Everpure (P) Accumulated Expenses (2015 - 2026)
Everpure (P) reported Accumulated Expenses of $192.58 million for fiscal Q2 2027 (quarter ended Aug 2, 2026), up 22.9% from $156.72 million a year earlier and up 5.8% from the prior quarter.
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Analysis
Everpure (P) Accumulated Expenses (2015 - 2026) Analysis & Trends
At the end of FY2026 (ended Feb 1, 2026), Everpure posted Accumulated Expenses of $184.34 million, up 17.6% from FY2025.
- Accumulated Expenses has increased for 11 consecutive fiscal years, with a five-year compound annual growth rate of 24.4% (FY2021 to FY2026).
- By fiscal year, Accumulated Expenses came in at $156.79 million in FY2025 (+15.5%), $135.76 million in FY2024 (+9.7%), $123.75 million in FY2023 (+57.6%) and $78.51 million in FY2022 (+27.1%).
- The fiscal Q2 2027 figure ranks as the highest quarterly Accumulated Expenses in data going back to fiscal Q4 2015.
- Year over year, Accumulated Expenses has now increased in each of the last eight quarters, with growth averaging 17.4% over the last eight quarters.
- The high point for year-over-year Accumulated Expenses in five years was fiscal Q2 2023 (growth of 76.7%); the low point was fiscal Q2 2025 (a decline of 7.3%).
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at $181.94 million (Q1 2027), $184.34 million (Q4 2026) and $159.83 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Apple | 5,059.58 Bn | 4,807.07 Bn | 54.77 Bn |
| 2 | Cisco Systems | 451.20 Bn | 387.12 Bn | 11.06 Bn |
| 3 | Dell Technologies | 365.27 Bn | 321.03 Bn | 9.83 Bn |
| 4 | Arista Networks | 251.01 Bn | 204.46 Bn | 1.91 Bn |
| 5 | Sandisk | 211.16 Bn | 199.69 Bn | 7.58 Bn |
| 6 | Seagate Technology Holdings | 159.53 Bn | 154.52 Bn | 1.90 Bn |
| 7 | Sony | 145.60 Bn | 82.87 Bn | 6.53 Bn |
| 8 | Western Digital | 128.87 Bn | 117.00 Bn | 2.03 Bn |
| 9 | Hewlett Packard Enterprise | 91.88 Bn | 69.75 Bn | 4.93 Bn |
| 10 | Everpure | 50.56 Bn | 44.97 Bn | 811.39 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 192.58 Mn |
| May 3, 2026 | 181.94 Mn |
| Feb 1, 2026 | 184.34 Mn |
| Nov 2, 2025 | 159.83 Mn |
| Aug 3, 2025 | 156.72 Mn |
| May 4, 2025 | 157.73 Mn |
| Feb 2, 2025 | 156.79 Mn |
| Nov 3, 2024 | 141.85 Mn |
| Aug 4, 2024 | 119.43 Mn |
| May 5, 2024 | 127.89 Mn |
| Feb 4, 2024 | 135.76 Mn |
| Nov 5, 2023 | 141.24 Mn |
| Aug 6, 2023 | 128.84 Mn |
| May 7, 2023 | 121.23 Mn |
| Feb 5, 2023 | 123.75 Mn |
| Nov 6, 2022 | 108.97 Mn |
| Aug 7, 2022 | 93.75 Mn |
| May 8, 2022 | 84.29 Mn |
| Feb 6, 2022 | 78.51 Mn |
| Oct 31, 2021 | 73.88 Mn |
API Access
Everpure 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=P&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "P", "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=P&period=max&api_key=YOUR_API_KEY");
const data = await res.json();