Digital Brands (DBGI) EPS (Basic) (2020 - 2026)
Digital Brands' (DBGI) quarterly EPS (Basic) came in at -$11.49 in Q2 2026, up 64.44% on a YoY basis from -$6.99 in Q2 2025, and up 59.25% quarter-over-quarter from -$28.19 in Q1 2026.
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Digital Brands (DBGI) EPS (Basic) (2020 - 2026) Analysis & Trends
Digital Brands (DBGI) has reported EPS (Basic) for 7 consecutive years, with -$11.49 the latest figure, recorded in Q2 2026.
- For the quarter ending Q2 2026, EPS (Basic) rose 64.44% year-over-year to -$11.49; the trailing twelve-month figure through Jun 2026 stood at -$61.93 (up 69.12% YoY), and the FY2025 full-year result was -$87.0, up 97.16% from the prior year.
- EPS (Basic) climbed to -$11.49 in Q2 2026 per DBGI's latest filing, from -$28.19 in the prior quarter.
- Across five years, EPS (Basic) topped out at $817.18 in Q2 2023 and bottomed at -$42283.9 in Q1 2022.
- Historically, EPS (Basic) has averaged -$5365.6 across 5 years, with a median of -$74.15 in 2024.
- The sharpest annual moves came in 2022 and 2023: EPS (Basic) tumbled 1095.02% in 2022, then surged 102.73% in 2023.
- Over 5 years, EPS (Basic) stood at -$17200.0 in 2022, then soared by 98.48% to -$261.24 in 2023, then tumbled by 382.51% to -$1260.5 in 2024, then soared by 94.92% to -$64.05 in 2025, then jumped by 82.06% to -$11.49 in 2026.
- According to Business Quant data, EPS (Basic) over the past three periods registered -$11.49, -$28.19, and -$64.05 for Q2 2026, Q1 2026, and Q4 2025 respectively.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Basic) (Qtr) |
|---|---|---|---|---|---|
| 1 | Lululemon Athletica | 10.45 Bn | 9.06 Bn | 1.46 Bn | 2.92 |
| 2 | Levi Strauss | 7.65 Bn | 6.67 Bn | 979.10 Mn | 0.23 |
| 3 | Gildan Activewear | 7.18 Bn | 6.91 Bn | 459.76 Mn | 0.56 |
| 4 | V F | 5.02 Bn | 4.35 Bn | 917.04 Mn | -0.25 |
| 5 | Kontoor Brands | 3.63 Bn | 3.57 Bn | 328.26 Mn | 1.13 |
| 6 | Pvh | 3.38 Bn | 2.42 Bn | 1.32 Bn | -2.23 |
| 7 | Columbia Sportswear | 2.91 Bn | 2.29 Bn | 358.43 Mn | 0.52 |
| 8 | Warby Parker | 2.78 Bn | 2.48 Bn | 136.46 Mn | 0.04 |
| 9 | Figs | 2.06 Bn | 1.76 Bn | 147.86 Mn | 0.17 |
| 10 | Digital Brands | 2.45 Mn | 1.06 Mn | 324,265.00 | -11.49 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -11.49 |
| Mar 31, 2026 | -28.19 |
| Dec 31, 2025 | -64.05 |
| Sep 30, 2025 | -47.19 |
| Jun 30, 2025 | -32.30 |
| Mar 31, 2025 | -37.42 |
| Dec 31, 2024 | -1,260.53 |
| Sep 30, 2024 | -64.22 |
| Jun 30, 2024 | -84.09 |
| Mar 31, 2024 | -19.65 |
| Dec 31, 2023 | -261.24 |
| Sep 30, 2023 | -576.01 |
| Jun 30, 2023 | 817.18 |
| Mar 31, 2023 | -633.64 |
| Dec 31, 2022 | -17,199.96 |
| Sep 30, 2022 | -4,913.48 |
| Jun 30, 2022 | -29,880.22 |
| Mar 31, 2022 | -42,283.92 |
| Dec 31, 2021 | -163,746.82 |
| Sep 30, 2021 | -67,057.32 |
API Access
Digital Brands EPS (Basic) 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=eps-basic&ticker=DBGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-basic", "ticker": "DBGI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=eps-basic&ticker=DBGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();