Zeo ScientifiX (ZEOX) Accumulated Expenses (2013 - 2022)
Zeo ScientifiX's Accumulated Expenses was $1.73 million in fiscal Q1 2022 (quarter ended Jan 31, 2022), up 23.3% from $1.4 million a year earlier and up 12.2% from the prior quarter.
Zeo ScientifiX (ZEOX) Accumulated Expenses (2013 - 2022) Analysis & Trends
At the end of FY2021 (ended Oct 31, 2021), Accumulated Expenses at Zeo ScientifiX came in at $1.54 million, up 33.4% from FY2020.
- Accumulated Expenses has now increased for three consecutive fiscal years, with a five-year compound annual growth rate of 32.5% (FY2016 to FY2021).
- In earlier fiscal years, Accumulated Expenses was $1.16 million in FY2020 (+83.0%), $631,809 in FY2019 (+92.8%), $327,662 in FY2018 (-85.0%) and $2.18 million in FY2017 (+477.5%).
- The fiscal Q1 2022 figure marks the highest quarterly Accumulated Expenses since fiscal Q1 2018.
- Compared with a year earlier, Accumulated Expenses has increased for 12 straight quarters, with growth averaging 47.2% over the last eight quarters.
- The best year-over-year quarter for Accumulated Expenses over five years was fiscal Q2 2019 (growth of 810.1%); the worst was fiscal Q2 2018 (a decline of 93.7%).
- Per Business Quant data, ZEOX's Accumulated Expenses in the three fiscal quarters before Q1 2022 was $1.54 million (Q4 2021), $1.33 million (Q3 2021) and $1.27 million (Q2 2021).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Eli Lilly | 1,082.65 Bn | 1,051.23 Bn | 19.71 Bn |
| 2 | Johnson & Johnson | 623.68 Bn | 542.21 Bn | 17.26 Bn |
| 3 | AbbVie | 459.43 Bn | 432.59 Bn | 12.70 Bn |
| 4 | Merck | 354.80 Bn | 309.23 Bn | 12.21 Bn |
| 5 | Novartis Ag | 269.16 Bn | 225.03 Bn | 11.24 Bn |
| 6 | Astrazeneca | 244.40 Bn | 217.97 Bn | 12.86 Bn |
| 7 | Amgen | 220.17 Bn | 175.57 Bn | 7.24 Bn |
| 8 | Gilead Sciences | 183.05 Bn | 157.16 Bn | 6.22 Bn |
| 9 | Pfizer | 160.27 Bn | 107.22 Bn | 10.94 Bn |
| 10 | Zeo ScientifiX | 9.34 Mn | 5.93 Mn | 2.06 Mn |
Historic Data
| Date | Value |
|---|---|
| Jan 31, 2022 | 1.73 Mn |
| Oct 31, 2021 | 1.54 Mn |
| Jul 31, 2021 | 1.33 Mn |
| Apr 30, 2021 | 1.27 Mn |
| Jan 31, 2021 | 1.40 Mn |
| Oct 31, 2020 | 1.16 Mn |
| Jul 31, 2020 | 1.12 Mn |
| Apr 30, 2020 | 949,035.00 |
| Jan 31, 2020 | 814,261.00 |
| Oct 31, 2019 | 631,809.00 |
| Jul 31, 2019 | 703,925.00 |
| Apr 30, 2019 | 618,602.00 |
| Jan 31, 2019 | 465,213.00 |
| Oct 31, 2018 | 327,662.00 |
| Jul 31, 2018 | 226,317.00 |
| Apr 30, 2018 | 67,973.00 |
| Jan 31, 2018 | 2.48 Mn |
| Oct 31, 2017 | 2.18 Mn |
| Jul 31, 2017 | 1.55 Mn |
| Apr 30, 2017 | 1.08 Mn |
Zeo ScientifiX 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=ZEOX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "ZEOX", "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=ZEOX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();