Summit Hotel Properties (INN) Accumulated Expenses (2012 - 2026)
Summit Hotel Properties (INN) posted Accumulated Expenses of $72.34 million for Q3 2020, down 14.8% from $84.92 million a year earlier but up 6.1% from the prior quarter.
Summit Hotel Properties (INN) Accumulated Expenses (2012 - 2026) Analysis & Trends
At the end of FY2019, Summit Hotel Properties' Accumulated Expenses came in at $71.76 million, up 8.6% from FY2018.
- Annual Accumulated Expenses has increased for seven consecutive years, with a five-year compound annual growth rate of 13.5% (FY2014 to FY2019).
- In prior years, Summit Hotel Properties' Accumulated Expenses was $66.05 million in FY2018 (+16.9%), $56.49 million in FY2017 (+20.5%), $46.88 million in FY2016 (+11.2%) and $42.17 million in FY2015 (+10.8%).
- Quarterly Accumulated Expenses has run from a low of $42.17 million in Q4 2015 to a high of $84.92 million in Q3 2019 over five years.
- On a year-over-year basis, Accumulated Expenses increased in six of the last eight quarters, with growth averaging 8.2%.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q2 2018, with growth of 29.3%; the weakest was Q3 2020, with a decline of 14.8%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $68.2 million (Q2 2020), $76.1 million (Q1 2020) and $71.76 million (Q4 2019).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Welltower | 181.70 Bn | 168.77 Bn | 1.47 Bn |
| 2 | Prologis | 123.65 Bn | 122.03 Bn | - |
| 3 | Simon Property | 80.48 Bn | 78.58 Bn | - |
| 4 | Public Storage | 62.76 Bn | 62.20 Bn | 112.08 Mn |
| 5 | Realty Income | 56.61 Bn | 57.99 Bn | - |
| 6 | Ryman Hospitality Properties | 47.80 Bn | 46.64 Bn | 266.41 Mn |
| 7 | Ventas | 47.78 Bn | 46.95 Bn | -3.39 Bn |
| 8 | Vivmark Residential | 38.23 Bn | 37.98 Bn | - |
| 9 | Extra Space Storage | 33.20 Bn | 32.98 Bn | 650.96 Mn |
| 10 | Summit Hotel Properties | 801.35 Mn | 969.71 Mn | 77.91 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 94.46 Mn |
| Jun 30, 2026 | 83.62 Mn |
| Mar 31, 2026 | 77.68 Mn |
| Dec 31, 2025 | 76.42 Mn |
| Sep 30, 2025 | 92.91 Mn |
| Jun 30, 2025 | 81.14 Mn |
| Mar 31, 2025 | 78.59 Mn |
| Dec 31, 2024 | 82.15 Mn |
| Sep 30, 2024 | 96.68 Mn |
| Jun 30, 2024 | 84.41 Mn |
| Mar 31, 2024 | 81.72 Mn |
| Dec 31, 2023 | 81.22 Mn |
| Sep 30, 2023 | 92.21 Mn |
| Jun 30, 2023 | 88.78 Mn |
| Mar 31, 2023 | 86.50 Mn |
| Dec 31, 2022 | 81.30 Mn |
| Sep 30, 2022 | 94.62 Mn |
| Jun 30, 2022 | 85.80 Mn |
| Mar 31, 2022 | 75.70 Mn |
| Dec 31, 2021 | 66.22 Mn |
Summit Hotel Properties 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=INN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "INN", "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=INN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();