Figs (FIGS) Accumulated Expenses (2020 - 2026)
Figs' (FIGS) quarterly Accumulated Expenses came in at $39.5 million in Q2 2026, up 77.77% year-over-year from $22.2 million in Q2 2025, and up 10.84% quarter-over-quarter from $35.7 million in Q1 2026.
Figs (FIGS) Accumulated Expenses (2020 - 2026) Analysis & Trends
Figs (FIGS) has reported Accumulated Expenses for 7 consecutive years, with $39.5 million the latest figure, recorded in Q2 2026.
- On a quarterly basis, Accumulated Expenses rose 77.77% year-over-year to $39.5 million in Q2 2026; TTM through Jun 2026 was $39.5 million, a 77.77% increase from a year earlier, with the FY2025 full-year figure at $20.5 million, down 51.49% from the prior year.
- Accumulated Expenses was $39.5 million for Q2 2026 at Figs, up from $35.7 million in the prior quarter.
- Over five years, Accumulated Expenses peaked at $54.2 million in Q1 2025 and troughed at $7.9 million in Q4 2023.
- A 5-year average of $27.2 million and a median of $25.2 million in 2022 frame the typical range for Accumulated Expenses.
- Across the five-year window, Accumulated Expenses plunged 69.78% in 2023 and jumped 435.24% in 2024, its largest moves.
- Over 5 years, Accumulated Expenses stood at $26.2 million in 2022, then plunged by 69.78% to $7.9 million in 2023, then jumped by 435.24% to $42.3 million in 2024, then sank by 51.49% to $20.5 million in 2025, then soared by 92.55% to $39.5 million in 2026.
- The last three Accumulated Expenses figures came in at $39.5 million (Q2 2026), $35.7 million (Q1 2026), and $20.5 million (Q4 2025), per Business Quant data.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Lululemon Athletica | 10.45 Bn | 9.06 Bn | 1.46 Bn |
| 2 | Levi Strauss | 7.65 Bn | 6.67 Bn | 979.10 Mn |
| 3 | Gildan Activewear | 7.18 Bn | 6.91 Bn | 459.76 Mn |
| 4 | V F | 5.02 Bn | 4.35 Bn | 917.04 Mn |
| 5 | Kontoor Brands | 3.63 Bn | 3.57 Bn | 328.26 Mn |
| 6 | Pvh | 3.38 Bn | 2.42 Bn | 1.32 Bn |
| 7 | Columbia Sportswear | 2.91 Bn | 2.29 Bn | 358.43 Mn |
| 8 | Warby Parker | 2.78 Bn | 2.48 Bn | 136.46 Mn |
| 9 | Figs | 2.06 Bn | 1.76 Bn | 147.86 Mn |
| 10 | Under Armour | 2.04 Bn | 1.65 Bn | 593.83 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 39.53 Mn |
| Mar 31, 2026 | 35.66 Mn |
| Dec 31, 2025 | 20.53 Mn |
| Sep 30, 2025 | 34.19 Mn |
| Jun 30, 2025 | 22.24 Mn |
| Mar 31, 2025 | 54.22 Mn |
| Dec 31, 2024 | 42.32 Mn |
| Sep 30, 2024 | 29.04 Mn |
| Jun 30, 2024 | 21.61 Mn |
| Mar 31, 2024 | 16.60 Mn |
| Dec 31, 2023 | 7.91 Mn |
| Sep 30, 2023 | 16.15 Mn |
| Jun 30, 2023 | 17.99 Mn |
| Mar 31, 2023 | 21.27 Mn |
| Dec 31, 2022 | 26.16 Mn |
| Sep 30, 2022 | 32.37 Mn |
| Jun 30, 2022 | 27.84 Mn |
| Mar 31, 2022 | 24.20 Mn |
| Dec 31, 2021 | 24.68 Mn |
| Sep 30, 2021 | 21.78 Mn |
Figs 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=FIGS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "FIGS", "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=FIGS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();