Open Text (OTEX) Non-Current Debt (2009 - 2026)
Open Text's Non-Current Debt was $600 million in fiscal Q4 2016 (quarter ended Jun 30, 2016).
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Analysis
Open Text (OTEX) Non-Current Debt (2009 - 2026) Analysis & Trends
- Non-Current Debt shows a four-year compound annual growth rate of -1.9% (FY2012 to FY2016).
- In earlier fiscal years, Non-Current Debt was $800 million in FY2015 (unchanged), $800 million in FY2014 and $648.5 million in FY2012.
- The fiscal Q4 2016 figure marks the highest quarterly Non-Current Debt since fiscal Q2 2012.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non-Current Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Adobe | 97.58 Bn | 72.83 Bn | 6.00 Bn | -250.00 Mn |
| 2 | Atlassian | 55.96 Bn | 49.24 Bn | 1.53 Bn | 989.56 Mn |
| 3 | Autodesk | 50.57 Bn | 38.61 Bn | 1.87 Bn | 1.99 Bn |
| 4 | Twilio | 39.35 Bn | 29.42 Bn | 725.87 Mn | -64,000.00 |
| 5 | Zoom Communications | 28.55 Bn | -2.24 Bn | 985.50 Mn | - |
| 6 | Figma | 11.38 Bn | 4.89 Bn | 309.61 Mn | - |
| 7 | Dropbox | 8.07 Bn | 3.71 Bn | 506.50 Mn | 2.58 Bn |
| 8 | Nice | 7.10 Bn | 5.56 Bn | 995.81 Mn | - |
| 9 | RingCentral | 6.67 Bn | 6.16 Bn | 472.31 Mn | 1.07 Bn |
| 10 | Open Text | 6.41 Bn | 1.84 Bn | 1.01 Bn | 5.73 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.73 Bn |
| Mar 31, 2026 | 6.17 Bn |
| Dec 31, 2025 | 6.34 Bn |
| Sep 30, 2025 | 6.34 Bn |
| Jun 30, 2025 | 6.34 Bn |
| Mar 31, 2025 | 6.35 Bn |
| Dec 31, 2024 | 6.35 Bn |
| Sep 30, 2024 | 6.35 Bn |
| Jun 30, 2024 | 6.36 Bn |
| Mar 31, 2024 | 8.31 Bn |
| Dec 31, 2023 | 8.47 Bn |
| Sep 30, 2023 | 8.55 Bn |
| Jun 30, 2023 | 8.56 Bn |
| Mar 31, 2023 | 8.57 Bn |
| Dec 31, 2022 | 5.19 Bn |
| Sep 30, 2022 | 4.21 Bn |
| Jun 30, 2022 | 4.21 Bn |
| Mar 31, 2022 | 4.21 Bn |
| Dec 31, 2021 | 4.21 Bn |
| Sep 30, 2021 | 3.58 Bn |
API Access
Open Text Non-Current Debt 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=non-current-debt&ticker=OTEX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-debt", "ticker": "OTEX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-current-debt&ticker=OTEX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();