Value investing has become increasingly popular among individual investors in recent years. The core principle of value investing is to identify and invest in undervalued stocks that are trading below their intrinsic value. Github, as one of the largest open source code repositories, offers a treasure trove of resources for beginners who want to learn deep value investing strategies. This article will provide an overview of how to find free deep value investing strategies and stock screeners on Github for beginners.
Search Github directly for ‘value investing strategy’
The most straightforward way is to directly search Github using keywords like ‘value investing strategy’, ‘deep value investing’, or ‘magic formula investing’. Sort the results by number of stars to surface the most popular repositories. For example, the repository ‘Value-Investing-Strategy’ by author ‘vikingInvestments’ provides a complete stock screening and value investing analysis template in Python. It covers steps from retrieving financial data to calculating valuation ratios and identifying undervalued stocks. The readme file gives a good tutorial for beginners to follow along.
Look for repositories of famous value investors
Another approach is to search for repositories created by well-known deep value investors. For example, Mohnish Pabrai is an influential value investor with great resources on Github. His ‘Dhandho Investor’ book code repository provides a full example screening for stocks based on the Pabrai Funds investment framework. The Python notebook covers data extraction, filtering for value criteria like low P/B and P/E, high ROIC, and qualitative checks. The screener is a great template for beginners to model after.
Search within popular algorithmic trading frameworks
Since value investing relies heavily on quantitative screening, many repositories contain value strategy implementations within broader algorithmic trading systems. For example, the library ‘pandas-ta’ offers 130+ technical analysis indicators that can be used for value factor screening. Within the library example scripts, there are notebooks covering value strategies like Greenblatt’s Magic Formula. The ‘backtrader’ Python backtesting framework also has value strategy examples among its community strategies. Exploring within these algorithmic trading projects can uncover reusable code snippets for value investing.
Join value investing online communities
Lastly, an effective way to find more Github resources is to join online communities dedicated to value investing. Subreddits like r/ValueInvesting often share interesting GitHub repositories for value strategies. The forum posts can point beginners directly to vetted open source projects instead of aimless searching. Community members may also provide assistance for customizing and improving existing value investing code bases. Apart from Reddit, platforms like Value Investors Club and GuruFocus Forums are great places to discover new Github projects mentioned by experienced value investors.
In summary, Github is home to many high quality open source resources for learning deep value investing strategies as a beginner. The key is to utilize effective search techniques, look to resources from well-known practitioners, explore within algorithmic trading projects, and join value investing communities. By fully taking advantage of what Github has to offer, beginners can level up their value investing knowledge and skills with practical code examples.