Air T (AIRT) Accumulated Expenses (2011 - 2026)
Air T (AIRT) posted Accumulated Expenses of $55.77 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), up 170.4% from $20.62 million a year earlier and up 12.2% from the prior quarter.
Air T (AIRT) Accumulated Expenses (2011 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Air T's Accumulated Expenses came in at $49.72 million, up 197.9% from FY2025.
- Annual Accumulated Expenses has increased for three consecutive fiscal years, with a four-year compound annual growth rate of 38.8% (FY2022 to FY2026).
- In prior fiscal years, Air T's Accumulated Expenses was $16.69 million in FY2025 (+6.7%), $15.65 million in FY2024 (+19.2%), $13.13 million in FY2023 (-1.9%) and $13.39 million in FY2022.
- The fiscal Q1 2027 figure stands as the highest quarterly Accumulated Expenses in data going back to fiscal Q4 2011.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last eight quarters, with growth averaging 88.5% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was fiscal Q4 2026, with growth of 197.9%; the weakest was fiscal Q3 2024, with a decline of 19.5%.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $49.72 million (Q4 2026), $46.52 million (Q3 2026) and $22.06 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | General Electric | 321.31 Bn | 275.31 Bn | 4.68 Bn |
| 2 | Rtx | 248.97 Bn | 222.19 Bn | 5.13 Bn |
| 3 | Boeing | 152.99 Bn | 59.70 Bn | 2.41 Bn |
| 4 | Lockheed Martin | 116.67 Bn | 103.39 Bn | 2.45 Bn |
| 5 | Howmet Aerospace | 92.54 Bn | 88.15 Bn | 951.00 Mn |
| 6 | General Dynamics | 89.31 Bn | 76.42 Bn | 2.18 Bn |
| 7 | Motorola Solutions | 74.04 Bn | 70.40 Bn | 1.68 Bn |
| 8 | Northrop Grumman | 67.90 Bn | 57.15 Bn | 2.12 Bn |
| 9 | Honeywell International | 67.82 Bn | 20.27 Bn | 3.65 Bn |
| 10 | Air T | 80.21 Mn | 582,585.15 | 70.16 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 55.77 Mn |
| Mar 31, 2026 | 49.72 Mn |
| Dec 31, 2025 | 46.52 Mn |
| Sep 30, 2025 | 22.06 Mn |
| Jun 30, 2025 | 20.62 Mn |
| Mar 31, 2025 | 16.69 Mn |
| Dec 31, 2024 | 16.30 Mn |
| Sep 30, 2024 | 14.33 Mn |
| Jun 30, 2024 | 14.53 Mn |
| Mar 31, 2024 | 15.65 Mn |
| Dec 31, 2023 | 12.03 Mn |
| Sep 30, 2023 | 12.30 Mn |
| Jun 30, 2023 | 14.64 Mn |
| Mar 31, 2023 | 13.13 Mn |
| Dec 31, 2022 | 14.94 Mn |
| Sep 30, 2022 | 13.63 Mn |
| Jun 30, 2022 | 14.22 Mn |
| Mar 31, 2022 | 13.39 Mn |
| Jun 30, 2019 | 401,275.00 |
| Mar 31, 2019 | 3.16 Mn |
Air T Accumulated Expenses 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=accumulated-expenses&ticker=AIRT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "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=accumulated-expenses&ticker=AIRT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();