AI Stock Predictions Powered by
10 Machine Learning Models
Every day, 10 independent ML algorithms analyze every S&P 500 stock and vote on direction. When most models agree with high confidence, you get a clear BUY or SELL signal.
Try Free →10 Algorithms, One Ensemble Signal
Each model brings a different strength — tree-based models catch non-linear patterns, deep learning models detect sequential trends. The ensemble combines them for higher accuracy.
101 Features Per Stock, Every Day
Models don't just look at price. They ingest technical indicators, earnings data, fundamentals, sector momentum, sentiment, and options flow.
RSI, MACD, Bollinger Bands, ADX, ATR, OBV, VWAP, Stochastic, Ichimoku, and 52 more
Earnings surprise, P/E, P/B, debt ratio, sector momentum, VIX correlation, options put/call ratio, institutional flows
Price up, beat SPY, >0.5% gain, >1% gain, positive + beat index — models train on multiple definitions of "success"
4 AI Advisors for a Second Opinion
Beyond the ML ensemble, four large language models independently analyze each stock. When multiple advisors agree, the conviction is higher.
Deep fundamental reasoning about market context, risks, and catalysts.
Broad market perspective with real-time data and trend analysis.
Fast portfolio reviews and quick second opinions on positions.
10 algorithms vote independently. Majority + high confidence = strong signal.
How We Measure Prediction Accuracy
Directional accuracy: We measure whether the predicted direction (up or down over 5 trading days) matches the actual price movement. A model that says "up" and the stock goes up is a correct prediction.
Time-series validation: Training data is split chronologically — models train on older data and validate on newer data, never the reverse. This prevents look-ahead bias that inflates accuracy in backtests.
Overfit rejection: Any model achieving >99% AUC on training data is automatically rejected. This catches models that memorize rather than generalize.
Nightly retraining: Models retrain every night with the latest market data. Stale models degrade — fresh models adapt to changing market conditions.
Past performance does not guarantee future results. All predictions are probabilistic, not guaranteed.
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