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 | 324.11 Bn | 277.88 Bn | 4.68 Bn | - |
| 2 | Rtx | 259.48 Bn | 230.96 Bn | 5.13 Bn | - |
| 3 | Boeing | 151.52 Bn | 58.21 Bn | 2.41 Bn | 11.00 Mn |
| 4 | Lockheed Martin | 126.52 Bn | 113.24 Bn | 2.45 Bn | - |
| 5 | General Dynamics | 92.31 Bn | 79.43 Bn | 2.18 Bn | - |
| 6 | Howmet Aerospace | 88.22 Bn | 83.82 Bn | 951.00 Mn | - |
| 7 | Motorola Solutions | 76.09 Bn | 72.44 Bn | 1.68 Bn | - |
| 8 | Northrop Grumman | 72.54 Bn | 61.78 Bn | 2.12 Bn | - |
| 9 | Honeywell International | 66.60 Bn | 18.72 Bn | 3.65 Bn | - |
| 10 | Applied Energetics | 196.56 Mn | 183.54 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();