Weibo (WB) Accumulated Expenses (2013 - 2026)
Weibo's Accumulated Expenses was $629.96 million in Q2 2026, up 8.1% from $582.52 million a year earlier but down 2.0% from the prior quarter.
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Analysis
Weibo (WB) Accumulated Expenses (2013 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Weibo came in at $634.45 million, down 0.9% from FY2024.
- Accumulated Expenses has now declined for three consecutive years, though with a five-year compound annual growth rate of 2.6% (FY2020 to FY2025).
- In earlier years, Accumulated Expenses was $640.21 million in FY2024 (-2.5%), $656.45 million in FY2023 (-28.2%), $913.98 million in FY2022 (+11.3%) and $821.03 million in FY2021 (+47.5%).
- Quarterly Accumulated Expenses has moved between $578.68 million (Q3 2025) and $913.98 million (Q4 2022) over five years.
- Compared with a year earlier, Accumulated Expenses was higher in two of the last eight quarters, with an average decline of 1.0%.
- The best year-over-year quarter for Accumulated Expenses over five years was Q3 2021 (growth of 61.8%); the worst was Q4 2023 (a decline of 28.2%).
- Per Business Quant data, WB's Accumulated Expenses in the three quarters before Q2 2026 was $642.55 million (Q1 2026), $634.45 million (Q4 2025) and $578.68 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 3,530.47 Bn | 3,265.37 Bn | 76.16 Bn |
| 2 | Meta Platforms | 1,632.54 Bn | 1,297.06 Bn | 51.23 Bn |
| 3 | Netflix | 263.43 Bn | 224.73 Bn | 6.80 Bn |
| 4 | Alibaba Group Holding | 244.80 Bn | 58.43 Bn | 15.16 Bn |
| 5 | Shopify | 193.65 Bn | 172.45 Bn | 1.78 Bn |
| 6 | Uber Technologies | 141.77 Bn | 112.59 Bn | 6.42 Bn |
| 7 | AppLovin | 135.64 Bn | 124.17 Bn | 1.94 Bn |
| 8 | Spotify Technology | 122.22 Bn | 79.14 Bn | 1.89 Bn |
| 9 | Booking Holdings | 121.62 Bn | 55.37 Bn | - |
| 10 | 1.53 Bn | -8.15 Bn | 324.02 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 629.96 Mn |
| Mar 31, 2026 | 642.55 Mn |
| Dec 31, 2025 | 634.45 Mn |
| Sep 30, 2025 | 578.68 Mn |
| Jun 30, 2025 | 582.52 Mn |
| Mar 31, 2025 | 649.89 Mn |
| Dec 31, 2024 | 640.21 Mn |
| Sep 30, 2024 | 638.83 Mn |
| Jun 30, 2024 | 625.54 Mn |
| Mar 31, 2024 | 662.80 Mn |
| Dec 31, 2023 | 656.45 Mn |
| Sep 30, 2023 | 597.53 Mn |
| Jun 30, 2023 | 675.96 Mn |
| Mar 31, 2023 | 705.89 Mn |
| Dec 31, 2022 | 913.98 Mn |
| Sep 30, 2022 | 632.78 Mn |
| Jun 30, 2022 | 756.96 Mn |
| Mar 31, 2022 | 799.88 Mn |
| Dec 31, 2021 | 821.03 Mn |
| Sep 30, 2021 | 732.52 Mn |
API Access
Weibo 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=WB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "WB", "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=WB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();