Realloys (ALOY) Operating Margin (2016 - 2026)
Realloys' Operating Margin was -4577.61% in Q2 2026, down 4372.61 percentage points from -205.00% a year earlier but up 7838.39 percentage points from the prior quarter.
Realloys (ALOY) Operating Margin (2016 - 2026) Analysis & Trends
On a trailing twelve-month basis, Realloys' Operating Margin was -4460.02% through Jun 30, 2026, down 4257.42 percentage points year-over-year; for FY2025, it came in at -165.69%, down 36.78 percentage points from FY2024.
- Operating Margin shows a five-year change of -153.43 percentage points (FY2020 to FY2025).
- In earlier years, Operating Margin was -128.91% in FY2024 (+41.65 pp), -170.56% in FY2023 (-78.89 pp), -91.67% in FY2022 (-54.40 pp) and -37.27% in FY2021 (-25.01 pp).
- Quarterly Operating Margin has moved between -12416.01% (Q1 2026) and -33.90% (Q3 2021) over five years.
- Compared with a year earlier, Operating Margin was higher in two of the last six quarters, with an average year-over-year change of -752.38 percentage points.
- The best year-over-year quarter for Operating Margin over five years was Q1 2024 (a gain of 93.60 percentage points); the worst was Q2 2026 (a drop of 4372.61 percentage points).
- Per Business Quant data, ALOY's Operating Margin in the three quarters before Q2 2026 was -12416.01% (Q1 2026), -247.99% (Q4 2025) and -62.97% (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Operating Margin (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 449.27 Bn | 418.33 Bn | 1.64 Bn | 47.12% |
| 2 | Oracle | 417.01 Bn | 289.56 Bn | - | 34.78% |
| 3 | Sap Se | 258.97 Bn | 180.05 Bn | 8.40 Bn | 26.76% |
| 4 | Salesforce | 185.51 Bn | 141.38 Bn | 8.70 Bn | 20.55% |
| 5 | ServiceNow | 134.41 Bn | 112.87 Bn | 2.82 Bn | 4.06% |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | -33.33% |
| 7 | Intuit | 71.93 Bn | 51.28 Bn | 3.44 Bn | 10.91% |
| 8 | Relx | 60.47 Bn | 57.43 Bn | - | - |
| 9 | Strategy | 54.44 Bn | 47.43 Bn | 81.55 Mn | -6,808.11% |
| 10 | Realloys | 550.26 Mn | 550.26 Mn | 475,000.00 | -4,577.61% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -4,577.61% |
| Mar 31, 2026 | -12,416.01% |
| Dec 31, 2025 | -247.99% |
| Sep 30, 2025 | -62.97% |
| Jun 30, 2025 | -205.00% |
| Dec 31, 2024 | -151.46% |
| Sep 30, 2024 | -113.32% |
| Jun 30, 2024 | -120.48% |
| Mar 31, 2024 | -133.04% |
| Dec 31, 2023 | -134.46% |
| Sep 30, 2023 | -119.32% |
| Jun 30, 2023 | -194.10% |
| Mar 31, 2023 | -226.64% |
| Dec 31, 2022 | -108.39% |
| Sep 30, 2022 | -98.29% |
| Jun 30, 2022 | -83.52% |
| Mar 31, 2022 | -80.25% |
| Dec 31, 2021 | -107.07% |
| Sep 30, 2021 | -33.90% |
| Jun 30, 2021 | -8.03% |
Realloys Operating Margin 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-margin&ticker=ALOY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-margin", "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=operating-margin&ticker=ALOY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();