Borealis Foods (BRLS) Accumulated Expenses (2021 - 2023)
Borealis Foods (BRLS) reported Accumulated Expenses of $3.43 million for Q4 2023, up 307.4% from $842,513 a year earlier and up 27.3% from the prior quarter.
Powered by 
Analysis
Borealis Foods (BRLS) Accumulated Expenses (2021 - 2023) Analysis & Trends
Dating back to Q4 2021, Borealis Foods' Accumulated Expenses record includes 9 quarters.
- By year, Accumulated Expenses came in at $842,513 in FY2022 (+258.4%) and $235,051 in FY2021.
- The Q4 2023 figure ranks as the highest quarterly Accumulated Expenses in data going back to Q4 2021.
- Year over year, Accumulated Expenses has now increased in each of the last five quarters, with growth averaging 220.9% over the last five quarters.
- Per Business Quant data, the three quarters before Q4 2023 came in at $2.7 million (Q3 2023), $2.1 million (Q2 2023) and $2.12 million (Q1 2023).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Unilever | 132.43 Bn | 107.80 Bn | - |
| 2 | Mondelez International | 73.80 Bn | 67.12 Bn | 3.99 Bn |
| 3 | Hershey | 31.86 Bn | 28.11 Bn | 1.26 Bn |
| 4 | Kraft Heinz | 26.96 Bn | 13.49 Bn | 2.03 Bn |
| 5 | General Mills | 17.20 Bn | 14.85 Bn | 1.49 Bn |
| 6 | J M Smucker | 12.70 Bn | 12.49 Bn | 979.60 Mn |
| 7 | Mccormick | 12.49 Bn | 12.36 Bn | 778.20 Mn |
| 8 | Hormel Foods | 10.97 Bn | 7.66 Bn | 471.52 Mn |
| 9 | Chewy | 7.31 Bn | 4.59 Bn | 1.01 Bn |
| 10 | Borealis Foods | 29.62 Mn | 28.72 Mn | 838,891.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | 3.43 Mn |
| Sep 30, 2023 | 2.70 Mn |
| Jun 30, 2023 | 2.10 Mn |
| Mar 31, 2023 | 2.12 Mn |
| Dec 31, 2022 | 842,513.00 |
| Sep 30, 2022 | 1.51 Mn |
| Jun 30, 2022 | 779,911.00 |
| Mar 31, 2022 | 541,152.00 |
| Dec 31, 2021 | 235,051.00 |
API Access
Borealis Foods Accumulated 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=accumulated-expenses&ticker=BRLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "BRLS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=BRLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();