Once I got my Stock Prediction based on Annual (10-K) and Quarterly (10-Q) statement model working, I just wasn't happy with the R-squared on it. And I didn't feel comfortable investing in the picks it made (based on predicted returns).
The R-squared on quarterly was so low, that trying to consider stocks it predicted for a quarter-long buy hold was just not feasible.
The R-squared on annual was considerably higher. But even then, it was not high enough to justify a stock purchase for a year-long tie-up of investment money.
Frankly, the stocks it was picking looked horrendous in many respects. Falling Knives, despite efforts to contain those, dominated the list. Others had low liquidity (read my earlier post on the Liquidity Effect) - and Solvency was an issue on them. Buying stocks with low or no liquidity and practically insolvent, and trying to hold them even a quarter, no less a year, is absolutely stupid.
I did Ensemble these models. But it didn't change the picture for me. And remember, I have Macro data and Macro Interactives in this model!
The conclusion:
Statements (fundamentals) are important - but not for picking stocks based on them necessarily. You would have to combine the fundamentals with other things.
I kind of knew this already, based on things I had read. I guess I needed to use the effort as a proving ground to myself.
So - in the end - I shelved these models. I learned a TON and it was great doing them. It built me into an AI Powerhouse with solid fundamentals in Quant Finance, an thorough understanding of Data Science and ML/AI algorithms, statistics, beefed-up math skills, etc.
I will move on.
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