Tilly'S (TLYS) Operating Expenses (2011 - 2026)
Tilly'S's Operating Expenses came in at $49.92 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 7.5% from $46.42 million a year earlier and up 13.0% from the prior quarter.
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Analysis
Tilly'S (TLYS) Operating Expenses (2011 - 2026) Analysis & Trends
Over the trailing twelve months to Aug 1, 2026, Tilly'S reported Operating Expenses of $187.5 million, down 3.4% year-over-year; for FY2026 (ended Jan 31, 2026), it was $183.81 million, down 7.9% from FY2025.
- Operating Expenses carries a five-year compound annual growth rate of 4.8% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $199.55 million in FY2025 (+1.5%), $196.64 million in FY2024 (+2.7%), $191.56 million in FY2023 (+1.3%) and $189.07 million in FY2022 (+30.2%).
- The fiscal Q2 2027 figure represents the highest quarterly Operating Expenses since fiscal Q4 2025.
- Year-over-year, Operating Expenses increased in two of the last eight quarters, with an average decline of 3.5%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q3 2022 (growth of 28.6%), and the weakest in fiscal Q3 2026 (a decline of 13.2%).
- Business Quant data shows TLYS's Operating Expenses at $44.17 million (Q1 2027), $48.9 million (Q4 2026) and $44.51 million (Q3 2026) in the three fiscal quarters before Q2 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Tilly'S | 144.91 Mn | -43.76 Mn | 58.10 Mn | 49.92 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 49.92 Mn |
| May 2, 2026 | 44.17 Mn |
| Jan 31, 2026 | 48.90 Mn |
| Nov 1, 2025 | 44.51 Mn |
| Aug 2, 2025 | 46.42 Mn |
| May 3, 2025 | 43.97 Mn |
| Feb 1, 2025 | 52.42 Mn |
| Nov 2, 2024 | 51.25 Mn |
| Aug 3, 2024 | 50.78 Mn |
| May 4, 2024 | 45.10 Mn |
| Feb 3, 2024 | 55.20 Mn |
| Oct 28, 2023 | 51.24 Mn |
| Jul 29, 2023 | 47.00 Mn |
| Apr 29, 2023 | 43.20 Mn |
| Jan 28, 2023 | 53.76 Mn |
| Oct 29, 2022 | 48.27 Mn |
| Jul 30, 2022 | 46.83 Mn |
| Apr 30, 2022 | 42.71 Mn |
| Jan 29, 2022 | 53.06 Mn |
| Oct 30, 2021 | 47.74 Mn |
API Access
Tilly'S 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=TLYS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TLYS", "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=TLYS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();