VirTra (VTSI) Inventory (2016 - 2026)
VirTra (VTSI) posted Inventory of $14.19 million for Q2 2026, up 10.8% from $12.81 million a year earlier but down 1.2% from the prior quarter.
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Analysis
VirTra (VTSI) Inventory (2016 - 2026) Analysis & Trends
At the end of FY2025, VirTra's Inventory came in at $13.06 million, down 10.4% from FY2024.
- Annual Inventory shows a five-year compound annual growth rate of 30.0% (FY2020 to FY2025).
- In prior years, VirTra's Inventory was $14.58 million in FY2024 (+17.6%), $12.4 million in FY2023 (+29.3%), $9.59 million in FY2022 (+91.3%) and $5.01 million in FY2021 (+42.6%).
- Quarterly Inventory has run from a low of $5.01 million in Q4 2021 to a high of $14.99 million in Q1 2025 over five years.
- On a year-over-year basis, Inventory increased in four of the last eight quarters, with growth averaging 6.1%.
- The strongest year-over-year quarter for Inventory in the past five years was Q4 2022, with growth of 91.3%; the weakest was Q3 2025, with a decline of 11.3%.
- According to Business Quant data, Inventory for the three prior quarters was $14.37 million (Q1 2026), $13.06 million (Q4 2025) and $12.34 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.21 Bn | 284.21 Bn | 4.68 Bn | 12.44 Bn |
| 2 | Rtx | 252.88 Bn | 226.09 Bn | 5.13 Bn | 14.41 Bn |
| 3 | Boeing | 145.76 Bn | 52.46 Bn | 2.41 Bn | 88.39 Bn |
| 4 | Lockheed Martin | 119.56 Bn | 106.28 Bn | 2.45 Bn | 4.41 Bn |
| 5 | Howmet Aerospace | 91.38 Bn | 86.98 Bn | 951.00 Mn | 2.18 Bn |
| 6 | General Dynamics | 90.40 Bn | 77.51 Bn | 2.18 Bn | 9.10 Bn |
| 7 | Motorola Solutions | 74.81 Bn | 71.18 Bn | 1.68 Bn | 1.33 Bn |
| 8 | Northrop Grumman | 71.85 Bn | 61.10 Bn | 2.12 Bn | 1.42 Bn |
| 9 | Honeywell International | 67.04 Bn | 19.48 Bn | 3.65 Bn | 6.40 Bn |
| 10 | VirTra | 32.03 Mn | -39.49 Mn | 3.42 Mn | 14.19 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.19 Mn |
| Mar 31, 2026 | 14.37 Mn |
| Dec 31, 2025 | 13.06 Mn |
| Sep 30, 2025 | 12.34 Mn |
| Jun 30, 2025 | 12.81 Mn |
| Mar 31, 2025 | 14.99 Mn |
| Dec 31, 2024 | 14.58 Mn |
| Sep 30, 2024 | 13.91 Mn |
| Jun 30, 2024 | 13.47 Mn |
| Mar 31, 2024 | 12.29 Mn |
| Dec 31, 2023 | 12.40 Mn |
| Sep 30, 2023 | 10.78 Mn |
| Jun 30, 2023 | 9.97 Mn |
| Mar 31, 2023 | 10.75 Mn |
| Dec 31, 2022 | 9.59 Mn |
| Sep 30, 2022 | 9.77 Mn |
| Jun 30, 2022 | 8.83 Mn |
| Mar 31, 2022 | 6.95 Mn |
| Dec 31, 2021 | 5.01 Mn |
| Sep 30, 2021 | 5.93 Mn |
API Access
VirTra 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=inventory&ticker=VTSI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "ticker": "VTSI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=inventory&ticker=VTSI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();