Portillo's (PTLO) Accumulated Expenses (2020 - 2026)
Portillo's' Accumulated Expenses came in at $32.68 million for Q2 2026, up 6.3% from $30.73 million a year earlier but down 11.3% from the prior quarter.
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Analysis
Portillo's (PTLO) Accumulated Expenses (2020 - 2026) Analysis & Trends
At the end of FY2025, Portillo's' Accumulated Expenses was $32.24 million, down 2.5% from FY2024.
- Accumulated Expenses carries a five-year compound annual growth rate of -1.5% (FY2020 to FY2025).
- Going back by year, Accumulated Expenses was $33.07 million in FY2024 (+3.2%), $32.04 million in FY2023 (+7.1%), $29.92 million in FY2022 (+1.5%) and $29.47 million in FY2021 (-15.4%).
- The five-year range for quarterly Accumulated Expenses is $21.27 million (Q1 2022) to $37.12 million (Q3 2025).
- Year-over-year, Accumulated Expenses increased in seven of the last eight quarters, with growth averaging 6.5%.
- The fastest year-over-year change in Accumulated Expenses over five years came in Q3 2023 (growth of 43.4%), and the weakest in Q3 2022 (a decline of 30.5%).
- Business Quant data shows PTLO's Accumulated Expenses at $36.85 million (Q1 2026), $32.24 million (Q4 2025) and $37.12 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - |
| 10 | Portillo's | 268.03 Mn | 215.40 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 32.68 Mn |
| Mar 29, 2026 | 36.85 Mn |
| Dec 28, 2025 | 32.24 Mn |
| Sep 28, 2025 | 37.12 Mn |
| Jun 29, 2025 | 30.73 Mn |
| Mar 30, 2025 | 34.24 Mn |
| Dec 29, 2024 | 33.07 Mn |
| Sep 29, 2024 | 36.25 Mn |
| Jun 30, 2024 | 27.57 Mn |
| Mar 31, 2024 | 29.90 Mn |
| Dec 31, 2023 | 32.04 Mn |
| Sep 24, 2023 | 33.36 Mn |
| Jun 25, 2023 | 31.32 Mn |
| Mar 26, 2023 | 27.59 Mn |
| Dec 25, 2022 | 29.92 Mn |
| Sep 25, 2022 | 23.26 Mn |
| Jun 26, 2022 | 25.12 Mn |
| Mar 27, 2022 | 21.27 Mn |
| Dec 26, 2021 | 29.47 Mn |
| Sep 26, 2021 | 33.48 Mn |
API Access
Portillo's Accumulated 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=accumulated-expenses&ticker=PTLO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "PTLO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=PTLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();