Papa Johns International (PZZA) Change in Accured Expenses (2009 - 2026)
Papa Johns International (PZZA) posted Change in Accured Expenses of $6.76 million for Q2 2026, up 160.5% from $2.6 million a year earlier.
Papa Johns International (PZZA) Change in Accured Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 28, 2026, Change in Accured Expenses at Papa Johns International was -$4.41 million; for FY2025, it was $6.96 million.
- Annual Change in Accured Expenses shows a five-year compound annual growth rate of -34.9% (FY2020 to FY2025).
- In prior years, Papa Johns International's Change in Accured Expenses was -$2.04 million in FY2024, $18.31 million in FY2023 (+261.7%), $5.06 million in FY2022 (-68.1%) and $15.88 million in FY2021 (-73.3%).
- Quarterly Change in Accured Expenses has run from a low of -$29.47 million in Q1 2022 to a high of $37.47 million in Q4 2022 over five years.
- On a year-over-year basis, Change in Accured Expenses increased in three of the last five quarters, with growth averaging 43.3%.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q3 2025, with growth of 160.9%; the weakest was Q4 2024, with a decline of 69.8%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was -$27.45 million (Q1 2026), $9.05 million (Q4 2025) and $7.23 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (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 | - | 100.69 Mn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 4.00 Mn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | -8.00 Mn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 32.50 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | -8.00 Mn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 107.00 Mn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 15.18 Mn |
| 10 | Papa Johns International | 648.56 Mn | 515.89 Mn | 143.37 Mn | 6.76 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 6.76 Mn |
| Mar 29, 2026 | -27.45 Mn |
| Dec 28, 2025 | 9.05 Mn |
| Sep 28, 2025 | 7.23 Mn |
| Jun 29, 2025 | 2.60 Mn |
| Mar 30, 2025 | -11.91 Mn |
| Dec 29, 2024 | 7.52 Mn |
| Sep 29, 2024 | 2.77 Mn |
| Jun 30, 2024 | 5.85 Mn |
| Mar 31, 2024 | -18.17 Mn |
| Dec 31, 2023 | 24.89 Mn |
| Sep 24, 2023 | -13.78 Mn |
| Jun 25, 2023 | 12.62 Mn |
| Mar 26, 2023 | -5.41 Mn |
| Dec 25, 2022 | 37.47 Mn |
| Sep 25, 2022 | 5.05 Mn |
| Jun 26, 2022 | -7.99 Mn |
| Mar 27, 2022 | -29.47 Mn |
| Dec 26, 2021 | -8.13 Mn |
| Sep 26, 2021 | 11.88 Mn |
Papa Johns International Change in Accured 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=change-in-accured-expenses&ticker=PZZA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "PZZA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=PZZA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();