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Build your first quant trading model.
Train on 30 years of market data. Get daily stock picks ranked by confidence. No code. No setup. Takes minutes.
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Demo Includes
- ✓Build up to 3 models
Full training pipeline — same engine as paid accounts
- ✓Full training details
Live terminal output, accuracy metrics, feature importance
- ✓50 pre-selected features (choose 10 per model)
Curated mix of technical, fundamental & macro indicators
- ✓Walk-forward backtest
Point-in-time compliant, no look-ahead bias
- ✓Portfolio backtest
Limited runs — simulate position sizing, stop-loss & rebalancing
- ✓Today's picks
Live predictions from your models, ranked by confidence
How It Works
🎯 WHAT IS QUANTBUILDER?
See Quant-Builder.ai in 31 seconds:
Quantitative Trading Research
QuantBuilder lets you train machine learning models on historical stock data, get daily picks ranked by confidence, and backtest strategies — before risking real money. No coding required.
- ✓ No coding knowledge required
- ✓ Visual interface for model building
- ✓ Daily predictions generated automatically
- ✓ Optional broker connection for one-click execution
THE 4-STEP WORKFLOW
1. BUILD
Train ML models on historical stock data
2. BACKTEST
Test your strategy against historical data
3. ANALYZE
Review daily picks & confidence scores
4. EXECUTE
Connect broker & trade (optional)
🔨 STEP 1: BUILD YOUR MODELS
Create machine learning models that learn patterns from years of stock market data. No coding required — choose your settings and click Train.
📋 WHAT DOES A MODEL ACTUALLY LOOK LIKE?
During training, the model scans 5 years of Technology stocks and finds every case where a stock went up 3% or more over 5 trading days. It then looks at what the indicators above were doing in the days before each of those moves — and learns the pattern. Once trained, every morning it looks at today's indicators across all 100 tech stocks and asks: “does this look like one of those setups?” The ones that do — ranked by how confident it is — become your picks.
🎯 What You Choose
- Stock Universe: QB500, QB1000, NASDAQ-100, sector-specific
- Training Regime: Bull, bear, sideways, recession, expansion
- Target: What return to predict (3-day +2%, 7-day +5%, etc.)
- Features: 450+ technical, fundamental & macro indicators
- Algorithm: LightGBM, XGBoost, CatBoost, Random Forest
⚡ What Happens
- Training (5–15 min): The model scans thousands of stocks across years of data
- Pattern Detection: Finds relationships between indicators & price moves
- Validation: Tests model on unseen data to prevent overfitting
- Scoring: Generates accuracy, Sharpe ratio, win rate & more
⚡ STEP 2: BACKTEST YOUR STRATEGY
Before risking real money, test your model's picks against historical data. See how a portfolio would have performed — with real position sizing, stop-losses, and rebalancing.
📊 Sample Results — Small Changes, Massive Impact
Three backtests, three confidence thresholds. 45% confidence wins over 46%, while 42% falls off a cliff. That's why you run multiple tests.
✅ POINT-IN-TIME COMPLIANT
- ✓ Includes delisted companies — no survivorship bias
- ✓ Uses data as it actually existed at each point in time
- ✓ Backtests see the same messy reality traders faced in real-time
⚠️ Portfolio Backtests include optional adverse slippage (default 10 bps entry + 10 bps exit). Commissions and market impact are not modeled — real trading costs can still differ.
📈 STEP 3: TODAY'S PICKS
Every morning, your models analyze the current market and generate ranked predictions. Each pick shows confidence %, expected return, direction, and key metrics.
Example: Low-Confidence Day (Illustrative)
This is an illustrative example of a day when many picks sat below a sample confidence threshold. The red Actual Return column shows what happened historically on that example day. Low confidence does not mean you will avoid losses, and skipping a day does not guarantee better outcomes. Past examples are not indicative of future results.
Example: Higher-Confidence Day (Illustrative)
This is an illustrative example of a day when more picks sat above a sample confidence threshold. The green Actual Return column shows what happened historically on that example day. Higher confidence is not a guarantee of profit. Past examples are not indicative of future results.
🎯 Understanding Confidence
Confidence is relative to each model, not universal. 55% from Model A may outperform 90% from Model B. Use your backtest to find each model's optimal threshold.
📊 Long vs Short
LONG: Expecting price to go up. Standard buy trade.
SHORT: Expecting price to go down. Requires margin account.
💼 STEP 4: BROKER CONNECTION (OPTIONAL)
Connect your Alpaca or Tradier account and submit trades directly from QuantBuilder — one click, 10+ positions, under 2 seconds.
🔐 Security
- 4-Digit Trading PIN: Required before every trade
- Encrypted API Keys: Credentials stored securely
- Paper Trading First: Test with fake money before going live
⚡ Trading Features
- Batch Trading: Send 10+ orders in one click
- Bracket Orders: Auto take-profit & stop-loss
- Position Sizing: Equal dollar or manual quantities
⚠️ RISK WARNING: QuantBuilder is a research platform. We do not execute trades or provide financial advice. Trading involves substantial risk of loss. Past performance does not indicate future results. Always test with paper trading first.
RISK DISCLOSURE
Quant-Builder.ai is a research and software platform for building and testing quantitative stock models. It is not a broker, investment adviser, or trading signal service. Nothing on this site is financial, investment, or trading advice.
Asset class: The platform focuses on US equity (stock) research and trading workflows. Trading equities involves substantial risk of loss, including loss of principal. Short selling, leverage, and margin (if used through your broker) increase risk.
Backtests and past results (including walk-forward tests, portfolio simulations, confidence scores, and example "Today's Picks" days) are hypothetical or historical illustrations. They do not guarantee future performance. Real trading can differ due to slippage, liquidity, commissions, timing, and market conditions.
You choose models, size positions, and authorize trades through your own brokerage account. All decisions and outcomes are your responsibility. Consult a licensed financial advisor before investing. See Terms and Privacy.
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