Agree Realty (ADC) Property Operating Expenses (2010 - 2019)
Agree Realty (ADC) posted Property Operating Expenses of $1.74 million for Q1 2019, up 14.7% from $1.52 million a year earlier and unchanged from the prior quarter.
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Analysis
Agree Realty (ADC) Property Operating Expenses (2010 - 2019) Analysis & Trends
For the trailing twelve months through Mar 31, 2019, Property Operating Expenses at Agree Realty was $5.96 million, up 37.7% year-over-year; for FY2018, it came in at $5.65 million, up 56.4% from FY2017.
- Annual Property Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 36.5% (FY2013 to FY2018).
- In prior years, Agree Realty's Property Operating Expenses was $3.61 million in FY2017 (+45.3%), $2.48 million in FY2016 (+40.5%), $1.77 million in FY2015 (+5.3%) and $1.68 million in FY2014 (+40.8%).
- On a year-over-year basis, Property Operating Expenses has increased in each of the last seven quarters, with growth averaging 90.2% over the last eight quarters.
- The strongest year-over-year quarter for Property Operating Expenses in the past five years was Q3 2017, with growth of 450.9%; the weakest was Q3 2016, with a decline of 60.1%.
- According to Business Quant data, Property Operating Expenses for the three prior quarters was $1.74 million (Q4 2018), $1.25 million (Q3 2018) and $1.24 million (Q2 2018).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Property Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 179.03 Bn | 165.05 Bn | 1.47 Bn | - |
| 2 | Prologis | 123.12 Bn | 117.08 Bn | - | 511.72 Mn |
| 3 | Simon Property | 75.49 Bn | 71.55 Bn | - | 171.44 Mn |
| 4 | Public Storage | 62.37 Bn | 61.09 Bn | - | 333.19 Mn |
| 5 | Realty Income | 56.23 Bn | 54.51 Bn | - | 122.39 Mn |
| 6 | Ventas | 46.05 Bn | 44.73 Bn | - | 1.10 Bn |
| 7 | Extra Space Storage | 33.71 Bn | 32.62 Bn | 650.96 Mn | - |
| 8 | Vici Properties | 27.71 Bn | 26.06 Bn | 1.06 Bn | - |
| 9 | Vivmark Residential | 24.79 Bn | 24.57 Bn | - | 142.75 Mn |
| 10 | Agree Realty | 8.73 Bn | 8.60 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | 1.74 Mn |
| Dec 31, 2018 | 1.74 Mn |
| Sep 30, 2018 | 1.25 Mn |
| Jun 30, 2018 | 1.24 Mn |
| Mar 31, 2018 | 1.52 Mn |
| Dec 31, 2017 | 969,000.00 |
| Sep 30, 2017 | 931,000.00 |
| Jun 30, 2017 | 915,000.00 |
| Mar 31, 2017 | 797,000.00 |
| Dec 31, 2016 | 815,000.00 |
| Sep 30, 2016 | 169,000.00 |
| Jun 30, 2016 | 929,000.00 |
| Mar 31, 2016 | 573,000.00 |
| Dec 31, 2015 | 357,000.00 |
| Sep 30, 2015 | 424,000.00 |
| Jun 30, 2015 | 415,707.00 |
| Mar 31, 2015 | 571,390.00 |
| Dec 31, 2014 | 384,369.00 |
| Sep 30, 2014 | 337,811.00 |
| Jun 30, 2014 | 458,294.00 |
API Access
Agree Realty Property Operating 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=property-operating-expenses&ticker=ADC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-operating-expenses", "ticker": "ADC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=property-operating-expenses&ticker=ADC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();