Getting Earnings Calendars for trading.
Company Earnings is one of the key parameters that investors commonly use to assess a stock or company because it shows how profitable a company is on a per-share basis.
EPS (Earnings per share) is calculated by subtracting any preferred dividends from a company's net income and dividing that amount by the number of shares outstanding.
To trace EPS and keep up with profitable decisions the option of having Earnings Calendar is really handy feature for prosperous investments.
The common source of market information is NASDAQ - National Association of Securities Dealers Automated Quotation.
In our case we will use very handy Python package finance_calendars - a simple wrapper of NASDAQ public API for Financial Calendars.
Using simple scripts below you will get all the necessary information on Earnings data for current day as well as historical information on any chosen date.
Output data is in Pandas dataframe format which can be easily converted to any suitable form for further visualisation and analysis.
Python code to extract earnings reports due on today's date:
# pip install finance-calendars
from finance_calendars import finance_calendars as fc
from datetime import datetime, date
import pandas as pd
earnings =fc.get_earnings_today()
print(earnings[:5])
# only 5 items listed, remove filter to get all data
Earnings reports due on today's date output:
Python code to get earnings reports due on the specified date:
earnings = fc.get_earnings_by_date(datetime(2022, 9, 26, 0, 0))
print(earnings[:5])
# only 5 items listed, remove filter to get all data
Earnings on the specified date output:
