Rtx (RTX) Change in Inventory (2009 - 2026)
Rtx (RTX) posted Change in Inventory of $543 million for Q3 2026, compared with -$182 million a year earlier and up 64.5% from the prior quarter.
Rtx (RTX) Change in Inventory (2009 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Change in Inventory at Rtx was $1.2 billion, up 53.4% year-over-year; for FY2025, it was $532 million, down 63.9% from FY2024.
- In prior years, Rtx's Change in Inventory was $1.47 billion in FY2024 (+33.5%), $1.1 billion in FY2023 (-29.9%), $1.58 billion in FY2022 and -$163 million in FY2021.
- Quarterly Change in Inventory has run from a low of -$483 million in Q4 2025 to a high of $813 million in Q1 2026 over five years.
- On a year-over-year basis, Change in Inventory increased in 1 of the last four quarters, with an average decline of 8.6%.
- The strongest year-over-year quarter for Change in Inventory in the past five years was Q1 2022, with growth of 419.5%; the weakest was Q3 2023, with a decline of 73.1%.
- According to Business Quant data, Change in Inventory for the three prior quarters was $330 million (Q2 2026), $813 million (Q1 2026) and -$483 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 339.69 Bn | 298.21 Bn | 5.02 Bn | 322.00 Mn |
| 2 | Rtx | 265.90 Bn | 234.17 Bn | 5.81 Bn | 543.00 Mn |
| 3 | Boeing | 141.68 Bn | 50.64 Bn | 2.17 Bn | 2.87 Bn |
| 4 | Lockheed Martin | 140.71 Bn | 124.94 Bn | 2.44 Bn | -424.00 Mn |
| 5 | General Dynamics | 99.12 Bn | 86.23 Bn | 2.18 Bn | -80.00 Mn |
| 6 | Howmet Aerospace | 86.37 Bn | 82.12 Bn | 1.00 Bn | -48.00 Mn |
| 7 | Motorola Solutions | 81.13 Bn | 77.47 Bn | 1.68 Bn | 156.00 Mn |
| 8 | Northrop Grumman | 74.95 Bn | 62.41 Bn | 2.35 Bn | -53.00 Mn |
| 9 | Honeywell International | 71.67 Bn | 23.80 Bn | 3.65 Bn | 31.00 Mn |
| 10 | TransDigm | 70.09 Bn | 58.09 Bn | 1.63 Bn | 87.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 543.00 Mn |
| Jun 30, 2026 | 330.00 Mn |
| Mar 31, 2026 | 813.00 Mn |
| Dec 31, 2025 | -483.00 Mn |
| Sep 30, 2025 | -182.00 Mn |
| Jun 30, 2025 | 384.00 Mn |
| Mar 31, 2025 | 813.00 Mn |
| Dec 31, 2024 | -231.00 Mn |
| Sep 30, 2024 | 344.00 Mn |
| Jun 30, 2024 | 715.00 Mn |
| Mar 31, 2024 | 646.00 Mn |
| Dec 31, 2023 | -326.00 Mn |
| Sep 30, 2023 | 108.00 Mn |
| Jun 30, 2023 | 602.00 Mn |
| Mar 31, 2023 | 720.00 Mn |
| Dec 31, 2022 | 141.00 Mn |
| Sep 30, 2022 | 401.00 Mn |
| Jun 30, 2022 | 446.00 Mn |
| Mar 31, 2022 | 587.00 Mn |
| Dec 31, 2021 | -220.00 Mn |
Rtx Change in Inventory 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=change-in-inventory&ticker=RTX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-inventory", "ticker": "RTX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-inventory&ticker=RTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();