Realloys (ALOY) Selling, General & Administrative (2015 - 2026)
Realloys (ALOY) reported Selling, General & Administrative of $36.03 million for Q2 2026, compared with $1.06 million a year earlier and down 57.8% from the prior quarter.
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Analysis
Realloys (ALOY) Selling, General & Administrative (2015 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Realloys' Selling, General & Administrative came in at $123.85 million; for FY2025, it came in at $4.5 million, up 26.2% from FY2024.
- Selling, General & Administrative has a five-year compound annual growth rate of 20.6% (FY2020 to FY2025).
- By year, Selling, General & Administrative came in at $3.57 million in FY2024 (-30.6%), $5.14 million in FY2023 (+8.7%), $4.73 million in FY2022 (+2.3%) and $4.63 million in FY2021 (+161.9%).
- Five-year quarterly Selling, General & Administrative spans a low of $655,904 in Q3 2025 and a high of $85.4 million in Q1 2026.
- Year over year, Selling, General & Administrative gained in two of the last six quarters, with growth averaging 10.8%.
- The high point for year-over-year Selling, General & Administrative in five years was Q4 2021 (growth of 263.2%); the low point was Q4 2022 (a decline of 51.6%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $85.4 million (Q1 2026), $1.76 million (Q4 2025) and $655,904 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | SG&A (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 453.55 Bn | 422.61 Bn | 1.64 Bn | 194.58 Mn |
| 2 | Oracle | 430.98 Bn | 303.54 Bn | - | 376.00 Mn |
| 3 | Sap Se | 256.23 Bn | 177.31 Bn | 8.40 Bn | -469.59 Mn |
| 4 | Salesforce | 193.08 Bn | 148.96 Bn | 8.70 Bn | 725.00 Mn |
| 5 | ServiceNow | 138.94 Bn | 117.40 Bn | 2.82 Bn | 369.00 Mn |
| 6 | Automatic Data Processing | 102.51 Bn | 84.63 Bn | 2.51 Bn | 1.25 Bn |
| 7 | Intuit | 75.44 Bn | 54.79 Bn | 3.44 Bn | 391.00 Mn |
| 8 | Relx | 60.79 Bn | 57.76 Bn | - | - |
| 9 | Strategy | 56.32 Bn | 49.31 Bn | 81.55 Mn | 39.92 Mn |
| 10 | Realloys | 558.51 Mn | 558.51 Mn | 475,000.00 | 36.03 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.03 Mn |
| Mar 31, 2026 | 85.40 Mn |
| Dec 31, 2025 | 1.76 Mn |
| Sep 30, 2025 | 655,904.00 |
| Jun 30, 2025 | 1.06 Mn |
| Mar 31, 2025 | 867,000.00 |
| Dec 31, 2024 | 832,816.00 |
| Sep 30, 2024 | 891,282.00 |
| Jun 30, 2024 | 938,269.00 |
| Mar 31, 2024 | 905,929.00 |
| Dec 31, 2023 | 1.06 Mn |
| Sep 30, 2023 | 957,372.00 |
| Jun 30, 2023 | 1.35 Mn |
| Mar 31, 2023 | 1.78 Mn |
| Dec 31, 2022 | 1.11 Mn |
| Sep 30, 2022 | 1.20 Mn |
| Jun 30, 2022 | 1.19 Mn |
| Mar 31, 2022 | 1.22 Mn |
| Dec 31, 2021 | 2.30 Mn |
| Sep 30, 2021 | 1.10 Mn |
API Access
Realloys Selling, General & Administrative 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=selling-general-and-administrative&ticker=ALOY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "selling-general-and-administrative", "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=selling-general-and-administrative&ticker=ALOY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();