Siga Technologies (SIGA) Operating Expenses (2010 - 2025)
Siga Technologies' Operating Expenses was $12.84 million in Q3 2025, up 35.6% from $9.47 million a year earlier but down 63.8% from the prior quarter.
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Analysis
Siga Technologies (SIGA) Operating Expenses (2010 - 2025) Analysis & Trends
On a trailing twelve-month basis, Siga Technologies' Operating Expenses was $81.96 million through Sep 30, 2025, up 18.5% year-over-year; for FY2024, it was $68.74 million, up 22.1% from FY2023.
- Operating Expenses shows a five-year compound annual growth rate of 18.8% (FY2019 to FY2024).
- In earlier years, Operating Expenses was $56.3 million in FY2023 (-17.3%), $68.08 million in FY2022 (+52.7%), $44.58 million in FY2021 (+10.2%) and $40.46 million in FY2020 (+39.2%).
- Quarterly Operating Expenses has moved between $6.8 million (Q1 2021) and $35.44 million (Q2 2025) over five years.
- Compared with a year earlier, Operating Expenses was higher in five of the last eight quarters, with growth averaging 35.2%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2022 (growth of 276.6%); the worst was Q3 2023 (a decline of 64.1%).
- Per Business Quant data, SIGA's Operating Expenses in the three quarters before Q3 2025 was $35.44 million (Q2 2025), $9.3 million (Q1 2025) and $24.38 million (Q4 2024).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 2.09 Bn |
| 10 | Siga Technologies | 247.78 Mn | -423.88 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2025 | 12.84 Mn |
| Jun 30, 2025 | 35.44 Mn |
| Mar 31, 2025 | 9.30 Mn |
| Dec 31, 2024 | 24.38 Mn |
| Sep 30, 2024 | 9.47 Mn |
| Jun 30, 2024 | 20.73 Mn |
| Mar 31, 2024 | 14.15 Mn |
| Dec 31, 2023 | 24.80 Mn |
| Sep 30, 2023 | 10.54 Mn |
| Jun 30, 2023 | 10.52 Mn |
| Mar 31, 2023 | 10.43 Mn |
| Dec 31, 2022 | 13.16 Mn |
| Sep 30, 2022 | 29.34 Mn |
| Jun 30, 2022 | 13.60 Mn |
| Mar 31, 2022 | 11.98 Mn |
| Dec 31, 2021 | 21.33 Mn |
| Sep 30, 2021 | 7.79 Mn |
| Jun 30, 2021 | 8.65 Mn |
| Mar 31, 2021 | 6.80 Mn |
| Dec 31, 2020 | 10.93 Mn |
API Access
Siga Technologies Operating 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=operating-expenses&ticker=SIGA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SIGA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SIGA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();