I'm new to QuantConnect and still trying to figure out how things work here. I use to do a bit of research on Portfolio123 that involved backtesting fundamentals using their screening tool. I was hoping the friendly folks here could get me started in building a Python script that would essentially do the same thing here.
My old backtest involved the following:
- Benchmark to the S&P 500 Equal Weight index
- Eliminate OTC stocks
- Eliminate ADRs
- Exclude the financial sector
- Eliminate stocks with average daily trading volume under $100,000
- Market Capitalization greater than 50 million
- Closing price greater than $1
- Fundamental (such as PE) not missing
- Rank stocks by PE and select those that are in the best 20th percentile (lowest 20% PE in this example)
- Ideally, rebalance the portfolio every 52-weeks
- Test from 1998 to 2020
Rahul Chowdhury
Hey George,
You can use Universe Selection to filter stocks for various properties. I've written up something that filters for the properties you mentioned. Please checkout the Liquid Value bootcamp for more information on selecting assets based on fundamental data.
George Silva
Thank you! I appreciate the help getting me started on this and the link to the bootcamp. I'll be working on that lesson right away.
George Silva
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