Byrna Technologies (BYRN) Operating Expenses (2011 - 2026)
Byrna Technologies' Operating Expenses was $15.08 million in fiscal Q3 2026 (quarter ended Aug 31, 2026), up 7.3% from $14.06 million a year earlier and up 3.1% from the prior quarter.
Byrna Technologies (BYRN) Operating Expenses (2011 - 2026) Analysis & Trends
On a trailing twelve-month basis, Byrna Technologies' Operating Expenses was $63.29 million through Aug 31, 2026, up 13.0% year-over-year; for FY2025 (ended Nov 30, 2025), it came in at $59.63 million, up 29.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 38.2% (FY2020 to FY2025).
- In earlier fiscal years, Operating Expenses was $46.1 million in FY2024 (+46.6%), $31.44 million in FY2023 (-7.6%), $34.01 million in FY2022 (+29.9%) and $26.18 million in FY2021 (+121.6%).
- Quarterly Operating Expenses has moved between $7.19 million (fiscal Q2 2023) and $17.11 million (fiscal Q4 2025) over five years.
- Compared with a year earlier, Operating Expenses has increased for 12 straight quarters, with growth averaging 22.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q3 2024 (growth of 67.7%); the worst was fiscal Q2 2023 (a decline of 17.7%).
- Per Business Quant data, BYRN's Operating Expenses in the three fiscal quarters before Q3 2026 was $14.63 million (Q2 2026), $16.47 million (Q1 2026) and $17.11 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amer Sports | 17.51 Bn | 15.10 Bn | 1.07 Bn | 909.20 Mn |
| 2 | Hasbro | 16.75 Bn | 11.71 Bn | 1.21 Bn | 1.08 Bn |
| 3 | Acushnet Holdings | 4.79 Bn | 4.52 Bn | 321.99 Mn | 236.71 Mn |
| 4 | Mattel | 4.43 Bn | 1.11 Bn | 542.12 Mn | - |
| 5 | YETI Holdings | 3.36 Bn | 2.82 Bn | 322.52 Mn | 229.01 Mn |
| 6 | Callaway Golf | 2.98 Bn | 868.19 Mn | 226.70 Mn | 182.00 Mn |
| 7 | Peloton Interactive | 2.49 Bn | -2.37 Bn | 342.60 Mn | 226.20 Mn |
| 8 | Sturm Ruger | 799.29 Mn | 382.73 Mn | 30.52 Mn | 24.54 Mn |
| 9 | Smith & Wesson Brands | 647.27 Mn | 559.52 Mn | 32.27 Mn | 28.05 Mn |
| 10 | Byrna Technologies | 87.79 Mn | 43.24 Mn | 12.15 Mn | 15.08 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 15.08 Mn |
| May 31, 2026 | 14.63 Mn |
| Feb 28, 2026 | 16.47 Mn |
| Nov 30, 2025 | 17.11 Mn |
| Aug 31, 2025 | 14.06 Mn |
| May 31, 2025 | 14.24 Mn |
| Feb 28, 2025 | 14.23 Mn |
| Nov 30, 2024 | 13.47 Mn |
| Aug 31, 2024 | 12.18 Mn |
| May 31, 2024 | 10.65 Mn |
| Feb 29, 2024 | 9.80 Mn |
| Nov 30, 2023 | 9.92 Mn |
| Aug 31, 2023 | 7.27 Mn |
| May 31, 2023 | 7.19 Mn |
| Feb 28, 2023 | 7.24 Mn |
| Nov 30, 2022 | 8.96 Mn |
| Aug 31, 2022 | 8.28 Mn |
| May 31, 2022 | 8.74 Mn |
| Feb 28, 2022 | 8.02 Mn |
| Nov 30, 2021 | 8.80 Mn |
Byrna Technologies Operating 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=operating-expenses&ticker=BYRN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BYRN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=BYRN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();