Noodles (NDLS) Exchange Rate Effect (2015 - 2018)
Noodles (NDLS) reported Exchange Rate Effect of -$11,000 for Q4 2018, compared with -$1,000 a year earlier.
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Analysis
Noodles (NDLS) Exchange Rate Effect (2015 - 2018) Analysis & Trends
For FY2018, Noodles posted Exchange Rate Effect of -$15,000.
- By year, Exchange Rate Effect came in at $41,000 in FY2017 and -$134,000 in FY2015.
- The Q4 2018 figure ranks as the lowest quarterly Exchange Rate Effect since Q3 2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 165.62 Bn | 160.44 Bn | 6.42 Bn | 99.00 Mn |
| 2 | Starbucks | 108.79 Bn | 96.42 Bn | - | -6.20 Mn |
| 3 | Chipotle Mexican Grill | 40.35 Bn | 36.33 Bn | - | 98,000.00 |
| 4 | Yum Brands | 37.59 Bn | 34.48 Bn | 1.47 Bn | -9.00 Mn |
| 5 | Restaurant Brands International | 24.96 Bn | 22.07 Bn | 1.38 Bn | -5.00 Mn |
| 6 | Darden Restaurants | 22.28 Bn | 21.39 Bn | -113.70 Mn | - |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | -5.00 Mn |
| 8 | Yum China Holdings | 14.08 Bn | 8.44 Bn | 537.00 Mn | 4.00 Mn |
| 9 | Texas Roadhouse | 10.31 Bn | 9.67 Bn | - | - |
| 10 | Noodles | 82.34 Mn | 73.64 Mn | 90.30 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jan 2, 2018 | -11,000.00 |
| Oct 3, 2017 | -6,000.00 |
| Jul 4, 2017 | 2,000.00 |
| Jan 3, 2017 | -1,000.00 |
| Sep 27, 2016 | -85,000.00 |
| Jun 28, 2016 | 22,000.00 |
| Mar 29, 2016 | 105,000.00 |
| Dec 29, 2015 | -42,000.00 |
| Sep 29, 2015 | -80,000.00 |
| Jun 30, 2015 | -12,000.00 |
API Access
Noodles Exchange Rate Effect 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=exchange-rate-effect&ticker=NDLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "ticker": "NDLS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=exchange-rate-effect&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();