Tat Technologies (TATT) EV to EBITDA (2015 - 2026)
Tat Technologies' EV to EBITDA was 23.47 in the quarter ended Jun 30, 2026, up 72.3% from 13.62 a year earlier and up 13.4% from the prior quarter.
Tat Technologies (TATT) EV to EBITDA (2015 - 2026) Analysis & Trends
On a trailing twelve-month basis, Tat Technologies' EV to EBITDA was 16.65 through Jun 30, 2026, up 36.7% year-over-year; for the year ended Dec 31, 2025, it came in at 21.90, up 45.1% from the prior year.
- In earlier years, EV to EBITDA was 15.09 in the year ended Dec 31, 2024 (+95.0%), 7.74 in the year ended Dec 31, 2023 (-53.8%), 16.75 in the year ended Dec 31, 2022 (-54.3%) and 36.64 in the year ended Dec 31, 2021 (-95.4%).
- The figure for the quarter ended Jun 30, 2026 marks the highest quarterly EV to EBITDA since the quarter ended Sep 30, 2022.
- Compared with a year earlier, EV to EBITDA has increased for nine straight quarters, with growth averaging 61.0% over the last eight quarters.
- The best year-over-year quarter for EV to EBITDA over five years was the quarter ended Dec 31, 2024 (growth of 95.1%); the worst was the quarter ended Sep 30, 2023 (a decline of 90.3%).
- Per Business Quant data, TATT's EV to EBITDA in the three quarters before the quarter ended Jun 30, 2026 was 20.71 (quarter ended Mar 31, 2026), 21.90 (quarter ended Dec 31, 2025) and 18.80 (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | General Electric | 330.06 Bn | 284.06 Bn | 4.68 Bn |
| 2 | Rtx | 252.10 Bn | 225.31 Bn | 5.13 Bn |
| 3 | Boeing | 148.40 Bn | 55.10 Bn | 2.41 Bn |
| 4 | Lockheed Martin | 118.20 Bn | 104.92 Bn | 2.45 Bn |
| 5 | Howmet Aerospace | 92.39 Bn | 87.99 Bn | 951.00 Mn |
| 6 | General Dynamics | 89.92 Bn | 77.03 Bn | 2.18 Bn |
| 7 | Motorola Solutions | 73.84 Bn | 70.20 Bn | 1.68 Bn |
| 8 | Northrop Grumman | 71.73 Bn | 60.97 Bn | 2.12 Bn |
| 9 | Honeywell International | 66.60 Bn | 19.04 Bn | 3.65 Bn |
| 10 | Tat Technologies | 459.86 Mn | 235.03 Mn | 13.32 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 23.47 |
| Mar 31, 2026 | 20.71 |
| Dec 31, 2025 | 21.90 |
| Sep 30, 2025 | 18.80 |
| Jun 30, 2025 | 13.62 |
| Mar 31, 2025 | 14.69 |
| Dec 31, 2024 | 15.09 |
| Sep 30, 2024 | 10.70 |
| Jun 30, 2024 | 9.88 |
| Mar 31, 2024 | 8.94 |
| Dec 31, 2023 | 7.73 |
| Sep 30, 2023 | 6.83 |
| Jun 30, 2023 | 7.78 |
| Mar 31, 2023 | 9.86 |
| Dec 31, 2022 | 16.77 |
| Sep 30, 2022 | 70.28 |
| Jun 30, 2022 | 38.96 |
| Dec 31, 2021 | 36.73 |
| Dec 31, 2020 | 193.94 |
| Sep 30, 2020 | 5.09 |
Tat Technologies EV to EBITDA 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=ev-to-ebitda&ticker=TATT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "TATT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=TATT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();