Coffee Holding (JVA) Operating Expenses (2010 - 2026)
Coffee Holding's Operating Expenses was $3.1 million in fiscal Q3 2026 (quarter ended Jul 31, 2026), down 7.5% from $3.35 million a year earlier and down 1.4% from the prior quarter.
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Analysis
Coffee Holding (JVA) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Coffee Holding's Operating Expenses was $14.45 million through Jul 31, 2026, up 6.5% year-over-year; for FY2025 (ended Oct 31, 2025), it came in at $13.26 million, up 1.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of -0.9% (FY2020 to FY2025).
- In earlier fiscal years, Operating Expenses was $13.08 million in FY2024 (+6.4%), $12.29 million in FY2023 (-24.8%) and $16.35 million in FY2022.
- The fiscal Q3 2026 figure marks the lowest quarterly Operating Expenses since fiscal Q2 2025.
- Compared with a year earlier, Operating Expenses was higher in six of the last eight quarters, with growth averaging 6.8%.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q1 2025 (growth of 44.6%); the worst was fiscal Q4 2023 (a decline of 51.3%).
- Per Business Quant data, JVA's Operating Expenses in the three fiscal quarters before Q3 2026 was $3.14 million (Q2 2026), $4.65 million (Q1 2026) and $3.56 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Coca Cola | 401.84 Bn | 388.31 Bn | 8.42 Bn | 3.72 Bn |
| 2 | Coca Cola Femsa Sab De Cv | 198.29 Bn | 198.29 Bn | 2.06 Bn | 1.49 Bn |
| 3 | Pepsico | 182.79 Bn | 140.55 Bn | 13.75 Bn | 9.49 Bn |
| 4 | Monster Beverage | 92.06 Bn | 80.31 Bn | 1.42 Bn | 679.19 Mn |
| 5 | Diageo | 51.95 Bn | 32.02 Bn | - | - |
| 6 | Ambev | 51.85 Bn | 37.14 Bn | 2.06 Bn | -263.15 Mn |
| 7 | Coca-Cola Europacific Partners | 51.70 Bn | 44.37 Bn | - | -1.63 Bn |
| 8 | Keurig Dr Pepper | 47.08 Bn | 43.13 Bn | 3.07 Bn | 2.40 Bn |
| 9 | Constellation Brands | 22.57 Bn | 22.12 Bn | 1.39 Bn | 538.20 Mn |
| 10 | Coffee Holding | 27.12 Mn | 18.43 Mn | 5.42 Mn | 3.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 3.10 Mn |
| Apr 30, 2026 | 3.14 Mn |
| Jan 31, 2026 | 4.65 Mn |
| Oct 31, 2025 | 3.56 Mn |
| Jul 31, 2025 | 3.35 Mn |
| Apr 30, 2025 | 2.84 Mn |
| Jan 31, 2025 | 4.14 Mn |
| Oct 31, 2024 | 3.24 Mn |
| Jul 31, 2024 | 3.21 Mn |
| Apr 30, 2024 | 3.77 Mn |
| Jan 31, 2024 | 2.86 Mn |
| Oct 31, 2023 | 3.10 Mn |
| Jul 31, 2023 | 2.85 Mn |
| Apr 30, 2023 | 3.22 Mn |
| Jan 31, 2023 | 3.12 Mn |
| Oct 31, 2022 | 6.37 Mn |
| Jul 31, 2022 | 2.91 Mn |
| Apr 30, 2022 | 3.37 Mn |
| Jan 31, 2022 | 3.72 Mn |
| Oct 31, 2021 | 4.71 Mn |
API Access
Coffee Holding 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=JVA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "JVA", "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=JVA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();