Thanks for sharing! Really curious about ML stock market models as they seem extremely difficult to outperform the market consistently over time. A few questio

Thanks for sharing! Really curious about ML stock market models as they seem extremely difficult to outperform the market consistently over time. A few questions: 1) Were these stock picks for major stocks / ETFs? Or small market cap stocks? 2) How many people were subscribed to your newsletter? 3) What do you estimate the impact was of creating a “self-fulfilling prophecy” of entering a position and then recommending your subscribers take the same position? 4) Do you think your asset mix outperformed the market by picking high risk / high reward stocks in a bull market? Or picking safe stocks in a bear market? In other words, how do you know the engine wasn’t biased towards the market trend that happened to play out? For example, if I have a basket of tech stocks that would typically outperform in a bull market and flip a coin to buy or short them and guess right, I could outperform the market by chance. How did you account for this? 5) Have you backtested the engine to see what it would have returned in previous years? (Obviously on unseen data, rather than data it used for training)