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🎯 TradeSight — Python Algorithmic Trading & Backtesting Strategy Lab

Python 3.11+ Flask License: MIT Tests: 169/169 Paper Trading Live P&L Portfolio GitHub Stars Strategies

Build, test, and evolve trading strategies with AI — entirely on your own machine. No cloud subscription. No data leaks. No monthly fees.

TradeSight is a self-hosted Python app that runs AI-powered strategy tournaments overnight, backtests technical indicators, and executes paper trades via Alpaca — all from a local web dashboard.

TradeSight Demo — Paper Trading Report


🤔 Who Is This For?

  • Algorithmic trading hobbyists who want to test strategies without risking real money
  • Python developers exploring quantitative finance and AI-driven decision systems
  • Privacy-conscious traders who don't want their strategies on someone else's server
  • Makers building autonomous financial agents

✨ Features

Feature Description
🧬 AI Strategy Tournaments Automated overnight evolution of trading strategies — the best wins, rest are retired
📊 15+ Technical Indicators MACD, RSI, Bollinger Bands, EMA crossovers, ATR, volume analysis, and more
💸 Paper Trading Connect Alpaca paper account — trade with fake money, track real P&L
🔍 Multi-Market Scanner Scan stocks + Polymarket prediction markets for signals simultaneously
🌐 Web Dashboard Real-time Flask interface — positions, signals, tournament results, logs
⏰ Cron Automation Overnight strategy improvement runs automatically — wake up to new results
🔒 100% Local Runs on your machine. Your strategies stay yours.

🚀 Quick Start

Requirements

Install

macOS (Homebrew):

brew tap rmbell09-lang/tradesight
brew install tradesight

From source:

git clone https://github.com/rmbell09-lang/tradesight.git
cd tradesight
pip install -r requirements.txt

Run

python START_TRADESIGHT.py

Dashboard opens at http://localhost:5000

Demo Mode (No API Keys Required)

TradeSight runs fully in demo mode with simulated market data — no Alpaca account needed to explore.

Live Paper Trading (Optional)

  1. Create a free Alpaca paper account
  2. Add your API keys to config/api_keys.json:
{
  "alpaca_key": "YOUR_KEY",
  "alpaca_secret": "YOUR_SECRET",
  "paper": true
}

📸 Dashboard

┌─────────────────────────────────────────────────┐
│  TradeSight Dashboard          [Localhost:5000]  │
├──────────┬──────────┬───────────┬───────────────┤
│ Markets  │Tournaments│  Trading  │   Settings    │
├──────────┴──────────┴───────────┴───────────────┤
│  Active Signals: 3    Open Positions: 2          │
│  Best Strategy: MACD Crossover (score: 0.72)     │
│  Paper P&L: -$113.96  (initial RSI strategy)     │
│  Next Tournament: Tonight @ 2:00 AM              │
└─────────────────────────────────────────────────┘

🧪 Test Results

169/169 tests passing ✅
python -m pytest tests/ -v

🏗️ Architecture

tradesight/
├── src/
│   ├── scanner.py          # Multi-market signal scanner
│   ├── strategy_lab/       # AI tournament engine
│   ├── trading/            # Alpaca paper trade executor
│   ├── indicators/         # 15+ technical indicators
│   └── automation/         # Overnight cron jobs
├── web/                    # Flask dashboard
├── config/                 # API keys + settings
├── data/                   # Price history cache
└── tests/                  # 169 unit tests

📈 Live Paper Trading — April 2026

Real money-at-risk (on paper). Updated automatically. System has been live since March 2026.

Current Portfolio: $532 total value | +6.43% total return (+$32.15)

Strategy Trades P&L Win Rate
MACD Crossover 1 +$17.89 100% ✅
VWAP Reversion 1 -$4.75 0%
RSI Mean Reversion 5 -$13.77 20%

Recent Closed Trades (Last 7 Days):

Symbol Strategy Entry Exit P&L
JPM MACD Crossover $242.94 $303.24 +$17.89 ✅
SPY RSI Mean Reversion $596.36 $649.79 +$6.06 ✅
AMZN VWAP Reversion $223.25 $209.69 -$4.75
QQQ RSI Mean Reversion $590.06 $565.22 -$6.56
GOOG RSI Mean Reversion $297.77 $276.47 -$13.28

This is a live paper trading account connected to Alpaca. All prices are real market data; no real money at risk. System runs overnight tournaments to evolve strategy parameters automatically. Early RSI underperformance drove a regime-filter upgrade now in production.


🗺️ Roadmap

  • Multi-indicator technical analysis (15+ indicators)
  • AI strategy tournament engine
  • Alpaca paper trading integration
  • Real-time web dashboard
  • Overnight automation (cron)
  • Phase 1: Active stop-loss + take-profit execution
  • Phase 1: Trailing stop with high-water mark
  • Phase 2: Confluence strategy (multi-indicator entry gates)
  • Phase 2: Market regime detection (bull/bear/sideways filter)
  • Phase 3: Monte Carlo simulation for strategy validation


💰 Support Development

TradeSight is MIT-licensed and free to use. If it saved you time or you want the packaged strategy lab with setup guide and pre-tuned parameters:

Get TradeSight Strategy Lab on Gumroad → — $49 one-time

Includes: packaged download, setup walkthrough, pre-configured Alpaca integration, and strategy parameter reference.

TradeSight is similar to — but different from — these popular Python trading tools:

Project What It Does How TradeSight Differs
backtrader Python backtesting framework TradeSight adds AI strategy evolution + live paper trading web dashboard
freqtrade Crypto trading bot TradeSight focuses on stocks (Alpaca API) with overnight strategy tournaments
vectorbt Vectorized backtesting in notebooks TradeSight is a self-hosted web app — no notebook required
zipline-reloaded Algorithmic trading library TradeSight is a full app, not a library — no Python trading experience needed
Jesse Crypto strategy framework TradeSight is for stocks + prediction markets, not crypto
nautilus_trader High-performance trading platform TradeSight is simpler, self-hosted, built for hobbyists not HFT
BillingWatch Self-hosted billing anomaly detection Same maker — catch Stripe issues before they cost you

Also useful for: python trading bot · algorithmic trading python · paper trading software · free backtesting · stock trading python · quantitative finance · algo trading strategy tester · self-hosted trading platform · automated trading system · backtesting framework


📄 License

MIT — free to use, modify, and build on.


⭐ If This Helped You

Star the repo — it helps other Python traders find it.

Got broken AI-generated code? → Vibe Code Rescue

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