Air T (AIRT) Total Liabilities (2011 - 2026)
Air T's Total Liabilities was $402.2 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 108.4% from $192.96 million a year earlier and up 22.5% from the prior quarter.
Air T (AIRT) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Total Liabilities at Air T came in at $328.25 million, up 87.3% from FY2025.
- Total Liabilities shows a five-year compound annual growth rate of 21.1% (FY2021 to FY2026).
- In earlier fiscal years, Total Liabilities was $175.3 million in FY2025 (+2.3%), $171.35 million in FY2024 (-3.0%), $176.58 million in FY2023 (-2.9%) and $181.88 million in FY2022 (+44.3%).
- The fiscal Q1 2027 figure marks the highest quarterly Total Liabilities in data going back to fiscal Q4 2011.
- Compared with a year earlier, Total Liabilities has increased for three straight quarters, with growth averaging 44.5% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was fiscal Q3 2026 (growth of 112.4%); the worst was fiscal Q2 2024 (a decline of 20.4%).
- Per Business Quant data, AIRT's Total Liabilities in the three fiscal quarters before Q1 2027 was $328.25 million (Q4 2026), $383.91 million (Q3 2026) and $185.65 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 343.33 Bn | 301.85 Bn | 5.02 Bn | 109.44 Bn |
| 2 | Rtx | 263.31 Bn | 231.58 Bn | 5.81 Bn | 105.63 Bn |
| 3 | Boeing | 138.56 Bn | 47.52 Bn | 2.17 Bn | 164.18 Bn |
| 4 | Lockheed Martin | 134.21 Bn | 118.45 Bn | 2.44 Bn | 54.45 Bn |
| 5 | General Dynamics | 97.50 Bn | 82.74 Bn | 2.25 Bn | 32.91 Bn |
| 6 | Motorola Solutions | 86.68 Bn | 83.15 Bn | 1.77 Bn | 18.06 Bn |
| 7 | Howmet Aerospace | 85.32 Bn | 81.08 Bn | 1.00 Bn | 7.52 Bn |
| 8 | Northrop Grumman | 76.52 Bn | 63.97 Bn | 2.35 Bn | 33.81 Bn |
| 9 | Honeywell International | 72.51 Bn | 32.02 Bn | 2.02 Bn | 30.44 Bn |
| 10 | Air T | 76.86 Mn | -19.06 Mn | 70.16 Mn | 402.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 402.20 Mn |
| Mar 31, 2026 | 328.25 Mn |
| Dec 31, 2025 | 383.91 Mn |
| Sep 30, 2025 | 185.65 Mn |
| Jun 30, 2025 | 192.96 Mn |
| Mar 31, 2025 | 175.30 Mn |
| Dec 31, 2024 | 180.72 Mn |
| Sep 30, 2024 | 188.31 Mn |
| Jun 30, 2024 | 170.32 Mn |
| Mar 31, 2024 | 171.35 Mn |
| Dec 31, 2023 | 154.83 Mn |
| Sep 30, 2023 | 160.82 Mn |
| Jun 30, 2023 | 174.79 Mn |
| Mar 31, 2023 | 176.58 Mn |
| Dec 31, 2022 | 189.91 Mn |
| Sep 30, 2022 | 201.99 Mn |
| Jun 30, 2022 | 187.96 Mn |
| Mar 31, 2022 | 181.88 Mn |
| Dec 31, 2021 | 142.50 Mn |
| Sep 30, 2021 | 132.65 Mn |
Air T Total Liabilities 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=total-liabilities&ticker=AIRT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "AIRT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=AIRT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();