Everspin Technologies (MRAM) Accumulated Expenses (2015 - 2026)
Everspin Technologies (MRAM) posted Accumulated Expenses of $9.31 million for Q3 2026, up 212.4% from $2.98 million a year earlier and up 39.9% from the prior quarter.
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Analysis
Everspin Technologies (MRAM) Accumulated Expenses (2015 - 2026) Analysis & Trends
At the end of FY2025, Everspin Technologies' Accumulated Expenses came in at $3.65 million, up 49.1% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 10.3% (FY2020 to FY2025).
- In prior years, Everspin Technologies' Accumulated Expenses was $2.45 million in FY2024 (-43.5%), $4.34 million in FY2023 (+22.7%), $3.53 million in FY2022 (-1.3%) and $3.58 million in FY2021 (+60.3%).
- The Q3 2026 figure stands as the highest quarterly Accumulated Expenses in data going back to Q4 2015.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last seven quarters, with growth averaging 72.3% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q3 2026, with growth of 212.4%; the weakest was Q4 2024, with a decline of 43.5%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $6.65 million (Q2 2026), $4.53 million (Q1 2026) and $3.65 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | SK hynix | 24,980.27 Bn | 24,964.04 Bn | 43.99 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,337.48 Bn | 9,919.73 Bn | 31.04 Bn |
| 3 | Nvidia | 3,939.34 Bn | 3,713.50 Bn | 72.14 Bn |
| 4 | Broadcom | 1,653.85 Bn | 1,579.89 Bn | 20.46 Bn |
| 5 | Micron Technology | 880.27 Bn | 785.91 Bn | 47.05 Bn |
| 6 | Advanced Micro Devices | 875.86 Bn | 824.07 Bn | 7.21 Bn |
| 7 | Asml Holding | 576.26 Bn | 531.95 Bn | 5.90 Bn |
| 8 | Intel | 316.79 Bn | 179.50 Bn | 7.10 Bn |
| 9 | Applied Materials | 294.03 Bn | 294.03 Bn | 5.25 Bn |
| 10 | Everspin Technologies | 299.12 Mn | 127.24 Mn | 10.61 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 9.31 Mn |
| Jun 30, 2026 | 6.65 Mn |
| Mar 31, 2026 | 4.53 Mn |
| Dec 31, 2025 | 3.65 Mn |
| Sep 30, 2025 | 2.98 Mn |
| Jun 30, 2025 | 2.25 Mn |
| Mar 31, 2025 | 2.56 Mn |
| Dec 31, 2024 | 2.45 Mn |
| Sep 30, 2024 | 2.14 Mn |
| Jun 30, 2024 | 1.76 Mn |
| Mar 31, 2024 | 2.12 Mn |
| Dec 31, 2023 | 4.34 Mn |
| Sep 30, 2023 | 3.48 Mn |
| Jun 30, 2023 | 2.83 Mn |
| Mar 31, 2023 | 2.08 Mn |
| Dec 31, 2022 | 3.53 Mn |
| Sep 30, 2022 | 2.44 Mn |
| Jun 30, 2022 | 2.17 Mn |
| Mar 31, 2022 | 1.57 Mn |
| Dec 31, 2021 | 3.58 Mn |
API Access
Everspin Technologies Accumulated 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=accumulated-expenses&ticker=MRAM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MRAM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=MRAM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();