Cheesecake Factory (CAKE) Cash & Equivalents (2009 - 2026)
Cheesecake Factory (CAKE) recorded Cash & Equivalents of $195.17 million in Q2 2026, up 31.2% from $148.76 million a year earlier but down 17.0% from the prior quarter.
Cheesecake Factory (CAKE) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2025, Cheesecake Factory reported Cash & Equivalents of $215.73 million, up 156.3% from FY2024.
- Annual Cash & Equivalents has a five-year compound annual growth rate of 7.0% (FY2020 to FY2025).
- Across earlier years, Cash & Equivalents came in at $84.18 million in FY2024 (+49.5%), $56.29 million in FY2023 and $189.63 million in FY2021 (+23.1%).
- Quarterly Cash & Equivalents has ranged from $40.65 million in Q2 2024 to $235.09 million in Q1 2026 over the past five years.
- On a year-over-year basis, Cash & Equivalents has increased for seven consecutive quarters, with growth averaging 137.9% over the last seven quarters.
- Peak year-over-year performance for Cash & Equivalents in the last five years was growth of 265.9% in Q2 2025, against a decline of 46.2% in Q3 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $235.09 million (Q1 2026), $215.73 million (Q4 2025) and $189.98 million (Q3 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 | 110.34 Bn | 97.96 Bn | - | 3.45 Bn |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | 674.00 Mn |
| 4 | Chipotle Mexican Grill | 39.00 Bn | 34.98 Bn | - | 228.20 Mn |
| 5 | Restaurant Brands International | 25.80 Bn | 21.35 Bn | 1.38 Bn | 1.06 Bn |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 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 | 15.57 Bn | 9.23 Bn | 537.00 Mn | 485.00 Mn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 202.43 Mn |
| 10 | Cheesecake Factory | 5.44 Bn | 4.61 Bn | - | 195.17 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 195.17 Mn |
| Mar 31, 2026 | 235.09 Mn |
| Dec 30, 2025 | 215.73 Mn |
| Sep 30, 2025 | 189.98 Mn |
| Jul 1, 2025 | 148.76 Mn |
| Apr 1, 2025 | 135.41 Mn |
| Dec 31, 2024 | 84.18 Mn |
| Oct 1, 2024 | 52.22 Mn |
| Jul 2, 2024 | 40.65 Mn |
| Apr 2, 2024 | 60.22 Mn |
| Jan 2, 2024 | 56.29 Mn |
| Oct 3, 2023 | 63.99 Mn |
| Jul 4, 2023 | 91.56 Mn |
| Apr 4, 2023 | 116.16 Mn |
| Jan 3, 2023 | 114.78 Mn |
| Sep 27, 2022 | 133.16 Mn |
| Jun 28, 2022 | 194.89 Mn |
| Mar 29, 2022 | 183.56 Mn |
| Dec 28, 2021 | 189.63 Mn |
| Sep 28, 2021 | 131.03 Mn |
Cheesecake Factory 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=CAKE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "CAKE", "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=CAKE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();