alpha-En (ALPE) Operating Expenses (2010 - 2023)
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Analysis
alpha-En (ALPE) Operating Expenses (2010 - 2023) Analysis & Trends
Peer Set
Peer Comparison
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | -3.07 Mn |
| Sep 30, 2019 | 1.24 Mn |
| Jun 30, 2019 | 1.40 Mn |
| Mar 31, 2019 | 1.21 Mn |
| Dec 31, 2018 | 902,000.00 |
| Sep 30, 2018 | 1.69 Mn |
| Jun 30, 2018 | 2.25 Mn |
| Mar 31, 2018 | 661,000.00 |
| Dec 31, 2017 | 2.16 Mn |
| Sep 30, 2017 | 2.36 Mn |
| Jun 30, 2017 | 701,000.00 |
| Mar 31, 2017 | 1.61 Mn |
| Dec 31, 2016 | 411,000.00 |
| Sep 30, 2016 | -249,000.00 |
| Jun 30, 2016 | 2.61 Mn |
| Mar 31, 2016 | 1.03 Mn |
| Dec 31, 2015 | 1.43 Mn |
| Sep 30, 2015 | 267,000.00 |
| Jun 30, 2015 | 84,000.00 |
| Mar 31, 2015 | 63,000.00 |
API Access
alpha-En Operating 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=operating-expenses&ticker=ALPE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ALPE", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=ALPE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();