Idt (IDT) Operating Expenses (2010 - 2026)
Idt's Operating Expenses was $101.62 million in fiscal Q4 2026 (quarter ended Jul 31, 2026), up 9.7% from $92.61 million a year earlier and up 9.6% from the prior quarter.
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Analysis
Idt (IDT) Operating Expenses (2010 - 2026) Analysis & Trends
For FY2026 (ended Jul 31, 2026), Operating Expenses at Idt came in at $375.62 million, up 8.6% from FY2025.
- Operating Expenses has now increased for four consecutive fiscal years, though with a five-year compound annual growth rate of -23.0% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $345.77 million in FY2025 (+6.3%), $325.4 million in FY2024 (+9.7%), $296.5 million in FY2023 (+11.9%) and $264.91 million in FY2022 (-81.0%).
- The fiscal Q4 2026 figure marks the highest quarterly Operating Expenses since fiscal Q3 2022.
- Compared with a year earlier, Operating Expenses has increased for five straight quarters, with growth averaging 7.5% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q4 2025 (growth of 12.9%); the worst was fiscal Q1 2023 (a decline of 80.7%).
- Per Business Quant data, IDT's Operating Expenses in the three fiscal quarters before Q4 2026 was $92.71 million (Q3 2026), $94.03 million (Q2 2026) and $87.25 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Verizon Communications | 187.82 Bn | 187.82 Bn | - | - |
| 2 | T-Mobile US | 170.42 Bn | 152.85 Bn | 15.13 Bn | 17.92 Bn |
| 3 | At&T | 146.99 Bn | 88.45 Bn | 26.22 Bn | 28.23 Bn |
| 4 | Grupo Televisa, S.A.B | 127.90 Bn | 119.63 Bn | 318.12 Mn | 115.06 Mn |
| 5 | Comcast | 84.34 Bn | 50.13 Bn | - | 23.98 Bn |
| 6 | Chunghwa Telecom | 37.90 Bn | 29.92 Bn | 728.80 Mn | 309.31 Mn |
| 7 | Vodafone Group Public | 37.53 Bn | 6.93 Bn | - | -125.27 Mn |
| 8 | EchoStar | 28.79 Bn | 19.88 Bn | 1.65 Bn | 3.06 Bn |
| 9 | Bce | 19.11 Bn | 17.23 Bn | 3.38 Bn | 2.51 Bn |
| 10 | Idt | 2.06 Bn | 1.11 Bn | 134.83 Mn | 101.62 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 101.62 Mn |
| Apr 30, 2026 | 92.71 Mn |
| Jan 31, 2026 | 94.03 Mn |
| Oct 31, 2025 | 87.25 Mn |
| Jul 31, 2025 | 92.61 Mn |
| Apr 30, 2025 | 85.38 Mn |
| Jan 31, 2025 | 83.79 Mn |
| Oct 31, 2024 | 83.99 Mn |
| Jul 31, 2024 | 82.06 Mn |
| Apr 30, 2024 | 85.61 Mn |
| Jan 31, 2024 | 80.91 Mn |
| Oct 31, 2023 | 76.83 Mn |
| Jul 31, 2023 | 78.75 Mn |
| Apr 30, 2023 | 77.18 Mn |
| Jan 31, 2023 | 72.26 Mn |
| Oct 31, 2022 | 68.92 Mn |
| Jul 31, 2022 | -728.96 Mn |
| Apr 30, 2022 | 314.85 Mn |
| Jan 31, 2022 | 322.80 Mn |
| Oct 31, 2021 | 356.22 Mn |
API Access
Idt Operating Expenses 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=operating-expenses&ticker=IDT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IDT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=IDT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();