Warby Parker (WRBY) Depreciation & Amortization (CF) (2020 - 2026)
Warby Parker's Depreciation & Amortization (CF) was $14.07 million in Q2 2026, up 12.7% from $12.49 million a year earlier and up 2.2% from the prior quarter.
Warby Parker (WRBY) Depreciation & Amortization (CF) (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Warby Parker's Depreciation & Amortization (CF) was $53.47 million through Jun 30, 2026, up 9.5% year-over-year; for FY2025, it came in at $50.28 million, up 9.6% from FY2024.
- Depreciation & Amortization (CF) has now increased for six consecutive years, with a five-year compound annual growth rate of 23.1% (FY2020 to FY2025).
- In earlier years, Depreciation & Amortization (CF) was $45.87 million in FY2024 (+19.0%), $38.55 million in FY2023 (+21.0%), $31.86 million in FY2022 (+47.9%) and $21.55 million in FY2021 (+21.3%).
- The Q2 2026 figure marks the highest quarterly Depreciation & Amortization (CF) in data going back to Q4 2020.
- Compared with a year earlier, Depreciation & Amortization (CF) has increased for 19 straight quarters, with growth averaging 13.2% over the last eight quarters.
- The year-over-year growth in Depreciation & Amortization (CF) has ranged between 5.9% (Q3 2025) and 55.6% (Q3 2022) over the last five years.
- Per Business Quant data, WRBY's Depreciation & Amortization (CF) in the three quarters before Q2 2026 was $13.77 million (Q1 2026), $13.1 million (Q4 2025) and $12.53 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Dep. & Amort. (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 56.89 Bn | 23.09 Bn | 4.80 Bn | 193.00 Mn |
| 2 | Ralph Lauren | 22.95 Bn | 15.05 Bn | 1.44 Bn | 58.90 Mn |
| 3 | Tapestry | 22.81 Bn | 18.77 Bn | 1.56 Bn | 45.20 Mn |
| 4 | Deckers Outdoor | 12.13 Bn | 5.00 Bn | - | - |
| 5 | Lululemon Athletica | 11.09 Bn | 5.34 Bn | 1.46 Bn | 142.33 Mn |
| 6 | Levi Strauss | 8.25 Bn | 4.84 Bn | 1.07 Bn | 54.80 Mn |
| 7 | Gildan Activewear | 7.59 Bn | 6.51 Bn | 459.76 Mn | 68.32 Mn |
| 8 | V F | 6.87 Bn | 3.49 Bn | 917.04 Mn | 57.79 Mn |
| 9 | Birkenstock Holding | 6.20 Bn | 4.52 Bn | 493.89 Mn | 40.22 Mn |
| 10 | Warby Parker | 3.16 Bn | 2.02 Bn | 136.46 Mn | 14.07 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.07 Mn |
| Mar 31, 2026 | 13.77 Mn |
| Dec 31, 2025 | 13.10 Mn |
| Sep 30, 2025 | 12.53 Mn |
| Jun 30, 2025 | 12.49 Mn |
| Mar 31, 2025 | 12.16 Mn |
| Dec 31, 2024 | 12.33 Mn |
| Sep 30, 2024 | 11.83 Mn |
| Jun 30, 2024 | 11.12 Mn |
| Mar 31, 2024 | 10.58 Mn |
| Dec 31, 2023 | 10.37 Mn |
| Sep 30, 2023 | 9.76 Mn |
| Jun 30, 2023 | 9.28 Mn |
| Mar 31, 2023 | 9.14 Mn |
| Dec 31, 2022 | 8.92 Mn |
| Sep 30, 2022 | 8.34 Mn |
| Jun 30, 2022 | 7.88 Mn |
| Mar 31, 2022 | 6.91 Mn |
| Dec 31, 2021 | 6.37 Mn |
| Sep 30, 2021 | 5.36 Mn |
Warby Parker Depreciation & Amortization (CF) 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=depreciation-and-amortization-cf&ticker=WRBY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "depreciation-and-amortization-cf", "ticker": "WRBY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=depreciation-and-amortization-cf&ticker=WRBY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();