Eco Science Solutions (ESSI) Total Non-Current Liabilities (2012 - 2016)
Eco Science Solutions' Total Non-Current Liabilities was $52,245 in fiscal Q3 2017 (quarter ended Oct 31, 2016), down 81.4% from $281,215 a year earlier but up 3.7% from the prior quarter.
Eco Science Solutions (ESSI) Total Non-Current Liabilities (2012 - 2016) Analysis & Trends
At the end of FY2016 (ended Jan 31, 2016), Total Non-Current Liabilities at Eco Science Solutions came in at $46,710, down 80.2% from FY2015.
- Total Non-Current Liabilities has now declined for three consecutive fiscal years, with a three-year compound annual growth rate of -59.8% (FY2013 to FY2016).
- In earlier fiscal years, Total Non-Current Liabilities was $236,350 in FY2015 (-18.2%), $288,991 in FY2014 (-59.7%) and $717,824 in FY2013.
- Quarterly Total Non-Current Liabilities has moved between $45,097 (fiscal Q3 2013) and $717,824 (fiscal Q4 2013) over five years.
- Compared with a year earlier, Total Non-Current Liabilities has declined for four straight quarters, with growth averaging 56.0% over the last eight quarters.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was fiscal Q1 2016 (growth of 350.3%); the worst was fiscal Q1 2015 (a decline of 88.0%).
- Per Business Quant data, ESSI's Total Non-Current Liabilities in the three fiscal quarters before Q3 2017 was $50,400 (Q2 2017), $48,555 (Q1 2017) and $46,710 (Q4 2016).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 462.03 Bn | 430.98 Bn | 1.64 Bn | 1.78 Bn |
| 2 | Oracle | 387.48 Bn | 259.61 Bn | - | 188.55 Bn |
| 3 | Sap Se | 266.80 Bn | 194.59 Bn | 8.40 Bn | 12.14 Bn |
| 4 | Salesforce | 199.03 Bn | 154.91 Bn | 8.70 Bn | 67.55 Bn |
| 5 | ServiceNow | 154.48 Bn | 132.94 Bn | 2.82 Bn | 18.55 Bn |
| 6 | Automatic Data Processing | 117.71 Bn | 99.83 Bn | 2.51 Bn | 56.02 Bn |
| 7 | Intuit | 92.43 Bn | 71.78 Bn | 3.44 Bn | 17.43 Bn |
| 8 | Relx | 72.15 Bn | 71.24 Bn | - | 1.33 Mn |
| 9 | Thomson Reuters | 50.59 Bn | 47.38 Bn | - | 6.95 Bn |
| 10 | Eco Science Solutions | 3.34 Mn | 3.28 Mn | - | - |
Historic Data
| Date | Value |
|---|---|
| Oct 31, 2016 | 52,245.00 |
| Jul 31, 2016 | 50,400.00 |
| Apr 30, 2016 | 48,555.00 |
| Jan 31, 2016 | 46,710.00 |
| Oct 31, 2015 | 281,215.00 |
| Jul 31, 2015 | 236,350.00 |
| Apr 30, 2015 | 236,350.00 |
| Jan 31, 2015 | 236,350.00 |
| Oct 31, 2014 | 94,881.00 |
| Jul 31, 2014 | 69,569.00 |
| Apr 30, 2014 | 52,491.00 |
| Jan 31, 2014 | 288,991.00 |
| Oct 31, 2013 | 610,431.00 |
| Jul 31, 2013 | 516,046.00 |
| Apr 30, 2013 | 437,375.00 |
| Jan 31, 2013 | 717,824.00 |
| Oct 31, 2012 | 45,097.00 |
Eco Science Solutions Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=ESSI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "ESSI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=ESSI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();