Borqs Technologies (BRQSF) Operating Expenses (2015 - 2018)
Borqs Technologies' Operating Expenses was $17.89 million in FY2025, up 92.0% from $9.32 million in FY2024.
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Analysis
Borqs Technologies (BRQSF) Operating Expenses (2015 - 2018) Analysis & Trends
From FY2015 onward, Borqs Technologies has reported Operating Expenses for 11 years.
- Operating Expenses shows a five-year compound annual growth rate of -15.8% (FY2020 to FY2025).
- The FY2025 figure marks the highest annual Operating Expenses since FY2021.
- Per Business Quant data, Operating Expenses in earlier years was $9.32 million in FY2024 (-38.8%), $15.24 million in FY2023 (+66.8%), $9.14 million in FY2022 (-68.5%) and $29 million in FY2021 (-31.3%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 260.12 Bn | 245.19 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 232.49 Bn | 212.89 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 125.70 Bn | 111.63 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 110.19 Bn | 97.50 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 92.71 Bn | 74.35 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 34.07 Bn | 20.19 Bn | - | - |
| 7 | Okta | 33.06 Bn | 23.16 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 30.90 Bn | 25.43 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 28.04 Bn | 18.51 Bn | 569.77 Mn | 541.37 Mn |
| 10 | Borqs Technologies | 2.66 Mn | -19.19 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2018 | 45.07 Mn |
| Sep 30, 2018 | 4.72 Mn |
| Jun 30, 2018 | 5.38 Mn |
| Mar 31, 2018 | 5.67 Mn |
| Sep 30, 2017 | 19.20 Mn |
| Jun 30, 2017 | 5.43 Mn |
| Mar 31, 2017 | 3.35 Mn |
| Dec 31, 2016 | 327,749.00 |
| Sep 30, 2016 | 6.10 Mn |
| Mar 31, 2016 | 177,789.00 |
| Dec 31, 2015 | 62,232.00 |
| Sep 30, 2015 | 2,975.00 |
API Access
Borqs 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=BRQSF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BRQSF", "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=BRQSF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();