Coda Octopus (CODA) Operating Expenses (2010 - 2026)
Coda Octopus (CODA) posted Operating Expenses of $3.52 million for fiscal Q3 2026 (quarter ended Jul 31, 2026), up 2.1% from $3.44 million a year earlier and up 26.3% from the prior quarter.
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Analysis
Coda Octopus (CODA) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jul 31, 2026, Operating Expenses at Coda Octopus was $13.17 million, up 4.2% year-over-year; for FY2025 (ended Oct 31, 2025), it came in at $13.13 million, up 24.0% from FY2024.
- Annual Operating Expenses has increased for three consecutive fiscal years, with a five-year compound annual growth rate of 5.7% (FY2020 to FY2025).
- In prior fiscal years, Coda Octopus' Operating Expenses was $10.59 million in FY2024 (+2.9%), $10.29 million in FY2023 (+1.0%), $10.19 million in FY2022 (-6.8%) and $10.93 million in FY2021 (+10.1%).
- The fiscal Q3 2026 figure stands as the highest quarterly Operating Expenses in data going back to fiscal Q1 2010.
- On a year-over-year basis, Operating Expenses increased in seven of the last eight quarters, with growth averaging 14.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q2 2025, with growth of 42.8%; the weakest was fiscal Q4 2022, with a decline of 28.1%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $2.79 million (Q2 2026), $3.36 million (Q1 2026) and $3.51 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 1.87 Bn |
| 10 | Coda Octopus | 121.04 Mn | -5.21 Mn | 5.05 Mn | 3.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 3.52 Mn |
| Apr 30, 2026 | 2.79 Mn |
| Jan 31, 2026 | 3.36 Mn |
| Oct 31, 2025 | 3.51 Mn |
| Jul 31, 2025 | 3.44 Mn |
| Apr 30, 2025 | 3.41 Mn |
| Jan 31, 2025 | 2.77 Mn |
| Oct 31, 2024 | 3.01 Mn |
| Jul 31, 2024 | 2.66 Mn |
| Apr 30, 2024 | 2.39 Mn |
| Jan 31, 2024 | 2.53 Mn |
| Oct 31, 2023 | 2.61 Mn |
| Jul 31, 2023 | 2.50 Mn |
| Apr 30, 2023 | 2.77 Mn |
| Jan 31, 2023 | 2.41 Mn |
| Oct 31, 2022 | 2.30 Mn |
| Jul 31, 2022 | 2.54 Mn |
| Apr 30, 2022 | 2.55 Mn |
| Jan 31, 2022 | 2.78 Mn |
| Oct 31, 2021 | 3.20 Mn |
API Access
Coda Octopus 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=CODA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CODA", "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=CODA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();