Roku (ROKU) Change in Accured Expenses (2016 - 2026)
Roku (ROKU) posted Change in Accured Expenses of $76.85 million for Q2 2026, up 751.2% from $9.03 million a year earlier.
Roku (ROKU) Change in Accured Expenses (2016 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at Roku was $172.09 million, up 206.5% year-over-year; for FY2025, it came in at $87.62 million, up 128.3% from FY2024.
- Annual Change in Accured Expenses shows a five-year compound annual growth rate of -7.2% (FY2020 to FY2025).
- In prior years, Roku's Change in Accured Expenses was $38.39 million in FY2024 (-33.5%), $57.71 million in FY2023 (-65.5%), $167.53 million in FY2022 (+29.9%) and $128.93 million in FY2021 (+1.3%).
- Quarterly Change in Accured Expenses has run from a low of -$109.59 million in Q1 2024 to a high of $162.51 million in Q3 2023 over five years.
- On a year-over-year basis, Change in Accured Expenses increased in two of the last five quarters, with growth averaging 125.1%.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q2 2026, with growth of 751.2%; the weakest was Q2 2025, with a decline of 78.9%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was -$41.34 million (Q1 2026), $12.01 million (Q4 2025) and $124.57 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 328.64 Bn | 313.71 Bn | 2.30 Bn | 369.00 Mn |
| 2 | CrowdStrike Holdings | 276.50 Bn | 256.94 Bn | 1.10 Bn | 72.38 Mn |
| 3 | Fortinet | 132.74 Bn | 118.67 Bn | 1.64 Bn | 75.10 Mn |
| 4 | Snowflake | 120.19 Bn | 107.50 Bn | 1.04 Bn | 108.85 Mn |
| 5 | Datadog | 99.51 Bn | 81.15 Bn | 881.34 Mn | 6.98 Mn |
| 6 | Okta | 35.35 Bn | 25.44 Bn | 641.00 Mn | -2.00 Mn |
| 7 | Axon Enterprise | 33.58 Bn | 28.10 Bn | 546.45 Mn | 256.58 Mn |
| 8 | Zscaler | 32.06 Bn | 18.18 Bn | - | - |
| 9 | MongoDB | 28.84 Bn | 19.30 Bn | 569.77 Mn | 43.09 Mn |
| 10 | Roku | 22.61 Bn | 13.06 Bn | 673.70 Mn | 76.85 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 76.85 Mn |
| Mar 31, 2026 | -41.34 Mn |
| Dec 31, 2025 | 12.01 Mn |
| Sep 30, 2025 | 124.57 Mn |
| Jun 30, 2025 | 9.03 Mn |
| Mar 31, 2025 | -57.98 Mn |
| Dec 31, 2024 | 24.34 Mn |
| Sep 30, 2024 | 80.76 Mn |
| Jun 30, 2024 | 42.88 Mn |
| Mar 31, 2024 | -109.59 Mn |
| Dec 31, 2023 | -12.50 Mn |
| Sep 30, 2023 | 162.51 Mn |
| Jun 30, 2023 | 215,000.00 |
| Mar 31, 2023 | -92.50 Mn |
| Dec 31, 2022 | 140.27 Mn |
| Sep 30, 2022 | 27.73 Mn |
| Jun 30, 2022 | -11.66 Mn |
| Mar 31, 2022 | 11.18 Mn |
| Dec 31, 2021 | 94.73 Mn |
| Sep 30, 2021 | 17.66 Mn |
Roku 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=ROKU&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "ROKU", "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=ROKU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();