Paychex (PAYX) Buildings (2010 - 2016)
Paychex's (PAYX) quarterly Buildings came in at $102.5 million in Q1 2016, up 0.59% year-over-year from $101.9 million in Q1 2015, and little changed quarter-over-quarter from $102.4 million in Q4 2015.
Paychex (PAYX) Buildings (2010 - 2016) Analysis & Trends
Paychex has disclosed Buildings across 7 years of filings, most recently posting $102.5 million for Q1 2016.
- In Q1 2016, Buildings rose 0.59% year-over-year to $102.5 million; the TTM figure through Feb 2016 stood at $102.5 million (up 0.59% YoY), while the FY2015 annual figure was $102.1 million, up 0.99% from the prior year.
- Buildings came in at $102.5 million for Q1 2016 at Paychex, roughly flat from $102.4 million in the prior quarter.
- In the past five years, Buildings ranged from a high of $102.5 million in Q1 2016 to a low of $95.7 million in Q1 2012.
- Average Buildings over 5 years is $100.2 million, with a median of $100.8 million recorded in 2014.
- Year-over-year, Buildings grew 2.82% in 2013 and increased 0.59% in 2016.
- Over 5 years, Buildings stood at $98.1 million in 2012, then increased by 2.55% to $100.6 million in 2013, then gained by 0.89% to $101.5 million in 2014, then gained by 0.89% to $102.4 million in 2015, then gained by 0.1% to $102.5 million in 2016.
- Per Business Quant data, the three most recent Buildings figures were $102.5 million in Q1 2016, $102.4 million in Q4 2015, and $102.4 million in Q3 2015.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 460.85 Bn | 451.55 Bn | 1.64 Bn |
| 2 | Oracle | 437.09 Bn | 400.44 Bn | - |
| 3 | Sap Se | 258.74 Bn | 237.66 Bn | 8.40 Bn |
| 4 | Salesforce | 195.52 Bn | 184.12 Bn | 8.70 Bn |
| 5 | ServiceNow | 145.61 Bn | 140.94 Bn | 2.82 Bn |
| 6 | Automatic Data Processing | 104.89 Bn | 100.66 Bn | 2.51 Bn |
| 7 | Intuit | 76.97 Bn | 69.77 Bn | 3.46 Bn |
| 8 | Relx | 60.41 Bn | 60.04 Bn | - |
| 9 | Strategy | 57.09 Bn | 54.64 Bn | 81.55 Mn |
| 10 | Paychex | 37.16 Bn | 36.02 Bn | 1.19 Bn |
Historic Data
| Date | Value |
|---|---|
| Feb 29, 2016 | 102.50 Mn |
| Nov 30, 2015 | 102.40 Mn |
| Aug 31, 2015 | 102.40 Mn |
| May 31, 2015 | 102.10 Mn |
| Feb 28, 2015 | 101.90 Mn |
| Nov 30, 2014 | 101.50 Mn |
| Aug 31, 2014 | 101.20 Mn |
| May 31, 2014 | 101.10 Mn |
| Feb 28, 2014 | 100.80 Mn |
| Nov 30, 2013 | 100.60 Mn |
| Aug 31, 2013 | 100.30 Mn |
| May 31, 2013 | 99.20 Mn |
| Feb 28, 2013 | 98.40 Mn |
| Nov 30, 2012 | 98.10 Mn |
| Aug 31, 2012 | 97.80 Mn |
| May 31, 2012 | 96.80 Mn |
| Feb 29, 2012 | 95.70 Mn |
| Nov 30, 2011 | 95.60 Mn |
| Aug 31, 2011 | 95.30 Mn |
| May 31, 2011 | 95.20 Mn |
Paychex Buildings 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=buildings&ticker=PAYX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "buildings", "ticker": "PAYX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=buildings&ticker=PAYX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();