Jingbo Technology (SVMB) Operating Expenses (2015 - 2026)
Jingbo Technology's Operating Expenses came in at $687,207 for fiscal Q1 2027 (quarter ended May 31, 2026), up 33.4% from $515,071 a year earlier but down 84.3% from the prior quarter.
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Analysis
Jingbo Technology (SVMB) Operating Expenses (2015 - 2026) Analysis & Trends
Over the trailing twelve months to May 31, 2026, Jingbo Technology reported Operating Expenses of $6.64 million, up 43.3% year-over-year; for FY2026 (ended Feb 28, 2026), it came in at $6.47 million, up 27.1% from FY2025.
- Operating Expenses carries a five-year compound annual growth rate of 166.1% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $5.09 million in FY2025 (+11.4%), $4.57 million in FY2024, $6.28 million in FY2023 (+5.7%) and $5.94 million in FY2022.
- The five-year range for quarterly Operating Expenses is $5,784 (fiscal Q2 2022) to $4.37 million (fiscal Q4 2026).
- Year-over-year, Operating Expenses has increased for three consecutive quarters, with growth averaging 13.4% over the last five quarters.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q2 2024 (growth of 217.0%), and the weakest in fiscal Q1 2026 (a decline of 46.9%).
- Business Quant data shows SVMB's Operating Expenses at $4.37 million (Q4 2026), $744,672 (Q3 2026) and $836,388 (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Jingbo Technology | 555.32 Mn | 554.58 Mn | 89,520.00 | 687,207.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 687,207.00 |
| Feb 28, 2026 | 4.37 Mn |
| Nov 30, 2025 | 744,672.00 |
| Aug 31, 2025 | 836,388.00 |
| May 31, 2025 | 515,071.00 |
| Feb 28, 2025 | 2.04 Mn |
| Nov 30, 2024 | 708,609.00 |
| Aug 31, 2024 | 1.37 Mn |
| May 31, 2024 | 970,894.00 |
| Nov 30, 2023 | 1.09 Mn |
| Aug 31, 2023 | 906,297.00 |
| May 31, 2023 | 1.46 Mn |
| Feb 28, 2023 | 573,444.00 |
| Nov 30, 2022 | 1.09 Mn |
| Aug 31, 2022 | 1.79 Mn |
| May 31, 2022 | 1.67 Mn |
| Feb 28, 2022 | 1.34 Mn |
| Nov 30, 2021 | 5,784.00 |
| Aug 31, 2021 | 19,938.00 |
| May 31, 2021 | 25,226.00 |
API Access
Jingbo Technology 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=SVMB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SVMB", "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=SVMB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();