I have this theory that high growth companies keep returning to the 4 years daily mean of (Today's Revenue) / (Share Price) and the rest of the fundamentals is noise in the long term. I checked the theory manually in Google Sheets and there are a lot of positive signs, but it needs proper backtesting on Quantopian.
Here are some screenshots from the Google Sheets:
https://i.imgur.com/HPaR7dk.png
https://i.imgur.com/vYEctfo.png
By high growth companies I mean:
- TSLA -- 15.10% (avg QoQ growth)
- FB -- 11.20%
- BABA -- 10.30%
- TCEHY -- 8.60%
- GOOGL -- 6.80%
- NFLX -- 6.80%
- AMZN -- 6.50%
- ADBE -- 5.60%
- SBUX -- 3.30%
It's quite easy to estimate what each of those companies will do in any particular day, based on the last X number of quarters of information. On significant deviations from the daily mean, for example, lower 20% percentile or higher 80% percentile - we can buy/sell those stocks. Also, we will continuously rebalance. In case that all stocks are "overpriced" - we should buy some SPXS while keeping most of the cash available.
Is there an algorithm similar to this? I can make code small changes, but building from scratch seems unfeasible to me so far...