A self-evolving AI trading agent that learns from quantitative optimization, user behavior, and real-time market intelligence.
Built for the Self-Evolving Agents Hackathon using LiquidMetal Raindrop, Fastino AI, and LinkUp.
Most trading bots use static rules and fixed parameters. StrategyEvolve is different:
- π§ Learns YOUR unique trading edge from your decisions and outcomes
- π Optimizes strategies through continuous backtesting and evolution
- π Stays current with real-time market news and context
- π Self-improves through three independent evolution loops
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β EVOLUTION LOOPS β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β Loop 1: Quantitative Optimization (Raindrop) β
β β’ Generate strategy variants β
β β’ Parallel backtesting β
β β’ Performance metrics & selection β
β β
β Loop 2: Behavioral Learning (Fastino) β
β β’ Ingest user trades & decisions β
β β’ Stage 3 agentic search discovers patterns β
β β’ Learn user's unique trading edge β
β β
β Loop 3: Contextual Intelligence (LinkUp) β
β β’ Real-time market news & sentiment β
β β’ Earnings & macro event detection β
β β’ Context-aware decision making β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Frontend:
- React 18 + TypeScript
- Vite for blazing fast dev experience
- TailwindCSS for modern UI
- Recharts for data visualization
- Zustand for state management
Backend:
- Node.js + Express
- TypeScript
- PostgreSQL (via Raindrop SmartSQL) β
AI/ML Platforms:
- Raindrop - Infrastructure, parallel tasks, SmartSQL database, observers β
- Fastino - User behavioral learning & personalization
- LinkUp - Real-time market intelligence
- Genetic algorithm-based parameter tuning
- Parallel backtesting via Raindrop Tasks (10x faster) β
- Performance metrics: Sharpe ratio, returns, drawdown, win rate
- Captures user trades, overrides, and reasoning
- Fastino Stage 3 discovers non-obvious patterns
- Learns user's emotional triggers and risk tolerance
- Real-time news and sentiment via LinkUp
- Earnings and macro event detection
- Context-aware signal enhancement
- Combines quantitative optimization with user behavioral patterns
- Blends systematic signals with human intuition
- Adaptive position sizing based on learned preferences
- Real-time visualization of strategy evolution
- Performance metrics over time
- User behavioral insights
- Market context integration
- Node.js 18+
- npm or yarn
- LiquidMetal API Key (Get one here)
- Fastino API Key (Get one here)
- LinkUp API Key (Get one here)
# Navigate to project
cd strategy-evolve
# Install frontend dependencies
cd frontend
npm install
# Install backend dependencies
cd ../backend
npm install
# Set up environment variables
cp .env.example .env
# Edit .env with your API keys
# Start development
npm run dev# LiquidMetal Raindrop
LM_API_KEY=your_liquidmetal_api_key
# Fastino
FASTINO_API_KEY=your_fastino_api_key
# LinkUp
LINKUP_API_KEY=your_linkup_api_key
# Server
PORT=3001
NODE_ENV=developmentstrategy-evolve/
βββ frontend/ # React + TypeScript UI
β βββ src/
β β βββ components/ # React components
β β βββ pages/ # Page components
β β βββ hooks/ # Custom hooks
β β βββ store/ # Zustand state management
β β βββ services/ # API services
β β βββ types/ # TypeScript types
β βββ package.json
β
βββ backend/ # Node.js + Express API
β βββ src/
β β βββ routes/ # API routes
β β βββ services/ # Business logic
β β β βββ fastino.ts # Fastino integration
β β β βββ linkup.ts # LinkUp integration
β β β βββ raindrop.ts # Raindrop integration
β β β βββ strategy.ts # Strategy engine
β β β βββ evolution.ts # Evolution logic
β β βββ models/ # Data models
β β βββ utils/ # Utilities
β βββ package.json
β
βββ docs/ # Documentation
β βββ PROJECT_PLAN.md # Detailed project plan
β
βββ README.md
- Not just memory - actual strategy improvement
- Three independent learning loops
- Quantifiable metrics showing evolution
- Raindrop: Tasks, Queues, SmartSQL, Observers, deployment
- Fastino: Register, ingest, Stage 3, query, chunks - all features used meaningfully
- LinkUp: Real-time intelligence, structured output, sourced answers
- First to combine quant optimization + behavioral learning + real-time context
- Goes beyond typical "chatbot with memory"
- Shows deep understanding of each platform's strengths
- Clear before/after metrics
- Live evolution visible in real-time
- Relatable use case (trading)
- Professional UI
MIT License
Built with β€οΈ for the Self-Evolving Agents Hackathon
Let's show the world what true self-evolving agents can do!