🎯 TradeSight — Python Algorithmic Trading & Backtesting Strategy Lab

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.

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🤔 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

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✨ 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.

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🚀 Quick Start

Requirements

• Python 3.11+
• macOS or Linux (Windows via WSL)
• Alpaca paper trading account (free, optional — demo mode works without it)

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
}

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📸 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              │
└─────────────────────────────────────────────────┘

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🧪 Test Results

169/169 tests passing ✅

python -m pytest tests/ -v

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🏗️ 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

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📈 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.

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🗺️ 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

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💰 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.

🔗 Related Projects & Alternatives

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

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📄 License

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

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⭐ If This Helped You

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

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