Starbucks (SBUX) Cash & Equivalents (2009 - 2026)
Starbucks (SBUX) recorded Cash & Equivalents of $3.45 billion in fiscal Q3 2026 (quarter ended Jun 28, 2026), down 17.3% from $4.17 billion a year earlier but up 125.2% from the prior quarter.
Starbucks (SBUX) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 28, 2025), Starbucks reported Cash & Equivalents of $3.22 billion, down 2.0% from FY2024.
- Annual Cash & Equivalents has a five-year compound annual growth rate of -5.8% (FY2020 to FY2025).
- Across earlier fiscal years, Cash & Equivalents came in at $3.29 billion in FY2024 (-7.5%), $3.55 billion in FY2023 (+26.0%), $2.82 billion in FY2022 (-56.3%) and $6.46 billion in FY2021 (+48.4%).
- Quarterly Cash & Equivalents has ranged from $1.53 billion in fiscal Q2 2026 to $6.46 billion in fiscal Q4 2021 over the past five years.
- On a year-over-year basis, Cash & Equivalents has declined for four consecutive quarters, with an average decline of 3.3% over the last eight quarters.
- Peak year-over-year performance for Cash & Equivalents in the last five years was growth of 48.4% in fiscal Q4 2021, against a decline of 56.3% in fiscal Q4 2022 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $1.53 billion (Q2 2026), $3.41 billion (Q1 2026) and $3.22 billion (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.96 Bn | 166.78 Bn | 6.42 Bn | 822.00 Mn |
| 2 | Starbucks | 109.62 Bn | 97.24 Bn | - | 3.45 Bn |
| 3 | Yum Brands | 41.39 Bn | 38.27 Bn | 1.47 Bn | 674.00 Mn |
| 4 | Chipotle Mexican Grill | 39.36 Bn | 35.34 Bn | - | 228.20 Mn |
| 5 | Restaurant Brands International | 25.77 Bn | 21.33 Bn | 1.38 Bn | 1.06 Bn |
| 6 | Darden Restaurants | 24.33 Bn | 23.43 Bn | 1.68 Bn | 220.50 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.06 Bn |
| 8 | Yum China Holdings | 15.61 Bn | 9.27 Bn | 537.00 Mn | 485.00 Mn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 202.43 Mn |
| 10 | Luckin Coffee | 10.66 Bn | 9.74 Bn | - | 327.91 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 3.45 Bn |
| Mar 29, 2026 | 1.53 Bn |
| Dec 28, 2025 | 3.41 Bn |
| Sep 28, 2025 | 3.22 Bn |
| Jun 29, 2025 | 4.17 Bn |
| Mar 30, 2025 | 2.67 Bn |
| Dec 29, 2024 | 3.67 Bn |
| Sep 29, 2024 | 3.29 Bn |
| Jun 30, 2024 | 3.18 Bn |
| Mar 31, 2024 | 2.76 Bn |
| Dec 31, 2023 | 3.00 Bn |
| Oct 1, 2023 | 3.55 Bn |
| Jul 2, 2023 | 3.36 Bn |
| Apr 2, 2023 | 3.07 Bn |
| Jan 1, 2023 | 3.19 Bn |
| Oct 2, 2022 | 2.82 Bn |
| Jul 3, 2022 | 3.18 Bn |
| Apr 3, 2022 | 3.91 Bn |
| Jan 2, 2022 | 3.97 Bn |
| Oct 3, 2021 | 6.46 Bn |
Starbucks Cash & Equivalents 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=cash-and-equivalents&ticker=SBUX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "SBUX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=cash-and-equivalents&ticker=SBUX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();