Applied Optoelectronics (AAOI) Long-Term Debt Repayments (2013 - 2026)
Applied Optoelectronics (AAOI) reported Long-Term Debt Repayments of $35.77 million for Q2 2026, up 51.3% from $23.64 million a year earlier and up 6.9% from the prior quarter.
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Analysis
Applied Optoelectronics (AAOI) Long-Term Debt Repayments (2013 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Applied Optoelectronics' Long-Term Debt Repayments came in at $134.43 million, up 133.8% year-over-year; for FY2025, it was $108.03 million, up 169.0% from FY2024.
- Long-Term Debt Repayments has a five-year compound annual growth rate of 28.1% (FY2020 to FY2025).
- By year, Long-Term Debt Repayments came in at $40.17 million in FY2024 (-25.3%), $53.75 million in FY2023 (+32.5%), $40.57 million in FY2022 (+25.0%) and $32.47 million in FY2021 (+3.6%).
- The Q2 2026 figure ranks as the highest quarterly Long-Term Debt Repayments in data going back to Q1 2013.
- Year over year, Long-Term Debt Repayments has now increased in each of the last four quarters, with growth averaging 122.7% over the last seven quarters.
- The high point for year-over-year Long-Term Debt Repayments in five years was Q3 2025 (growth of 528.5%); the low point was Q2 2023 (a decline of 99.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $33.45 million (Q1 2026), $33.81 million (Q4 2025) and $31.41 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 5,087.13 Bn | 4,834.62 Bn | 54.77 Bn | 232.00 Mn |
| 2 | Cisco Systems | 413.90 Bn | 349.82 Bn | 11.06 Bn | 4.40 Bn |
| 3 | Dell Technologies | 289.90 Bn | 245.66 Bn | 9.83 Bn | 1.02 Bn |
| 4 | Arista Networks | 215.69 Bn | 169.14 Bn | 1.91 Bn | - |
| 5 | Sandisk | 184.10 Bn | 172.62 Bn | 7.58 Bn | - |
| 6 | Sony | 161.13 Bn | 100.89 Bn | 6.53 Bn | -67.19 Mn |
| 7 | Seagate Technology Holdings | 145.63 Bn | 140.62 Bn | 1.90 Bn | 300.00 Mn |
| 8 | Western Digital | 127.86 Bn | 115.99 Bn | 2.03 Bn | 1.32 Bn |
| 9 | Hewlett Packard Enterprise | 73.67 Bn | 51.55 Bn | 4.93 Bn | 1.32 Bn |
| 10 | Applied Optoelectronics | 5.74 Bn | 4.46 Bn | 53.21 Mn | 35.85 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 35.85 Mn |
| Mar 31, 2026 | 33.46 Mn |
| Dec 31, 2025 | 33.81 Mn |
| Sep 30, 2025 | 31.43 Mn |
| Jun 30, 2025 | 23.64 Mn |
| Mar 31, 2025 | 19.23 Mn |
| Dec 31, 2024 | 14.09 Mn |
| Sep 30, 2024 | 5.00 Mn |
| Mar 31, 2024 | 15.16 Mn |
| Dec 31, 2023 | 14.10 Mn |
| Sep 30, 2023 | 8.63 Mn |
| Jun 30, 2023 | 10,000.00 |
| Mar 31, 2023 | 12.30 Mn |
| Dec 31, 2022 | 13.52 Mn |
| Sep 30, 2022 | 9.78 Mn |
| Jun 30, 2022 | 16.49 Mn |
| Mar 31, 2022 | 8.14 Mn |
| Dec 31, 2021 | 7.19 Mn |
| Sep 30, 2021 | 7.00 Mn |
| Jun 30, 2021 | 7.13 Mn |
API Access
Applied Optoelectronics Long-Term Debt Repayments 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=long-term-debt-repayments&ticker=AAOI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "ticker": "AAOI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=long-term-debt-repayments&ticker=AAOI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();