Getting Started: Paper Trading

Paper trading lets you test strategies with virtual capital in real-time market conditions. QuanterLab provides three paper trading modules, each designed for a different type of strategy.

Classic Paper Trading (PT003MRSB)

Designed for configs saved from the Strategy Builder modules (Mean Reversion, Momentum, Crossover, Breakout). Access it from the Dashboard or the Execution ribbon.

How It Works

1. Import a config — The module reads your saved strategy configs from the Execution ribbon. Click on a config to load it
2. Create a project — Group related configs into a project (e.g., "MR Strategies"). Assign capital to the project
3. Deploy instances — Each config becomes an instance with its own ticker and allocated capital. Click Deploy to start scanning
4. Monitor — The instance scans live market data, evaluates your entry/confirmation/exit conditions, and auto-executes trades when signals trigger. The price chart, indicator chart, and signal log update in real time

Advanced Paper Trading (PT004UBPT)

Designed for configs saved from the Overlay/Builder (UB001UNIV). It supports all 50+ indicators with full entry, confirmation, and exit condition layers.

Key Differences from Classic

• Indicator support — Classic supports the family-specific indicators. Advanced supports every indicator in the platform
• Three condition layers — Entry, Confirmation, and Exit are fully independent with different indicators possible on each
• Three indicator charts — The monitoring view shows separate charts for entry indicator (gold), confirmation indicator (orange), and exit indicator (red)
• Direction support — Long or Short trading as configured in the Overlay/Builder

Deploying an Advanced Instance

1. Save a config from the Overlay/Builder (the "Save to Ribbon" button in the backtest results)
2. Open Advanced Paper Trading from the Dashboard or Execution ribbon
3. Click on your saved config to import it
4. Set the ticker, capital amount, and click Deploy
5. The instance loads historical data, computes all indicator values, and begins scanning for signals

ML Paper Trading (ML001HPTX)

For machine learning models trained in the ML Training module. This module runs your trained model against live market data to generate real-time buy/sell predictions.

How It Works

1. Train a model — Use the ML Training module to train a Random Forest, XGBoost, LightGBM, or CatBoost model on a ticker
2. Deploy to Paper Trading — The trained model appears in ML Paper Trading. Start the instance
3. Live predictions — The model runs feature engineering on live data and generates predictions at each bar. Classification models output Buy/Sell/Hold signals. Regression models output predicted price direction
4. Auto-execution — When a buy signal triggers and no position is open, the instance enters. When a sell signal triggers, it exits. Position status, P&L, and signal history update in real time

Monitoring Your Instances

All active paper trading instances appear in the left sidebar of every page. You can see at a glance:

• Instance status — SCANNING (waiting for entry), LONG (in a long position), SHORT (in a short position), IDLE (stopped)
• Current P&L — Live unrealized profit/loss percentage for open positions
• Instance type — MR (Mean Reversion), UB (Universal Builder), ML (Machine Learning)

Click on any sidebar instance to jump directly to its monitoring page.

Common Workflow