Harrow (HROW) Total Non-Current Liabilities (2014 - 2024)
Harrow (HROW) recorded Total Non-Current Liabilities of $291.21 million in Q3 2024, up 40.0% from $207.95 million a year earlier and up 18.5% from the prior quarter.
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Analysis
Harrow (HROW) Total Non-Current Liabilities (2014 - 2024) Analysis & Trends
At the end of FY2023, Harrow reported Total Non-Current Liabilities of $239.04 million.
- Annual Total Non-Current Liabilities has a five-year compound annual growth rate of 58.5% (FY2018 to FY2023).
- Across earlier years, Total Non-Current Liabilities came in at $29.85 million in FY2020 (-3.3%) and $30.87 million in FY2019 (+29.2%).
- The Q3 2024 figure is the highest quarterly Total Non-Current Liabilities in data going back to Q2 2014.
- On a year-over-year basis, Total Non-Current Liabilities has increased for three consecutive quarters.
- Peak year-over-year performance for Total Non-Current Liabilities in the last five years was growth of 40.0% in Q3 2024, against a decline of 11.2% in Q1 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $245.74 million (Q2 2024), $232.62 million (Q1 2024) and $239.04 million (Q4 2023).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 105.99 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 106.45 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 80.25 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 48.34 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -967.00 Mn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 81.11 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 36.04 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 100.86 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 5.92 Bn |
| 10 | Harrow | 1.18 Bn | 858.40 Mn | 50.36 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2024 | 291.21 Mn |
| Jun 30, 2024 | 245.74 Mn |
| Mar 31, 2024 | 232.62 Mn |
| Dec 31, 2023 | 239.04 Mn |
| Sep 30, 2023 | 207.95 Mn |
| Jun 30, 2023 | 199.66 Mn |
| Mar 31, 2023 | 193.70 Mn |
| Mar 31, 2021 | 27.58 Mn |
| Dec 31, 2020 | 29.85 Mn |
| Sep 30, 2020 | 33.74 Mn |
| Jun 30, 2020 | 33.26 Mn |
| Mar 31, 2020 | 31.07 Mn |
| Dec 31, 2019 | 30.87 Mn |
| Sep 30, 2019 | 30.17 Mn |
| Jun 30, 2019 | 29.36 Mn |
| Mar 31, 2019 | 28.68 Mn |
| Dec 31, 2018 | 23.90 Mn |
| Sep 30, 2018 | 23.04 Mn |
| Jun 30, 2018 | 21.80 Mn |
| Mar 31, 2018 | 20.32 Mn |
API Access
Harrow 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=HROW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "HROW", "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=HROW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();