Netflix (NFLX) Change in Accured Expenses (2009 - 2026)
Netflix's Change in Accured Expenses was -$1.25 billion in Q2 2026, compared with -$267.24 million a year earlier.
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Analysis
Netflix (NFLX) Change in Accured Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Netflix's Change in Accured Expenses was $888.15 million through Jun 30, 2026, up 848.9% year-over-year; for FY2025, it was $881.22 million, up 359.2% from FY2024.
- Change in Accured Expenses shows a five-year compound annual growth rate of 34.8% (FY2020 to FY2025).
- In earlier years, Change in Accured Expenses was $191.9 million in FY2024 (+85.3%), $103.57 million in FY2023, -$55.51 million in FY2022 and $180.34 million in FY2021 (-9.0%).
- The Q2 2026 figure marks the lowest quarterly Change in Accured Expenses in data going back to Q1 2009.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q1 2026 (growth of 322.9%); the worst was Q1 2023 (a decline of 47.2%).
- Per Business Quant data, NFLX's Change in Accured Expenses in the three quarters before Q2 2026 was $1.3 billion (Q1 2026), $134.89 million (Q4 2025) and $707.15 million (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 | Airbnb | 95.83 Bn | 49.06 Bn | 2.98 Bn | -68.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -1.25 Bn |
| Mar 31, 2026 | 1.30 Bn |
| Dec 31, 2025 | 134.89 Mn |
| Sep 30, 2025 | 707.15 Mn |
| Jun 30, 2025 | -267.24 Mn |
| Mar 31, 2025 | 306.41 Mn |
| Dec 31, 2024 | -124.59 Mn |
| Sep 30, 2024 | 179.01 Mn |
| Jun 30, 2024 | -114.30 Mn |
| Mar 31, 2024 | 251.78 Mn |
| Dec 31, 2023 | -194.54 Mn |
| Sep 30, 2023 | -65.03 Mn |
| Jun 30, 2023 | 177.83 Mn |
| Mar 31, 2023 | 185.30 Mn |
| Dec 31, 2022 | -379.63 Mn |
| Sep 30, 2022 | 212.07 Mn |
| Jun 30, 2022 | -238.72 Mn |
| Mar 31, 2022 | 350.76 Mn |
| Dec 31, 2021 | -95.90 Mn |
| Sep 30, 2021 | 269.77 Mn |
API Access
Netflix 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=NFLX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "NFLX", "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=NFLX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();