Tootsie Roll Industries (TR) Operating Expenses (2009 - 2026)
Tootsie Roll Industries (TR) reported Operating Expenses of $54.25 million for Q2 2026, up 22.3% from $44.36 million a year earlier and up 93.2% from the prior quarter.
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Analysis
Tootsie Roll Industries (TR) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Tootsie Roll Industries' Operating Expenses came in at $166.08 million, up 8.9% year-over-year; for FY2025, it came in at $157.5 million, up 3.2% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 7.0% (FY2020 to FY2025).
- By year, Operating Expenses came in at $152.68 million in FY2024 (-1.5%), $155.01 million in FY2023 (+27.1%), $121.98 million in FY2022 (-7.7%) and $132.11 million in FY2021 (+17.8%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q2 2009.
- Year over year, Operating Expenses gained in four of the last eight quarters, with growth averaging 3.7%.
- The high point for year-over-year Operating Expenses in five years was Q2 2023 (growth of 83.1%); the low point was Q2 2022 (a decline of 36.1%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $28.08 million (Q1 2026), $36.72 million (Q4 2025) and $47.03 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 133.59 Bn | 108.95 Bn | - | - |
| 2 | Mondelez International | 75.71 Bn | 69.03 Bn | 3.99 Bn | 2.01 Bn |
| 3 | Hershey | 32.64 Bn | 28.88 Bn | 1.26 Bn | 628.91 Mn |
| 4 | Kraft Heinz | 27.82 Bn | 14.35 Bn | 2.03 Bn | 8.46 Bn |
| 5 | General Mills | 18.09 Bn | 15.75 Bn | 1.49 Bn | 853.60 Mn |
| 6 | Mccormick | 13.03 Bn | 12.90 Bn | 778.20 Mn | 441.80 Mn |
| 7 | J M Smucker | 12.89 Bn | 12.68 Bn | 979.60 Mn | 411.10 Mn |
| 8 | Hormel Foods | 10.92 Bn | 7.61 Bn | 471.52 Mn | 323.50 Mn |
| 9 | Chewy | 7.33 Bn | 4.62 Bn | 1.01 Bn | 919.20 Mn |
| 10 | Tootsie Roll Industries | 2.85 Bn | 2.24 Bn | 52.63 Mn | 54.25 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 54.25 Mn |
| Mar 31, 2026 | 28.08 Mn |
| Dec 31, 2025 | 36.72 Mn |
| Sep 30, 2025 | 47.03 Mn |
| Jun 30, 2025 | 44.36 Mn |
| Mar 31, 2025 | 29.39 Mn |
| Dec 31, 2024 | 36.89 Mn |
| Sep 30, 2024 | 41.83 Mn |
| Jun 30, 2024 | 35.04 Mn |
| Mar 31, 2024 | 38.92 Mn |
| Dec 31, 2023 | 40.36 Mn |
| Sep 30, 2023 | 39.30 Mn |
| Jun 30, 2023 | 37.86 Mn |
| Mar 31, 2023 | 37.50 Mn |
| Dec 31, 2022 | 38.27 Mn |
| Sep 30, 2022 | 35.96 Mn |
| Jun 30, 2022 | 20.67 Mn |
| Mar 31, 2022 | 27.07 Mn |
| Dec 31, 2021 | 37.18 Mn |
| Sep 30, 2021 | 35.74 Mn |
API Access
Tootsie Roll Industries 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=TR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TR", "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=TR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();