One Score to Rule Them All: 0-100
Most stock screeners give you a wall of numbers and leave interpretation to you. TradeAlerts AI is different. Our unified scoring model distills 7 independent analysis components into a single score from 0 to 100 for each ticker, every day. A score of 80+ means multiple signals are converging; a score below 30 means stay away.
This is not a simple average. Each component is weighted dynamically based on the current market regime. In a trending market, momentum and flow signals carry more weight. In a choppy, range-bound market, mean reversion and GEX signals dominate. The model adapts.
The 7 Components
1. ML Direction Model
A gradient-boosted ensemble trained on 50+ features predicts the probability of bullish vs bearish moves over 1-5 day horizons. This is the core directional engine powering every score.
2. Options Flow Score
Aggregated options flow sentiment including sweep detection, premium weighting, and DTE-adjusted aggression scoring. When smart money is active, this component spikes.
3. Technical Analysis
10 technical indicators including RSI, MACD, Bollinger Bands, volume profile, and support/resistance levels. Computed across multiple timeframes and combined into a technical conviction score.
4. GEX Positioning
Gamma exposure analysis including dealer regime (positive/negative), proximity to call/put walls, GEX flip point relative to current price, and charm/vanna effects.
5. Market Regime
Macro regime classification (risk-on, risk-off, transitional) based on VIX, yield curves, sector rotation, and cross-asset correlation. The regime determines how other components are weighted.
6. Trigger Events
Earnings dates, ex-dividend dates, FOMC meetings, sector catalysts, and other scheduled events that can move individual stocks or the broader market. Event proximity adjusts position sizing recommendations.
7. Track Record
Historical accuracy of signals for each ticker. Some stocks respond better to flow signals; others to technical levels. The model learns which components work best for which tickers over time.
Sortable table showing all 570+ tickers with unified score (0-100 with color gradient), individual component scores, directional bias arrow, conviction level, and the primary signal driver for each ticker
How Plays Are Generated
When a ticker's unified score crosses a threshold (typically 70+), the system generates an actionable options play:
- Direction confirmed: The ML model and at least 2 other components must agree on direction.
- Strike selection: Optimal strike is chosen based on delta, liquidity, and the expected magnitude of the move.
- Expiration selection: DTE is selected to balance theta decay against the expected move timeline, typically 2-4 weeks for swing trades.
- Entry zone: A price range for the option where the risk/reward is favorable.
- Exit strategy: Every play includes a stop loss, profit target, and a scale-out plan (e.g., sell half at 50% gain, trail the rest).
The Conviction Slider
Not every trader has the same risk tolerance. The conviction slider lets you filter the scanner output by minimum score. Set it to 80 and you will see only the highest-conviction setups with full signal convergence. Set it to 50 and you will see more ideas with moderate conviction.
Historical backtesting shows that trades with unified scores above 75 have a significantly higher win rate than those scoring 50-60, though the lower-scoring trades sometimes produce the largest winners when they do work.
What Machine Learning Model Do We Use?
The core ML engine is a gradient-boosted decision tree ensemble (similar to XGBoost/LightGBM architecture) trained on 50+ features including price action, volume, options flow, implied volatility surface, and inter-market correlations. The model is retrained weekly using walk-forward validation to prevent overfitting and adapt to changing market conditions.
Unlike black-box neural networks, our tree-based model provides feature importance explanations for each prediction. When the model scores NVDA at 85, you can see exactly which features are driving that score: maybe it is a combination of bullish options flow, positive GEX positioning, and a technical breakout above resistance.
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Frequently Asked Questions
Our unified scoring model combines 7 components (ML direction, options flow, technical analysis, GEX positioning, market regime, trigger events, and track record) into a single 0-100 score for each ticker. Components are weighted dynamically based on the current market regime. Scores above 75 indicate strong signal convergence across multiple data sources.
We use a gradient-boosted decision tree ensemble (similar to XGBoost architecture) trained on 50+ features. The model is retrained weekly using walk-forward validation to prevent overfitting. Unlike neural networks, our model provides feature importance explanations so you can see exactly what is driving each score.
We scan over 570 optionable tickers covering mega-caps, large-caps, popular mid-caps, and key ETFs (SPY, QQQ, IWM). The free tier provides full scanning for all Magnificent 7 stocks. Premium unlocks the full 570+ ticker universe.
Yes. Every generated play includes a specific stop loss level, profit target, and a scale-out plan (for example, sell half at 50% profit and trail the remaining position). The exit strategy is customized based on the stock's volatility, the option's delta/theta profile, and the expected move magnitude.