MicroAlgo (MLGO) Accumulated Expenses (2019 - 2021)
MicroAlgo's Accumulated Expenses came in at $1.08 million for Q2 2026, down 4.8% from $1.14 million a year earlier.
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Analysis
MicroAlgo (MLGO) Accumulated Expenses (2019 - 2021) Analysis & Trends
At the end of FY2025, MicroAlgo's Accumulated Expenses was $1.19 million, up 4.8% from FY2024.
- Accumulated Expenses carries a five-year compound annual growth rate of 97.1% (FY2020 to FY2025).
- Going back by year, Accumulated Expenses was $1.13 million in FY2024 (-38.8%), $1.85 million in FY2023 (+4.1%) and $1.78 million in FY2022.
- The Q2 2026 figure represents the lowest quarterly Accumulated Expenses since Q3 2021.
- Year-over-year, Accumulated Expenses increased in 1 of the last four quarters, with an average decline of 19.3%.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | SK hynix | 24,576.54 Bn | 24,560.31 Bn | 43.99 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,284.32 Bn | 9,899.31 Bn | 27.22 Bn |
| 3 | Nvidia | 4,083.27 Bn | 3,857.43 Bn | 72.14 Bn |
| 4 | Broadcom | 1,582.22 Bn | 1,508.26 Bn | 20.46 Bn |
| 5 | Advanced Micro Devices | 844.94 Bn | 793.16 Bn | 7.21 Bn |
| 6 | Micron Technology | 820.10 Bn | 725.74 Bn | 47.05 Bn |
| 7 | Asml Holding | 581.15 Bn | 536.84 Bn | 5.90 Bn |
| 8 | Intel | 308.67 Bn | 171.38 Bn | 7.10 Bn |
| 9 | Applied Materials | 295.64 Bn | 261.08 Bn | 4.59 Bn |
| 10 | MicroAlgo | 27.11 Mn | -1.10 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2021 | 76,058.00 |
| Jun 30, 2021 | 31,058.00 |
| Mar 31, 2021 | 17,136.00 |
| Dec 31, 2020 | 39,972.00 |
| Dec 31, 2019 | 7,035.00 |
API Access
MicroAlgo 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=MLGO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MLGO", "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=MLGO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();