Oracle (ORCL) Short term Debt (2009 - 2019)
Oracle's (ORCL) quarterly Short term Debt came in at $4.5 billion in Q2 2019, little changed year-over-year from $4.5 billion in Q2 2018, and little changed on a QoQ basis from $4.5 billion in Q1 2019.
Oracle (ORCL) Short term Debt (2009 - 2019) Analysis & Trends
Oracle (ORCL) has 11 years of Short term Debt data on file, last reported at $4.5 billion in Q2 2019.
- On a quarterly basis, Short term Debt changed 0.07% year-over-year to $4.5 billion in Q2 2019; TTM through May 2019 was $4.5 billion, a 0.07% change from a year earlier, with the FY2019 full-year figure at $4.5 billion, changed 0.07% from the prior year.
- Short term Debt for Q2 2019 stood at $4.5 billion, roughly flat from $4.5 billion in the prior quarter.
- Across five years, Short term Debt topped out at $9.8 billion in Q2 2017 and bottomed at $999.0 million in Q3 2016.
- Historically, Short term Debt has averaged $3.9 billion across 5 years, with a median of $3.8 billion in 2016.
- The widest annual swing landed in 2017, when Short term Debt jumped 400.3%; it then plunged 54.16% in 2018.
- Year by year, Short term Debt stood at $2.0 billion in 2015, then surged by 91.9% to $3.8 billion in 2016, then slumped by 34.89% to $2.5 billion in 2017, then jumped by 159.18% to $6.5 billion in 2018, then plunged by 30.62% to $4.5 billion in 2019.
- Per Business Quant data, the three most recent Short term Debt figures were $4.5 billion in Q2 2019, $4.5 billion in Q1 2019, and $6.5 billion in Q4 2018.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 460.85 Bn | 451.55 Bn | 1.64 Bn |
| 2 | Oracle | 437.09 Bn | 400.44 Bn | - |
| 3 | Sap Se | 258.74 Bn | 237.66 Bn | 8.40 Bn |
| 4 | Salesforce | 195.52 Bn | 184.12 Bn | 8.70 Bn |
| 5 | ServiceNow | 145.61 Bn | 140.94 Bn | 2.82 Bn |
| 6 | Automatic Data Processing | 104.89 Bn | 100.66 Bn | 2.51 Bn |
| 7 | Intuit | 76.97 Bn | 69.77 Bn | 3.46 Bn |
| 8 | Relx | 60.41 Bn | 60.04 Bn | - |
| 9 | Strategy | 57.09 Bn | 54.64 Bn | 81.55 Mn |
| 10 | Workday | 46.40 Bn | 42.99 Bn | 2.21 Bn |
Historic Data
| Date | Value |
|---|---|
| May 31, 2019 | 4.49 Bn |
| Feb 28, 2019 | 4.49 Bn |
| Nov 30, 2018 | 6.48 Bn |
| Aug 31, 2018 | 3.74 Bn |
| May 31, 2018 | 4.49 Bn |
| Feb 28, 2018 | 4.49 Bn |
| Nov 30, 2017 | 2.50 Bn |
| Aug 31, 2017 | 5.00 Bn |
| May 31, 2017 | 9.80 Bn |
| Feb 28, 2017 | 3.50 Bn |
| Nov 30, 2016 | 3.84 Bn |
| Aug 31, 2016 | 999.00 Mn |
| May 31, 2016 | 3.75 Bn |
| Nov 30, 2015 | 2.00 Bn |
| Aug 31, 2015 | 2.00 Bn |
| May 31, 2015 | 2.00 Bn |
| Feb 28, 2015 | 2.00 Bn |
| May 31, 2014 | 1.51 Bn |
| Feb 28, 2014 | 1.52 Bn |
| Nov 30, 2013 | 1.53 Bn |
Oracle Short term 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=short-term-debt&ticker=ORCL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "short-term-debt", "ticker": "ORCL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=short-term-debt&ticker=ORCL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();