SciSparc (SPRC) Non Operating Interest Expenses (2016 - 2018)
SciSparc (SPRC) reported Non Operating Interest Expenses of $8.2 million for FY2025, compared with $353,000 in FY2024.
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Analysis
SciSparc (SPRC) Non Operating Interest Expenses (2016 - 2018) Analysis & Trends
Dating back to FY2015, SciSparc's Non Operating Interest Expenses record includes 11 years.
- Non Operating Interest Expenses has a five-year compound annual growth rate of 56.5% (FY2020 to FY2025).
- The FY2025 figure ranks as the highest annual Non Operating Interest Expenses in data going back to FY2015.
- According to Business Quant data, Non Operating Interest Expenses came in at $353,000 in FY2024 (-66.5%), $1.06 million in FY2023 (-47.6%), $2.01 million in FY2022 and $21,000 in FY2021 (-97.6%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,348.13 Bn | 1,321.74 Bn | 20.46 Bn | - |
| 2 | Johnson & Johnson | 675.90 Bn | 595.76 Bn | 17.30 Bn | 217.00 Mn |
| 3 | AbbVie | 519.45 Bn | 487.50 Bn | 13.12 Bn | - |
| 4 | Merck | 364.95 Bn | 327.95 Bn | 13.19 Bn | - |
| 5 | Novartis Ag | 311.58 Bn | 285.16 Bn | - | - |
| 6 | Astrazeneca | 289.34 Bn | 262.94 Bn | 13.26 Bn | -477.00 Mn |
| 7 | Amgen | 251.64 Bn | 203.30 Bn | 7.58 Bn | 653.00 Mn |
| 8 | Gilead Sciences | 212.05 Bn | 187.07 Bn | 6.73 Bn | 269.00 Mn |
| 9 | Pfizer | 167.35 Bn | 115.00 Bn | 12.56 Bn | - |
| 10 | SciSparc | 138,868.72 | -6.97 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2018 | 116,000.00 |
| Sep 30, 2018 | 11,000.00 |
| Jun 30, 2018 | 1,000.00 |
| Mar 31, 2018 | 2,000.00 |
| Dec 31, 2017 | 142,000.00 |
| Sep 30, 2017 | -79,000.00 |
| Jun 30, 2017 | 437,000.00 |
| Dec 31, 2016 | -8,000.00 |
| Sep 30, 2016 | 10,000.00 |
API Access
SciSparc Non Operating Interest 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=non-operating-interest-expenses&ticker=SPRC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "SPRC", "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-operating-interest-expenses&ticker=SPRC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();