Light & Wonder (LAWIL) Change in Accured Expenses (2009 - 2016)
Light & Wonder's Change in Accured Expenses came in at $77.3 million for Q3 2016, up 183.2% from $27.3 million a year earlier.
Light & Wonder (LAWIL) Change in Accured Expenses (2009 - 2016) Analysis & Trends
Over the trailing twelve months to Sep 30, 2016, Light & Wonder reported Change in Accured Expenses of $68.7 million, up 141.9% year-over-year; for FY2015, it was $100,000, down 99.8% from FY2014.
- Change in Accured Expenses carries a five-year compound annual growth rate of -57.1% (FY2010 to FY2015).
- Going back by year, Change in Accured Expenses was $47 million in FY2014 (-10.6%), $52.6 million in FY2013, $1.5 million in FY2012 (-88.1%) and $12.6 million in FY2011 (+82.1%).
- The Q3 2016 figure represents the highest quarterly Change in Accured Expenses in data going back to Q3 2009.
- Year-over-year, Change in Accured Expenses increased in two of the last six quarters, with growth averaging 62.0%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q3 2015 (growth of 415.1%), and the weakest in Q1 2016 (a decline of 76.4%).
- Business Quant data shows LAWIL's Change in Accured Expenses at -$27.4 million (Q2 2016), $1.3 million (Q1 2016) and $17.5 million (Q4 2015) in the three quarters before Q3 2016.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Las Vegas Sands | 23.47 Bn | 9.89 Bn | 1.48 Bn | - |
| 2 | DraftKings | 16.53 Bn | 12.19 Bn | 551.45 Mn | -14.75 Mn |
| 3 | Flutter Entertainment | 12.99 Bn | 6.73 Bn | 1.71 Bn | - |
| 4 | Madison Square Garden Sports | 9.80 Bn | 9.40 Bn | 119.21 Mn | -72.25 Mn |
| 5 | Life Time Group Holdings | 9.15 Bn | 8.39 Bn | 412.26 Mn | - |
| 6 | Wynn Resorts | 7.85 Bn | 1.40 Bn | 758.95 Mn | 20.70 Mn |
| 7 | MGM Resorts International | 7.67 Bn | -517.04 Mn | 1.98 Bn | -19.98 Mn |
| 8 | Light & Wonder | 7.12 Bn | 6.43 Bn | 618.00 Mn | - |
| 9 | Caesars Entertainment | 6.04 Bn | 2.66 Bn | 1.50 Bn | 187.00 Mn |
| 10 | Super Group (SGHC) | 5.70 Bn | 3.69 Bn | - | - |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2016 | 77.30 Mn |
| Jun 30, 2016 | -27.40 Mn |
| Mar 31, 2016 | 1.30 Mn |
| Dec 31, 2015 | 17.50 Mn |
| Sep 30, 2015 | 27.30 Mn |
| Jun 30, 2015 | -50.20 Mn |
| Mar 31, 2015 | 5.50 Mn |
| Dec 31, 2014 | 45.80 Mn |
| Sep 30, 2014 | 5.30 Mn |
| Jun 30, 2014 | -23.40 Mn |
| Mar 31, 2014 | 19.30 Mn |
| Dec 31, 2013 | 55.00 Mn |
| Sep 30, 2013 | 12.70 Mn |
| Jun 30, 2013 | -1.50 Mn |
| Mar 31, 2013 | -13.60 Mn |
| Dec 31, 2012 | -2.33 Mn |
| Sep 30, 2012 | 12.95 Mn |
| Jun 30, 2012 | -3.15 Mn |
| Mar 31, 2012 | -5.97 Mn |
| Dec 31, 2011 | -2.07 Mn |
Light & Wonder 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=LAWIL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "LAWIL", "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=LAWIL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();