Mondelez International (MDLZ) Land & Improvements (2009 - 2011)
Mondelez International's Land & Improvements was $782 million in Q3 2011, down 4.9% from the prior quarter.
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Analysis
Mondelez International (MDLZ) Land & Improvements (2009 - 2011) Analysis & Trends
At the end of FY2010, Land & Improvements at Mondelez International came in at $795 million, up 61.6% from FY2009.
- In earlier years, Land & Improvements was $492 million in FY2009.
- The Q3 2011 figure marks the lowest quarterly Land & Improvements since Q2 2010.
- Per Business Quant data, MDLZ's Land & Improvements in the three quarters before Q3 2011 was $822 million (Q2 2011), $814 million (Q1 2011) and $795 million (Q4 2010).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Land & Improvements (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 132.43 Bn | 107.80 Bn | - | - |
| 2 | Mondelez International | 73.80 Bn | 67.12 Bn | 3.99 Bn | - |
| 3 | Hershey | 31.86 Bn | 28.11 Bn | 1.26 Bn | 195.99 Mn |
| 4 | Kraft Heinz | 26.96 Bn | 13.49 Bn | 2.03 Bn | - |
| 5 | General Mills | 17.20 Bn | 14.85 Bn | 1.49 Bn | - |
| 6 | J M Smucker | 12.70 Bn | 12.49 Bn | 979.60 Mn | 158.50 Mn |
| 7 | Mccormick | 12.49 Bn | 12.36 Bn | 778.20 Mn | - |
| 8 | Hormel Foods | 10.97 Bn | 7.66 Bn | 471.52 Mn | 75.32 Mn |
| 9 | Chewy | 7.31 Bn | 4.59 Bn | 1.01 Bn | - |
| 10 | Conagra Brands | 6.43 Bn | 5.74 Bn | 618.70 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2011 | 782.00 Mn |
| Jun 30, 2011 | 822.00 Mn |
| Mar 31, 2011 | 814.00 Mn |
| Dec 31, 2010 | 795.00 Mn |
| Jun 30, 2010 | 714.00 Mn |
| Dec 31, 2009 | 492.00 Mn |
API Access
Mondelez International Land & Improvements 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=land-and-improvements&ticker=MDLZ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "land-and-improvements", "ticker": "MDLZ", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=land-and-improvements&ticker=MDLZ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();