Macrogenics (MGNX) Cash & Equivalents (2012 - 2026)
Macrogenics (MGNX) reported Cash & Equivalents of $113.91 million for Q2 2026, down 12.8% from $130.69 million a year earlier but up 71.2% from the prior quarter.
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Analysis
Macrogenics (MGNX) Cash & Equivalents (2012 - 2026) Analysis & Trends
At the end of FY2025, Macrogenics posted Cash & Equivalents of $57.22 million, down 68.7% from FY2024.
- Cash & Equivalents has a five-year compound annual growth rate of -20.6% (FY2020 to FY2025).
- By year, Cash & Equivalents came in at $182.84 million in FY2024 (+81.1%), $100.96 million in FY2023 (-7.3%), $108.88 million in FY2022 (-11.8%) and $123.47 million in FY2021 (-31.8%).
- Five-year quarterly Cash & Equivalents spans a low of $21.47 million in Q2 2022 and a high of $224.26 million in Q1 2023.
- Year over year, Cash & Equivalents has now declined in each of the last four quarters, with growth averaging 15.8% over the last eight quarters.
- The high point for year-over-year Cash & Equivalents in five years was Q2 2023 (growth of 406.6%); the low point was Q2 2022 (a decline of 88.6%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $66.52 million (Q1 2026), $57.22 million (Q4 2025) and $80.13 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,261.99 Bn | 1,235.61 Bn | 20.46 Bn | 4.89 Bn |
| 2 | Johnson & Johnson | 678.93 Bn | 598.79 Bn | 17.30 Bn | 16.91 Bn |
| 3 | AbbVie | 518.29 Bn | 486.30 Bn | 13.12 Bn | 10.77 Bn |
| 4 | Merck | 365.98 Bn | 328.92 Bn | 13.19 Bn | 9.55 Bn |
| 5 | Novartis Ag | 316.85 Bn | 290.09 Bn | - | 400.00 Mn |
| 6 | Astrazeneca | 293.40 Bn | 267.29 Bn | 13.26 Bn | 7.94 Bn |
| 7 | Amgen | 251.78 Bn | 203.43 Bn | 7.58 Bn | 13.19 Bn |
| 8 | Gilead Sciences | 210.61 Bn | 185.71 Bn | 6.73 Bn | 6.44 Bn |
| 9 | Pfizer | 166.87 Bn | 114.23 Bn | 12.56 Bn | 1.82 Bn |
| 10 | Macrogenics | 150.40 Mn | -167.37 Mn | - | 113.91 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 113.91 Mn |
| Mar 31, 2026 | 66.52 Mn |
| Dec 31, 2025 | 57.22 Mn |
| Sep 30, 2025 | 80.13 Mn |
| Jun 30, 2025 | 130.69 Mn |
| Mar 31, 2025 | 145.57 Mn |
| Dec 31, 2024 | 182.84 Mn |
| Sep 30, 2024 | 179.63 Mn |
| Jun 30, 2024 | 83.93 Mn |
| Mar 31, 2024 | 80.36 Mn |
| Dec 31, 2023 | 100.96 Mn |
| Sep 30, 2023 | 89.90 Mn |
| Jun 30, 2023 | 108.76 Mn |
| Mar 31, 2023 | 224.26 Mn |
| Dec 31, 2022 | 108.88 Mn |
| Sep 30, 2022 | 83.99 Mn |
| Jun 30, 2022 | 21.47 Mn |
| Mar 31, 2022 | 47.33 Mn |
| Dec 31, 2021 | 123.47 Mn |
| Sep 30, 2021 | 190.53 Mn |
API Access
Macrogenics Cash & Equivalents 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=cash-and-equivalents&ticker=MGNX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "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=cash-and-equivalents&ticker=MGNX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();