Donnelley Financial Solutions (DFIN) Finished Goods (2015 - 2017)
Donnelley Financial Solutions' Finished Goods came in at $6.3 million for Q4 2017, up 10.5% from $5.7 million a year earlier and up 8.6% from the prior quarter.
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Analysis
Donnelley Financial Solutions (DFIN) Finished Goods (2015 - 2017) Analysis & Trends
Going back to Q4 2015, Donnelley Financial Solutions' Finished Goods data covers 7 quarters.
- Going back by year, Finished Goods was $5.7 million in FY2016 (+23.9%) and $4.6 million in FY2015.
- The five-year range for quarterly Finished Goods is $4.6 million (Q4 2015) to $7.2 million (Q2 2017).
- Business Quant data shows DFIN's Finished Goods at $5.8 million (Q3 2017), $7.2 million (Q2 2017) and $6.5 million (Q1 2017) in the three quarters before Q4 2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 473.66 Bn | 442.61 Bn | 1.64 Bn |
| 2 | Oracle | 385.52 Bn | 257.65 Bn | - |
| 3 | Sap Se | 270.68 Bn | 198.46 Bn | 8.40 Bn |
| 4 | Salesforce | 197.54 Bn | 153.41 Bn | 8.70 Bn |
| 5 | ServiceNow | 157.06 Bn | 135.52 Bn | 2.82 Bn |
| 6 | Automatic Data Processing | 118.45 Bn | 100.57 Bn | 2.51 Bn |
| 7 | Intuit | 92.02 Bn | 71.37 Bn | 3.44 Bn |
| 8 | Relx | 72.92 Bn | 72.01 Bn | - |
| 9 | Strategy | 52.15 Bn | 45.13 Bn | 81.55 Mn |
| 10 | Donnelley Financial Solutions | 1.34 Bn | 1.24 Bn | 148.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2017 | 6.30 Mn |
| Sep 30, 2017 | 5.80 Mn |
| Jun 30, 2017 | 7.20 Mn |
| Mar 31, 2017 | 6.50 Mn |
| Dec 31, 2016 | 5.70 Mn |
| Sep 30, 2016 | 5.80 Mn |
| Dec 31, 2015 | 4.60 Mn |
API Access
Donnelley Financial Solutions Finished Goods 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=finished-goods&ticker=DFIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "finished-goods", "ticker": "DFIN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=finished-goods&ticker=DFIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();