Seapeak (SEAL-PA) Change in Accured Expenses (2009 - 2012)
Seapeak's Change in Accured Expenses came in at -$1.58 million for FY2015, compared with -$6.76 million in FY2014.
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Analysis
Seapeak (SEAL-PA) Change in Accured Expenses (2009 - 2012) Analysis & Trends
Going back to FY2009, Seapeak's Change in Accured Expenses data covers 7 years.
- The five-year range for annual Change in Accured Expenses is -$8.61 million (FY2012) to $8.07 million (FY2011).
- Per Business Quant, earlier years put Change in Accured Expenses at -$6.76 million in FY2014, $7.66 million in FY2013, -$8.61 million in FY2012 and $8.07 million in FY2011.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 165.28 Bn | 159.81 Bn | - | 187.00 Mn |
| 2 | Csx | 87.86 Bn | 84.08 Bn | - | - |
| 3 | Canadian Pacific Kansas City | 75.56 Bn | 75.27 Bn | - | - |
| 4 | Norfolk Southern | 71.27 Bn | 65.91 Bn | - | - |
| 5 | United Parcel Service | 69.70 Bn | 46.62 Bn | - | 147.00 Mn |
| 6 | Fedex | 68.71 Bn | 34.65 Bn | - | 1.21 Bn |
| 7 | Delta Air Lines | 55.32 Bn | 37.50 Bn | - | - |
| 8 | Old Dominion Freight Line | 37.44 Bn | 36.71 Bn | - | - |
| 9 | United Airlines Holdings | 36.52 Bn | -19.85 Bn | - | - |
| 10 | Seapeak | 2.21 Bn | 1.86 Bn | 152.57 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2012 | -6.48 Mn |
| Sep 30, 2012 | -2.25 Mn |
| Jun 30, 2012 | 3.99 Mn |
| Mar 31, 2012 | -3.87 Mn |
| Dec 31, 2011 | 10.22 Mn |
| Sep 30, 2011 | -2.33 Mn |
| Jun 30, 2011 | 3.05 Mn |
| Mar 31, 2011 | -2.86 Mn |
| Dec 31, 2010 | -4.94 Mn |
| Sep 30, 2010 | 3.92 Mn |
| Jun 30, 2010 | 1.39 Mn |
| Mar 31, 2010 | -3.62 Mn |
| Dec 31, 2009 | -4.02 Mn |
| Sep 30, 2009 | 1.47 Mn |
| Jun 30, 2009 | 1.83 Mn |
| Mar 31, 2009 | 2.52 Mn |
API Access
Seapeak Change in Accured 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=change-in-accured-expenses&ticker=SEAL-PA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "SEAL-PA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=SEAL-PA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();