 2023 | -70.90% |
| Sep 30, 2023 | -64.39% |
| Jun 30, 2023 | -111.86% |
| Mar 31, 2023 | -300.89% |
| Dec 31, 2022 | -138.03% |
| Sep 30, 2022 | -117.39% |
| Jun 30, 2022 | -79.52% |
| Mar 31, 2022 | -47.64% |
| Dec 31, 2021 | -71.51% |
| Dec 31, 2017 | -4,054.02% |
API Access
Realloys 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=ALOY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-capital-employed-[roce]", "ticker": "ALOY", "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=ALOY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();