Angi (ANGI) Accumulated Expenses (2016 - 2026)
Angi (ANGI) posted Accumulated Expenses of $153.62 million for Q2 2026, down 12.3% from $175.15 million a year earlier but up 0.3% from the prior quarter.
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Analysis
Angi (ANGI) Accumulated Expenses (2016 - 2026) Analysis & Trends
At the end of FY2025, Angi's Accumulated Expenses came in at $166.31 million, down 2.9% from FY2024.
- Annual Accumulated Expenses has declined for four consecutive years, though with a five-year compound annual growth rate of 2.3% (FY2020 to FY2025).
- In prior years, Angi's Accumulated Expenses was $171.35 million in FY2024 (-4.4%), $179.33 million in FY2023 (-1.9%), $182.79 million in FY2022 (-1.6%) and $185.75 million in FY2021 (+25.3%).
- Quarterly Accumulated Expenses has run from a low of $146.4 million in Q3 2025 to a high of $238.96 million in Q2 2022 over five years.
- On a year-over-year basis, Accumulated Expenses increased in 1 of the last eight quarters, with an average decline of 7.3%.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q2 2022, with growth of 33.8%; the weakest was Q3 2024, with a decline of 18.1%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $153.14 million (Q1 2026), $166.31 million (Q4 2025) and $146.4 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 4,109.95 Bn | 3,867.48 Bn | 73.85 Bn |
| 2 | Netflix | 282.52 Bn | 242.72 Bn | 6.52 Bn |
| 3 | Alibaba Group Holding | 249.53 Bn | 67.40 Bn | 15.11 Bn |
| 4 | Shopify | 193.10 Bn | 170.29 Bn | 1.71 Bn |
| 5 | Uber Technologies | 138.52 Bn | 110.49 Bn | 6.38 Bn |
| 6 | Booking Holdings | 120.43 Bn | 53.48 Bn | - |
| 7 | PDD Holdings | 108.89 Bn | -143.04 Bn | 9.45 Bn |
| 8 | Spotify Technology | 101.14 Bn | 58.37 Bn | 1.86 Bn |
| 9 | Airbnb | 94.68 Bn | 47.91 Bn | 2.98 Bn |
| 10 | Angi | 291.71 Mn | -785.96 Mn | 236.33 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 153.62 Mn |
| Mar 31, 2026 | 153.14 Mn |
| Dec 31, 2025 | 166.31 Mn |
| Sep 30, 2025 | 146.40 Mn |
| Jun 30, 2025 | 175.15 Mn |
| Mar 31, 2025 | 152.03 Mn |
| Dec 31, 2024 | 171.35 Mn |
| Sep 30, 2024 | 160.26 Mn |
| Jun 30, 2024 | 188.59 Mn |
| Mar 31, 2024 | 161.61 Mn |
| Dec 31, 2023 | 179.33 Mn |
| Sep 30, 2023 | 195.77 Mn |
| Jun 30, 2023 | 212.49 Mn |
| Mar 31, 2023 | 188.88 Mn |
| Dec 31, 2022 | 182.79 Mn |
| Sep 30, 2022 | 194.47 Mn |
| Jun 30, 2022 | 238.96 Mn |
| Mar 31, 2022 | 194.50 Mn |
| Dec 31, 2021 | 185.75 Mn |
| Sep 30, 2021 | 203.75 Mn |
API Access
Angi 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=ANGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "ANGI", "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=ANGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();