Applied Energetics (AERG) Return on Sales [ROS] (2011 - 2026)
Applied Energetics (AERG) recorded Return on Sales [ROS] of -6934.90% in Q2 2026, down 1552.45 percentage points from -5382.46% a year earlier.
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Analysis
Applied Energetics (AERG) Return on Sales [ROS] (2011 - 2026) Analysis & Trends
On a TTM basis, Applied Energetics' Return on Sales [ROS] came in at -5149.65% as of Jun 30, 2026, down 4513.77 percentage points year-over-year; for FY2025, it came in at -3233.57%, down 2855.38 percentage points from FY2024.
- Annual Return on Sales [ROS] has a five-year change of -255.13 percentage points (FY2020 to FY2025).
- Across earlier years, Return on Sales [ROS] came in at -378.19% in FY2024 (-97.12 pp), -281.07% in FY2023 (+160.12 pp) and -441.18% in FY2022.
- The Q2 2026 figure is the lowest quarterly Return on Sales [ROS] since Q2 2020.
- On a year-over-year basis, Return on Sales [ROS] rose in 1 of the last seven quarters, with an average year-over-year change of -2140.61 percentage points.
- Peak year-over-year performance for Return on Sales [ROS] in the last five years was a gain of 487.93 percentage points in Q2 2023, against a drop of 5320.13 percentage points in Q4 2025 at the low end.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 295.17 Bn | 253.91 Bn | 5.02 Bn | -47.62% |
| 2 | Rtx | 257.77 Bn | 227.75 Bn | 5.81 Bn | 13.37% |
| 3 | Boeing | 148.82 Bn | 55.52 Bn | 2.41 Bn | 0.64% |
| 4 | Lockheed Martin | 139.64 Bn | 123.87 Bn | 2.44 Bn | 11.80% |
| 5 | General Dynamics | 94.53 Bn | 81.64 Bn | 2.18 Bn | 10.36% |
| 6 | Motorola Solutions | 79.77 Bn | 76.13 Bn | 1.68 Bn | 25.82% |
| 7 | Northrop Grumman | 78.36 Bn | 65.81 Bn | 2.35 Bn | 11.41% |
| 8 | Howmet Aerospace | 74.35 Bn | 69.95 Bn | 951.00 Mn | 27.92% |
| 9 | Honeywell International | 70.09 Bn | 22.54 Bn | 3.65 Bn | 18.37% |
| 10 | Applied Energetics | 207.09 Mn | 194.07 Mn | 40,430.00 | -6,934.90% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -6,934.90% |
| Dec 31, 2025 | -5,598.60% |
| Sep 30, 2025 | -3,643.80% |
| Jun 30, 2025 | -5,382.46% |
| Mar 31, 2025 | -1,480.64% |
| Dec 31, 2024 | -278.47% |
| Sep 30, 2024 | -317.63% |
| Jun 30, 2024 | -264.04% |
| Mar 31, 2024 | -1,946.91% |
| Dec 31, 2023 | -206.05% |
| Sep 30, 2023 | -256.67% |
| Jun 30, 2023 | -327.01% |
| Mar 31, 2023 | -398.36% |
| Dec 31, 2022 | -276.94% |
| Sep 30, 2022 | -161.64% |
| Jun 30, 2022 | -814.94% |
| Dec 31, 2020 | -2,978.43% |
| Sep 30, 2020 | -770.28% |
| Mar 31, 2020 | -12,195.84% |
| Sep 30, 2015 | -17,025.39% |
API Access
Applied Energetics Return on Sales [ROS] 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-sales-%5Bros%5D&ticker=AERG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "AERG", "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-sales-%5Bros%5D&ticker=AERG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();