Mcdonalds (MCD) EV to EBITDA (2009 - 2026)
Mcdonalds' (MCD) quarterly EV to EBITDA came in at 57.06 in Q2 2026, down 10.75% on a YoY basis from 63.93 in Q2 2025, and down 23.29% quarter-over-quarter from 74.38 in Q1 2026.
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Mcdonalds (MCD) EV to EBITDA (2009 - 2026) Analysis & Trends
Mcdonalds (MCD) has reported EV to EBITDA for 18 consecutive years, with 57.06 the latest figure, recorded in Q2 2026.
- For the quarter ending Q2 2026, EV to EBITDA fell 10.75% year-over-year to 57.06; the trailing twelve-month figure through Jun 2026 stood at 14.88 (down 14.07% YoY), and the FY2025 full-year result was 15.46, down 0.85% from the prior year.
- EV to EBITDA fell to 57.06 in Q2 2026 per MCD's latest filing, from 74.38 in the prior quarter.
- Across five years, EV to EBITDA topped out at 105.01 in Q2 2022 and bottomed at 57.06 in Q2 2026.
- Historically, EV to EBITDA has averaged 71.47 across 5 years, with a median of 70.69 in 2023.
- The sharpest annual moves came in 2022 and 2023: EV to EBITDA jumped 66.77% in 2022, then tumbled 33.78% in 2023.
- Over 5 years, EV to EBITDA stood at 73.64 in 2022, then advanced by 1.54% to 74.77 in 2023, then slipped by 3.93% to 71.84 in 2024, then decreased by 4.58% to 68.55 in 2025, then dropped by 16.76% to 57.06 in 2026.
- According to Business Quant data, EV to EBITDA over the past three periods registered 57.06, 74.38, and 68.55 for Q2 2026, Q1 2026, and Q4 2025 respectively.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 168.67 Bn | 167.85 Bn | 6.42 Bn |
| 2 | Starbucks | 107.32 Bn | 103.72 Bn | 6.49 Bn |
| 3 | Chipotle Mexican Grill | 41.40 Bn | 40.73 Bn | 2.35 Bn |
| 4 | Yum Brands | 38.39 Bn | 37.72 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 25.02 Bn | 25.51 Bn | 1.89 Bn |
| 6 | Darden Restaurants | 24.39 Bn | 24.17 Bn | 3.68 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 15.95 Bn | 1.89 Bn |
| 8 | Yum China Holdings | 14.09 Bn | 13.41 Bn | 2.22 Bn |
| 9 | Texas Roadhouse | 10.81 Bn | 10.63 Bn | 1.44 Bn |
| 10 | Dominos Pizza | 9.81 Bn | 9.60 Bn | 478.23 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 57.06 |
| Mar 31, 2026 | 74.38 |
| Dec 31, 2025 | 68.55 |
| Sep 30, 2025 | 63.75 |
| Jun 30, 2025 | 63.93 |
| Mar 31, 2025 | 83.88 |
| Dec 31, 2024 | 71.84 |
| Sep 30, 2024 | 68.07 |
| Jun 30, 2024 | 62.33 |
| Mar 31, 2024 | 73.96 |
| Dec 31, 2023 | 74.77 |
| Sep 30, 2023 | 58.48 |
| Jun 30, 2023 | 69.54 |
| Mar 31, 2023 | 79.16 |
| Dec 31, 2022 | 73.64 |
| Sep 30, 2022 | 60.12 |
| Jun 30, 2022 | 105.01 |
| Mar 31, 2022 | 78.07 |
| Dec 31, 2021 | 81.19 |
| Sep 30, 2021 | 58.89 |
API Access
Mcdonalds EV to EBITDA 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=ev-to-ebitda&ticker=MCD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "MCD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=MCD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();