Photronics (PLAB) Total Liabilities (2010 - 2026)
Photronics' Total Liabilities was $247.04 million in fiscal Q3 2026 (quarter ended Aug 2, 2026), up 15.0% from $214.77 million a year earlier and up 4.1% from the prior quarter.
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Analysis
Photronics (PLAB) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Oct 31, 2025), Total Liabilities at Photronics came in at $207.23 million, down 10.4% from FY2024.
- Total Liabilities has now declined for four consecutive fiscal years, with a five-year compound annual growth rate of -1.7% (FY2020 to FY2025).
- In earlier fiscal years, Total Liabilities was $231.3 million in FY2024 (-7.7%), $250.61 million in FY2023 (-1.2%), $253.74 million in FY2022 (-13.6%) and $293.64 million in FY2021 (+30.0%).
- Quarterly Total Liabilities has moved between $206.26 million (fiscal Q2 2025) and $296.08 million (fiscal Q1 2022) over five years.
- Compared with a year earlier, Total Liabilities has increased for three straight quarters, with growth averaging 0.1% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was fiscal Q4 2021 (growth of 30.0%); the worst was fiscal Q4 2022 (a decline of 13.6%).
- Per Business Quant data, PLAB's Total Liabilities in the three fiscal quarters before Q3 2026 was $237.37 million (Q2 2026), $251.5 million (Q1 2026) and $207.23 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,369.70 Bn | 5,143.86 Bn | 72.14 Bn | 91.29 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,240.62 Bn | 1,865.48 Bn | 27.22 Bn | 92.36 Bn |
| 3 | Broadcom | 1,610.24 Bn | 1,536.29 Bn | 20.46 Bn | 88.46 Bn |
| 4 | Micron Technology | 1,032.70 Bn | 938.34 Bn | 47.05 Bn | 57.51 Bn |
| 5 | Advanced Micro Devices | 903.31 Bn | 860.06 Bn | 6.20 Bn | 17.24 Bn |
| 6 | Asml Holding | 651.41 Bn | 607.10 Bn | 5.90 Bn | 36.36 Bn |
| 7 | Intel | 474.60 Bn | 343.73 Bn | 6.51 Bn | 99.30 Bn |
| 8 | Lam Research | 327.65 Bn | 304.45 Bn | 3.48 Bn | 11.06 Bn |
| 9 | Applied Materials | 324.38 Bn | 289.82 Bn | 4.59 Bn | 17.90 Bn |
| 10 | Photronics | 1.68 Bn | -854.37 Mn | 71.73 Mn | 247.04 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 247.04 Mn |
| May 3, 2026 | 237.37 Mn |
| Feb 1, 2026 | 251.50 Mn |
| Oct 31, 2025 | 207.23 Mn |
| Aug 3, 2025 | 214.77 Mn |
| May 4, 2025 | 206.26 Mn |
| Feb 2, 2025 | 210.46 Mn |
| Oct 31, 2024 | 231.30 Mn |
| Jul 28, 2024 | 231.67 Mn |
| Apr 28, 2024 | 235.42 Mn |
| Jan 28, 2024 | 235.78 Mn |
| Oct 31, 2023 | 250.61 Mn |
| Jul 30, 2023 | 251.47 Mn |
| Apr 30, 2023 | 246.34 Mn |
| Jan 29, 2023 | 258.96 Mn |
| Oct 31, 2022 | 253.74 Mn |
| Jul 31, 2022 | 269.64 Mn |
| May 1, 2022 | 281.66 Mn |
| Jan 30, 2022 | 296.08 Mn |
| Oct 31, 2021 | 293.64 Mn |
API Access
Photronics 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=PLAB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PLAB", "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=PLAB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();