This repository contains code and files for the creation of a value investing screener using web scraping.
The code takes two .csv files containing tickers traded in the NASDAQ and the NYSE. You can download and put them in the working directory; here the links:
- NYSE http://www.nasdaq.com/screening/companies-by-industry.aspx?exchange=NYSE&render=download
- NASDAQ http://www.nasdaq.com/screening/companies-by-industry.aspx?exchange=NASDAQ&render=download
The .csv files should be replaced with updated ones whenever you want, as new IPOs take place or firms are delisted during time.
The code scrapes data from the https://www.gurufocus.com/ website for every ticker found. The process uses regular expressions to locate the numbers. Before running the code you should install the packages required. Download the requirements.txt in the repo in your local directory and run this in your terminal
pip install -r /path/to/requirements.txt
For each ticker, the code downloads (if available):
- Stock price
- ROIC (in %)
- Owner Earnings per Share
- 10y, 5y Revenue Growth
- 10y, 5y EPS Growth
- 10y, 5y Ebit Growth
- 10y, 5y Ebitda Growth
- 10y, 5y Free Cash Flow Growth
- 10y, 5y Dividend Growth
- 10y, 5y BV Growth
- 10y, 5y Stock Price Growth
- Ten Cap Valuation (computed)
The output is a pandas dataframe which is exported as a .csv file in your working directory. Here's a simple screenshot:
I have made the work available to everyone, feel free to share, improve and commit to it. Inside the code you will find some #TODO which I wanted to implement.
Hope you will enjoy it and find it useful as much as I did.