National Presto Industries (NPK) Total Liabilities (2010 - 2026)
National Presto Industries' Total Liabilities came in at $87.34 million for Q2 2026, down 10.7% from $97.79 million a year earlier but up 17.8% from the prior quarter.
National Presto Industries (NPK) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, National Presto Industries' Total Liabilities was $105.6 million, up 23.1% from FY2024.
- Total Liabilities has increased in each of the last six years, with a five-year compound annual growth rate of 12.4% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $85.77 million in FY2024 (+1.8%), $84.28 million in FY2023 (+32.1%), $63.8 million in FY2022 (+1.6%) and $62.78 million in FY2021 (+6.7%).
- The five-year range for quarterly Total Liabilities is $57.61 million (Q2 2022) to $124.06 million (Q3 2025).
- Year-over-year, Total Liabilities increased in six of the last eight quarters, with growth averaging 10.7%.
- The fastest year-over-year change in Total Liabilities over five years came in Q3 2025 (growth of 50.7%), and the weakest in Q1 2026 (a decline of 14.5%).
- Business Quant data shows NPK's Total Liabilities at $74.14 million (Q1 2026), $105.6 million (Q4 2025) and $124.06 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | SharkNinja | 25.65 Bn | 23.31 Bn | 860.34 Mn | 2.75 Bn |
| 2 | Somnigroup International | 13.10 Bn | 12.65 Bn | 817.20 Mn | 8.38 Bn |
| 3 | Hni | 3.38 Bn | 2.95 Bn | 647.20 Mn | 3.01 Bn |
| 4 | Newell Brands | 2.32 Bn | 1.47 Bn | 812.00 Mn | 8.61 Bn |
| 5 | Sonos | 2.13 Bn | 1.02 Bn | 189.31 Mn | 478.59 Mn |
| 6 | Whirlpool | 2.04 Bn | -1.44 Bn | 442.00 Mn | 13.39 Bn |
| 7 | Corsair Gaming | 1.46 Bn | 1.00 Bn | 104.29 Mn | 551.41 Mn |
| 8 | Millerknoll | 1.38 Bn | 756.09 Mn | 395.60 Mn | 2.66 Bn |
| 9 | Arhaus | 1.36 Bn | 443.23 Mn | 172.07 Mn | 1.04 Bn |
| 10 | National Presto Industries | 1.04 Bn | 1.01 Bn | 28.55 Mn | 87.34 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 5, 2026 | 87.34 Mn |
| Mar 31, 2026 | 74.14 Mn |
| Dec 31, 2025 | 105.60 Mn |
| Sep 28, 2025 | 124.06 Mn |
| Jun 29, 2025 | 97.79 Mn |
| Mar 30, 2025 | 86.71 Mn |
| Dec 31, 2024 | 85.77 Mn |
| Sep 29, 2024 | 82.33 Mn |
| Jun 30, 2024 | 80.01 Mn |
| Mar 31, 2024 | 85.82 Mn |
| Dec 31, 2023 | 84.28 Mn |
| Oct 1, 2023 | 73.29 Mn |
| Jul 2, 2023 | 66.51 Mn |
| Apr 2, 2023 | 66.40 Mn |
| Dec 31, 2022 | 63.80 Mn |
| Oct 2, 2022 | 61.92 Mn |
| Jul 3, 2022 | 57.61 Mn |
| Apr 3, 2022 | 59.12 Mn |
| Dec 31, 2021 | 62.78 Mn |
| Oct 3, 2021 | 71.84 Mn |
National Presto Industries Total 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-liabilities&ticker=NPK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "NPK", "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-liabilities&ticker=NPK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();