Appsoft Technologies (ASFT) Change in Accured Expenses (2015 - 2026)
Appsoft Technologies (ASFT) posted Change in Accured Expenses of $2,772 for Q2 2026, up 13.9% from $2,434 a year earlier and up 3.4% from the prior quarter.
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Analysis
Appsoft Technologies (ASFT) Change in Accured Expenses (2015 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at Appsoft Technologies was $10,598, up 17.8% year-over-year; for FY2025, it came in at $9,846, up 17.9% from FY2024.
- Annual Change in Accured Expenses shows a five-year compound annual growth rate of 17.5% (FY2020 to FY2025).
- In prior years, Appsoft Technologies' Change in Accured Expenses was $8,354 in FY2024, -$13,681 in FY2023 and -$17,107 in FY2021.
- The Q2 2026 figure stands as the highest quarterly Change in Accured Expenses since Q2 2020.
- On a year-over-year basis, Change in Accured Expenses has increased in each of the last six quarters, with growth averaging 24.5% over the last seven quarters.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q3 2024, with growth of 67.9%; the weakest was Q1 2022, with a decline of 100.0%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was $2,681 (Q1 2026), $2,621 (Q4 2025) and $2,524 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,173.87 Bn | 3,931.39 Bn | 73.85 Bn | 6.31 Bn |
| 2 | Meta Platforms | 1,849.67 Bn | 1,552.19 Bn | 49.47 Bn | 5.93 Bn |
| 3 | Netflix | 279.23 Bn | 239.43 Bn | 6.52 Bn | -1.25 Bn |
| 4 | Alibaba Group Holding | 245.86 Bn | 63.73 Bn | 15.11 Bn | - |
| 5 | Shopify | 196.08 Bn | 173.27 Bn | 1.71 Bn | - |
| 6 | Uber Technologies | 138.90 Bn | 110.88 Bn | 6.38 Bn | 447.00 Mn |
| 7 | Booking Holdings | 119.48 Bn | 52.53 Bn | - | 2.38 Bn |
| 8 | PDD Holdings | 107.30 Bn | -144.64 Bn | 9.45 Bn | - |
| 9 | Spotify Technology | 97.33 Bn | 54.56 Bn | 1.86 Bn | - |
| 10 | Appsoft Technologies | 1.12 Mn | 1.12 Mn | - | 2,772.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2,772.00 |
| Mar 31, 2026 | 2,681.00 |
| Dec 31, 2025 | 2,621.00 |
| Sep 30, 2025 | 2,524.00 |
| Jun 30, 2025 | 2,434.00 |
| Mar 31, 2025 | 2,267.00 |
| Dec 31, 2024 | 2,183.00 |
| Sep 30, 2024 | 2,114.00 |
| Jun 30, 2024 | 2,072.00 |
| Mar 31, 2024 | 1,985.00 |
| Dec 31, 2023 | -4,253.00 |
| Sep 30, 2023 | 1,259.00 |
| Jun 30, 2023 | -12,156.00 |
| Mar 31, 2023 | 1,469.00 |
| Sep 30, 2022 | -1.00 |
| Mar 31, 2022 | 1.00 |
| Dec 31, 2021 | -14,607.00 |
| Sep 30, 2021 | -5,031.00 |
| Jun 30, 2021 | 232.00 |
| Mar 31, 2021 | 2,299.00 |
API Access
Appsoft Technologies Change in Accured 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=change-in-accured-expenses&ticker=ASFT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "ASFT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=ASFT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();