Magnite (MGNI) Change in Accured Expenses (2013 - 2026)
Magnite (MGNI) recorded Change in Accured Expenses of $81.39 million in Q2 2026, down 62.8% from $218.64 million a year earlier.
Magnite (MGNI) Change in Accured Expenses (2013 - 2026) Analysis & Trends
On a TTM basis, Magnite's Change in Accured Expenses came in at $150.31 million as of Jun 30, 2026, down 33.4% year-over-year; for FY2025, it came in at $142.6 million, up 46.4% from FY2024.
- Annual Change in Accured Expenses has a five-year compound annual growth rate of 13.7% (FY2020 to FY2025).
- Across earlier years, Change in Accured Expenses came in at $97.38 million in FY2024 (-67.0%), $294.68 million in FY2023 (+222.5%), $91.38 million in FY2022 (-67.9%) and $284.91 million in FY2021 (+279.5%).
- Quarterly Change in Accured Expenses has ranged from -$249.74 million in Q1 2024 to $268.34 million in Q4 2023 over the past five years.
- On a year-over-year basis, Change in Accured Expenses rose in three of the last five quarters, with an average decline of 5.0%.
- Peak year-over-year performance for Change in Accured Expenses in the last five years was growth of 231.6% in Q4 2021, against a decline of 69.8% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at -$21.4 million (Q1 2026), $132.72 million (Q4 2025) and -$42.41 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 3,893.85 Bn | 3,651.37 Bn | 73.85 Bn | 6.31 Bn |
| 2 | Meta Platforms | 1,633.93 Bn | 1,336.45 Bn | 49.47 Bn | 5.93 Bn |
| 3 | Netflix | 271.96 Bn | 233.26 Bn | 6.80 Bn | 85.51 Mn |
| 4 | Alibaba Group Holding | 231.45 Bn | 45.22 Bn | 15.11 Bn | - |
| 5 | Shopify | 218.36 Bn | 195.54 Bn | 1.71 Bn | - |
| 6 | Uber Technologies | 135.44 Bn | 107.24 Bn | 6.38 Bn | 447.00 Mn |
| 7 | Booking Holdings | 119.78 Bn | 52.83 Bn | - | 2.38 Bn |
| 8 | Spotify Technology | 119.39 Bn | 76.31 Bn | 1.89 Bn | - |
| 9 | PDD Holdings | 110.49 Bn | -133.29 Bn | 9.45 Bn | - |
| 10 | Magnite | 3.29 Bn | 1.73 Bn | 130.79 Mn | 81.39 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 81.39 Mn |
| Mar 31, 2026 | -21.40 Mn |
| Dec 31, 2025 | 132.72 Mn |
| Sep 30, 2025 | -42.41 Mn |
| Jun 30, 2025 | 218.64 Mn |
| Mar 31, 2025 | -166.35 Mn |
| Dec 31, 2024 | 80.95 Mn |
| Sep 30, 2024 | 92.53 Mn |
| Jun 30, 2024 | 173.64 Mn |
| Mar 31, 2024 | -249.74 Mn |
| Dec 31, 2023 | 268.34 Mn |
| Sep 30, 2023 | 78.53 Mn |
| Jun 30, 2023 | 88.88 Mn |
| Mar 31, 2023 | -141.07 Mn |
| Dec 31, 2022 | 207.95 Mn |
| Sep 30, 2022 | -84.65 Mn |
| Jun 30, 2022 | 109.39 Mn |
| Mar 31, 2022 | -141.31 Mn |
| Dec 31, 2021 | 171.11 Mn |
| Sep 30, 2021 | -17.22 Mn |
Magnite 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=MGNI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "MGNI", "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=MGNI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();