Applied Energetics (AERG) Long-Term Debt Issuances (2017 - 2023)
Applied Energetics' Long-Term Debt Issuances came in at $155,541 for FY2023, down 11.3% from $175,435 in FY2022.
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Analysis
Applied Energetics (AERG) Long-Term Debt Issuances (2017 - 2023) Analysis & Trends
Going back to FY2017, Applied Energetics' Long-Term Debt Issuances data covers 6 years.
- Long-Term Debt Issuances carries a five-year compound annual growth rate of 0.8% (FY2018 to FY2023).
- The FY2023 figure represents the lowest annual Long-Term Debt Issuances since FY2018.
- Per Business Quant, earlier years put Long-Term Debt Issuances at $175,435 in FY2022, $4.32 million in FY2020 (+84.0%) and $2.35 million in FY2019.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Issuance (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 334.86 Bn | 293.38 Bn | 5.02 Bn | - |
| 2 | Rtx | 256.39 Bn | 224.66 Bn | 5.81 Bn | - |
| 3 | Boeing | 137.52 Bn | 46.48 Bn | 2.17 Bn | 11.00 Mn |
| 4 | Lockheed Martin | 130.55 Bn | 114.79 Bn | 2.44 Bn | - |
| 5 | General Dynamics | 95.65 Bn | 80.88 Bn | 2.25 Bn | - |
| 6 | Motorola Solutions | 85.05 Bn | 81.51 Bn | 1.77 Bn | 942.00 Mn |
| 7 | Howmet Aerospace | 81.91 Bn | 77.67 Bn | 1.00 Bn | - |
| 8 | Northrop Grumman | 74.74 Bn | 62.20 Bn | 2.35 Bn | - |
| 9 | Honeywell International | 69.91 Bn | 29.43 Bn | 2.02 Bn | - |
| 10 | Applied Energetics | 195.41 Mn | 182.39 Mn | 40,430.00 | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2023 | 155,541.00 |
| Mar 31, 2022 | 175,435.00 |
| Sep 30, 2020 | 4.32 Mn |
| Dec 31, 2019 | 200,000.00 |
| Sep 30, 2019 | 1.00 Mn |
| Jun 30, 2019 | 750,000.00 |
| Mar 31, 2019 | 400,000.00 |
| Sep 30, 2018 | 50,000.00 |
| Jun 30, 2018 | 7,500.00 |
| Mar 31, 2018 | 92,250.00 |
| Dec 31, 2017 | 90,000.00 |
API Access
Applied Energetics Long-Term Debt Issuances 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=long-term-debt-issuances&ticker=AERG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-issuances", "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=long-term-debt-issuances&ticker=AERG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();