Macrogenics (MGNX) Total Liabilities (2012 - 2026)
Macrogenics' Total Liabilities was $302.54 million in Q2 2026, up 52.2% from $198.8 million a year earlier and up 53.8% from the prior quarter.
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Analysis
Macrogenics (MGNX) Total Liabilities (2012 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Macrogenics came in at $201.26 million, up 38.2% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 19.4% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $145.6 million in FY2024 (-0.1%), $145.81 million in FY2023 (+5.3%), $138.46 million in FY2022 (+44.8%) and $95.63 million in FY2021 (+15.4%).
- The Q2 2026 figure marks the highest quarterly Total Liabilities in data going back to Q4 2012.
- Compared with a year earlier, Total Liabilities has increased for six straight quarters, with growth averaging 25.8% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q1 2023 (growth of 151.2%); the worst was Q1 2024 (a decline of 39.3%).
- Per Business Quant data, MGNX's Total Liabilities in the three quarters before Q2 2026 was $196.68 million (Q1 2026), $201.26 million (Q4 2025) and $203.76 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 116.09 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 141.05 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 87.82 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | 80.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | 65.46 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 83.95 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 37.53 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 115.64 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 7.18 Bn |
| 10 | Macrogenics | 258.40 Mn | -59.37 Mn | - | 302.54 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 302.54 Mn |
| Mar 31, 2026 | 196.68 Mn |
| Dec 31, 2025 | 201.26 Mn |
| Sep 30, 2025 | 203.76 Mn |
| Jun 30, 2025 | 198.80 Mn |
| Mar 31, 2025 | 145.45 Mn |
| Dec 31, 2024 | 145.60 Mn |
| Sep 30, 2024 | 144.43 Mn |
| Jun 30, 2024 | 143.32 Mn |
| Mar 31, 2024 | 142.13 Mn |
| Dec 31, 2023 | 145.81 Mn |
| Sep 30, 2023 | 145.99 Mn |
| Jun 30, 2023 | 134.11 Mn |
| Mar 31, 2023 | 234.23 Mn |
| Dec 31, 2022 | 138.46 Mn |
| Sep 30, 2022 | 72.39 Mn |
| Jun 30, 2022 | 75.56 Mn |
| Mar 31, 2022 | 93.23 Mn |
| Dec 31, 2021 | 95.63 Mn |
| Sep 30, 2021 | 100.72 Mn |
API Access
Macrogenics Total 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-liabilities&ticker=MGNX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "MGNX", "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-liabilities&ticker=MGNX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();