NovaBridge Biosciences (NBP) Return on Sales [ROS] (2019 - 2023)
NovaBridge Biosciences' Return on Sales [ROS] came in at -789260.00% for Q4 2023, down 785884.13 percentage points from the prior quarter.
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Analysis
NovaBridge Biosciences (NBP) Return on Sales [ROS] (2019 - 2023) Analysis & Trends
For FY2023, NovaBridge Biosciences' Return on Sales [ROS] was -31313.96%, down 12401.77 percentage points from FY2022.
- Return on Sales [ROS] has declined in each of the last three years, with a five-year change of -30498.35 percentage points (FY2018 to FY2023).
- Going back by year, Return on Sales [ROS] was -18912.18% in FY2022 (-16587.40 pp), -2324.79% in FY2021 (-2319.51 pp), -5.27% in FY2020 (+4878.23 pp) and -4883.50% in FY2019 (-4067.90 pp).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,076.25 Bn | 1,044.84 Bn | 19.71 Bn | 51.16% |
| 2 | Johnson & Johnson | 617.18 Bn | 535.70 Bn | 17.26 Bn | 28.21% |
| 3 | AbbVie | 464.58 Bn | 437.73 Bn | 12.70 Bn | 37.86% |
| 4 | Merck | 356.04 Bn | 310.47 Bn | 12.21 Bn | -3.52% |
| 5 | Novartis Ag | 269.07 Bn | 224.94 Bn | 11.24 Bn | 32.97% |
| 6 | Astrazeneca | 243.21 Bn | 216.77 Bn | 12.86 Bn | 20.57% |
| 7 | Amgen | 217.88 Bn | 173.28 Bn | 7.24 Bn | 34.95% |
| 8 | Gilead Sciences | 179.62 Bn | 153.74 Bn | 6.22 Bn | -133.21% |
| 9 | Pfizer | 158.45 Bn | 105.40 Bn | 10.94 Bn | 28.37% |
| 10 | NovaBridge Biosciences | 149.78 Mn | 149.78 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | -789,260.00% |
| Sep 30, 2023 | -3,375.87% |
| Jun 30, 2023 | -7,578.62% |
| Dec 31, 2020 | 60.24% |
| Sep 30, 2019 | -2,042.94% |
API Access
NovaBridge Biosciences Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=NBP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "NBP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=NBP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();