Everpure (P) Operating Leases (2019 - 2026)
Everpure (P) reported Operating Leases of $175.03 million for fiscal Q2 2027 (quarter ended Aug 2, 2026), down 0.7% from $176.25 million a year earlier and down 5.7% from the prior quarter.
Everpure (P) Operating Leases (2019 - 2026) Analysis & Trends
At the end of FY2026 (ended Feb 1, 2026), Everpure posted Operating Leases of $172.06 million, up 25.3% from FY2025.
- Operating Leases has a five-year compound annual growth rate of 7.4% (FY2021 to FY2026).
- By fiscal year, Operating Leases came in at $137.28 million in FY2025 (+11.4%), $123.2 million in FY2024 (-13.5%), $142.47 million in FY2023 (+52.4%) and $93.48 million in FY2022 (-22.3%).
- Five-year quarterly Operating Leases spans a low of $91.64 million in fiscal Q1 2023 and a high of $185.6 million in fiscal Q1 2027.
- Year over year, Operating Leases gained in seven of the last eight quarters, with growth averaging 20.9%.
- The high point for year-over-year Operating Leases in five years was fiscal Q4 2023 (growth of 52.4%); the low point was fiscal Q4 2022 (a decline of 22.3%).
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at $185.6 million (Q1 2027), $172.06 million (Q4 2026) and $181.95 million (Q3 2026).
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
| Date | Value |
|---|---|
| Aug 2, 2026 | 175.03 Mn |
| May 3, 2026 | 185.60 Mn |
| Feb 1, 2026 | 172.06 Mn |
| Nov 2, 2025 | 181.95 Mn |
| Aug 3, 2025 | 176.25 Mn |
| May 4, 2025 | 129.74 Mn |
| Feb 2, 2025 | 137.28 Mn |
| Nov 3, 2024 | 146.39 Mn |
| Aug 4, 2024 | 128.67 Mn |
| May 5, 2024 | 120.71 Mn |
| Feb 4, 2024 | 123.20 Mn |
| Nov 5, 2023 | 122.39 Mn |
| Aug 6, 2023 | 132.19 Mn |
| May 7, 2023 | 139.67 Mn |
| Feb 5, 2023 | 142.47 Mn |
| Nov 6, 2022 | 147.11 Mn |
| Aug 7, 2022 | 150.71 Mn |
| May 8, 2022 | 91.64 Mn |
| Feb 6, 2022 | 93.48 Mn |
| Oct 31, 2021 | 99.03 Mn |
Everpure Operating Leases 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-leases&ticker=P&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "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=operating-leases&ticker=P&period=max&api_key=YOUR_API_KEY");
const data = await res.json();