Monster Beverage (MNST) Accumulated Expenses (2009 - 2026)
Monster Beverage (MNST) posted Accumulated Expenses of $335.53 million for Q2 2026, up 29.6% from $258.94 million a year earlier but down 15.5% from the prior quarter.
Monster Beverage (MNST) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Monster Beverage's Accumulated Expenses came in at $306.09 million, up 38.6% from FY2024.
- Annual Accumulated Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 16.5% (FY2020 to FY2025).
- In prior years, Monster Beverage's Accumulated Expenses was $220.76 million in FY2024 (+20.0%), $183.99 million in FY2023 (+6.4%), $172.99 million in FY2022 (-18.0%) and $210.96 million in FY2021 (+47.9%).
- Quarterly Accumulated Expenses has run from a low of $172.99 million in Q4 2022 to a high of $396.86 million in Q1 2026 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last nine quarters, with growth averaging 29.9% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q1 2026, with growth of 51.2%; the weakest was Q4 2022, with a decline of 18.0%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $396.86 million (Q1 2026), $306.09 million (Q4 2025) and $325.45 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Coca Cola | 395.83 Bn | 382.30 Bn | 8.42 Bn |
| 2 | Coca Cola Femsa Sab De Cv | 193.51 Bn | 193.51 Bn | 2.06 Bn |
| 3 | Pepsico | 175.42 Bn | 133.18 Bn | 13.75 Bn |
| 4 | Monster Beverage | 88.66 Bn | 76.91 Bn | 1.42 Bn |
| 5 | Diageo | 52.30 Bn | 32.37 Bn | - |
| 6 | Ambev | 50.76 Bn | 36.05 Bn | 2.06 Bn |
| 7 | Coca-Cola Europacific Partners | 50.09 Bn | 42.76 Bn | - |
| 8 | Keurig Dr Pepper | 46.34 Bn | 42.38 Bn | 3.07 Bn |
| 9 | Constellation Brands | 22.12 Bn | 21.67 Bn | 1.39 Bn |
| 10 | Coca-Cola Consolidated | 13.61 Bn | 11.24 Bn | 778.41 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 335.53 Mn |
| Mar 31, 2026 | 396.86 Mn |
| Dec 31, 2025 | 306.09 Mn |
| Sep 30, 2025 | 325.45 Mn |
| Jun 30, 2025 | 258.94 Mn |
| Mar 31, 2025 | 262.55 Mn |
| Dec 31, 2024 | 220.76 Mn |
| Sep 30, 2024 | 259.09 Mn |
| Jun 30, 2024 | 213.91 Mn |
| Mar 31, 2024 | 204.68 Mn |
| Dec 31, 2023 | 183.99 Mn |
| Sep 30, 2023 | 207.73 Mn |
| Jun 30, 2023 | 198.66 Mn |
| Mar 31, 2023 | 245.93 Mn |
| Dec 31, 2022 | 172.99 Mn |
| Sep 30, 2022 | 198.69 Mn |
| Dec 31, 2021 | 210.96 Mn |
| Sep 30, 2021 | 180.72 Mn |
| Jun 30, 2021 | 172.50 Mn |
| Mar 31, 2021 | 170.95 Mn |
Monster Beverage 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=MNST&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MNST", "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=MNST&period=max&api_key=YOUR_API_KEY");
const data = await res.json();