I Tested 1,856 ML Trading Strategies. The Results Were Brutal.

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I tested 1,856 machine-learning trading strategies on real Bitcoin and S&P 500 data to see whether ML can actually find a tradable edge.

The notebook trains multiple models, converts predictions into trading rules, and tests everything with walk-forward validation, transaction costs, regime checks, stress tests, and statistical filtering.

The top strategy (risk adjusted) returned +128% after costs, but the real question is whether it survived proper validation.

Support my work and get access to the notebooks here:
https://www.youtube.com/channel/UC87aeHqMrlR6ED0w2SVi5nw/join

Comment what you are interested in below!

Disclaimer: This video is for educational and research purposes only and should not be considered financial advice. All backtests are based on historical data and past performance does not guarantee future results. Trading involves significant risk including the potential loss of capital. Always do your own research before making financial decisions.