Steven Madden (SHOO) Total Non-Current Liabilities (2010 - 2026)
Steven Madden (SHOO) posted Total Non-Current Liabilities of $848.69 million for Q2 2026, down 16.3% from $1.01 billion a year earlier and down 14.5% from the prior quarter.
Steven Madden (SHOO) Total Non-Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Steven Madden's Total Non-Current Liabilities came in at $995.42 million, up 88.5% from FY2024.
- Annual Total Non-Current Liabilities has increased for three consecutive years, with a five-year compound annual growth rate of 23.4% (FY2020 to FY2025).
- In prior years, Steven Madden's Total Non-Current Liabilities was $528.21 million in FY2024 (+7.8%), $489.94 million in FY2023 (+18.3%), $414.13 million in FY2022 (-21.6%) and $528.04 million in FY2021 (+52.1%).
- The Q2 2026 figure stands as the lowest quarterly Total Non-Current Liabilities since Q1 2025.
- On a year-over-year basis, Total Non-Current Liabilities increased in seven of the last eight quarters, with growth averaging 50.1%.
- The strongest year-over-year quarter for Total Non-Current Liabilities in the past five years was Q1 2026, with growth of 90.7%; the weakest was Q3 2022, with a decline of 24.4%.
- According to Business Quant data, Total Non-Current Liabilities for the three prior quarters was $992.45 million (Q1 2026), $995.42 million (Q4 2025) and $1.1 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 52.47 Bn | 18.46 Bn | 5.39 Bn | - |
| 2 | Tapestry | 23.05 Bn | 19.01 Bn | 1.56 Bn | 5.46 Bn |
| 3 | Ralph Lauren | 21.35 Bn | 13.45 Bn | 1.44 Bn | 4.76 Bn |
| 4 | Deckers Outdoor | 11.12 Bn | 3.99 Bn | - | 384.05 Mn |
| 5 | Lululemon Athletica | 10.25 Bn | 4.50 Bn | 1.46 Bn | 3.63 Bn |
| 6 | Levi Strauss | 7.60 Bn | 4.25 Bn | 979.10 Mn | 4.12 Bn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 4.37 Bn |
| 8 | Birkenstock Holding | 5.97 Bn | 4.27 Bn | 493.89 Mn | 2.75 Bn |
| 9 | Crocs | 5.64 Bn | 5.06 Bn | 700.71 Mn | 2.33 Bn |
| 10 | Steven Madden | 3.28 Bn | 2.92 Bn | 309.66 Mn | 848.69 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 848.69 Mn |
| Mar 31, 2026 | 992.45 Mn |
| Dec 31, 2025 | 995.42 Mn |
| Sep 30, 2025 | 1.10 Bn |
| Jun 30, 2025 | 1.01 Bn |
| Mar 31, 2025 | 520.46 Mn |
| Dec 31, 2024 | 528.21 Mn |
| Sep 30, 2024 | 585.86 Mn |
| Jun 30, 2024 | 533.17 Mn |
| Mar 31, 2024 | 449.33 Mn |
| Dec 31, 2023 | 489.94 Mn |
| Sep 30, 2023 | 427.60 Mn |
| Jun 30, 2023 | 417.84 Mn |
| Mar 31, 2023 | 356.96 Mn |
| Dec 31, 2022 | 414.13 Mn |
| Sep 30, 2022 | 363.37 Mn |
| Jun 30, 2022 | 459.04 Mn |
| Mar 31, 2022 | 424.19 Mn |
| Dec 31, 2021 | 528.04 Mn |
| Sep 30, 2021 | 480.88 Mn |
Steven Madden Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=SHOO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "SHOO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=SHOO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();