QuantumAlpha Capital

A Python-based algorithmic multi-analyst trading platform for cryptocurrency perpetual futures on Hyperliquid exchange. Features AI-powered market analysis, real-time technical indicators, and automated trade execution with risk management.

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Features

• Automated Trading: Systematic trade execution on Hyperliquid perpetual futures
• Multi-Analyst AI System: 4-specialist ensemble (Technical, ML, Risk, Quant) with judge consensus
• AI Integration: Multiple LLM providers (OpenRouter) for market analysis and decision making
• Technical Analysis: Real-time RSI, MACD, EMA indicators via TAAPI.io
• Risk Management: Position sizing, stop-loss, take-profit automation
• GUI Dashboard: Real-time portfolio monitoring with live charts and analyst insights
• Multi-Asset Support: BTC, ETH, LTC perpetual futures trading

Architecture

Core Components

• Market Processor (src/backend/bot_engine.py): Main trading loop with 5-minute cycles
• Multi-Analyst System (src/backend/analysts/): 4-specialist ensemble with judge consensus
• Decision Engine (src/backend/agent/decision_maker.py): AI-powered trade signal generation
• Exchange API (src/backend/trading/hyperliquid_api.py): Hyperliquid integration
• GUI Interface (src/gui/): NiceGUI-based dashboard with real-time updates
• Technical Analysis (src/backend/indicators/): TAAPI.io client with caching

Data Flow

TAAPI.io → Technical Indicators → Multi-Analyst System → Judge Consensus → Trade Signals → Hyperliquid Execution
    ↓              ↓                       ↓                    ↓              ↓              ↓
Market Data → Portfolio State → Analyst Insights → GUI Dashboard → User Interface → Trade Management

Multi-Analyst System

The platform features a sophisticated 4-analyst ensemble system:

• Technical Analyst: Price action, chart patterns, technical indicators
• ML Analyst: Machine learning models and AI-based predictions
• Risk Analyst: Risk management, position sizing, portfolio optimization
• Quant Analyst: Statistical models, market microstructure analysis

Each analyst provides independent recommendations which are evaluated by a Judge system that determines the final consensus decision based on confidence levels and market conditions.

Installation

Requirements

• Python 3.9+
• Hyperliquid account with API access
• OpenRouter API key for AI models
• TAAPI.io subscription for technical indicators

Setup

1. Clone Repository

   git clone https://github.com/LoopGlitch26/QuantumAlpha-Capital.git
   cd QuantumAlpha-Capital

2. Install Dependencies

   pip install -r requirements.txt

3. Configure Environment

   cp .env.example .env
   # Edit .env with your API keys

4. Run Application

   python main.py

Configuration

Environment Variables

# Trading Configuration
INSTRUMENTS=BTC ETH LTC                    # Assets to trade
ANALYSIS_TIMEFRAME=5m                      # Analysis frequency
EXECUTION_MODE=systematic                  # systematic/manual
AI_MODEL=deepseek/deepseek-chat-v3.1      # AI model selection
USE_MULTI_ANALYST=true                     # Enable 4-analyst ensemble system

# API Keys
HYPERLIQUID_PRIVATE_KEY=your_key          # Trading wallet private key
OPENROUTER_API_KEY=your_key               # AI model access
TAAPI_API_KEY=your_key                    # Technical analysis data

# Network
HYPERLIQUID_NETWORK=mainnet               # mainnet/testnet

Trading Parameters

• Position Sizing: Configurable allocation per asset
• Leverage: 1-10x leverage on perpetual futures
• Risk Management: Stop-loss and take-profit automation
• Execution Modes: Systematic (auto) or manual approval

Technical Specifications

AI Models Supported

• DeepSeek Chat V3.1 (recommended)
• OpenAI GPT-4/GPT-4o
• Anthropic Claude 3.5
• Google Gemini Pro
• Meta Llama models

Technical Indicators

• Trend: EMA 20/50 (5m and 4h timeframes)
• Momentum: RSI 7/14, MACD
• Volatility: ATR 3/14
• Volume: Real-time volume analysis

Exchange Features

• Hyperliquid Perpetuals: BTC-USD, ETH-USD, LTC-USD
• Order Types: Market, limit orders
• Position Management: Long/short positions
• Real-time Data: WebSocket price feeds

GUI Dashboard

Components

• Portfolio Metrics: Balance, PnL, Sharpe ratio, active positions
• Multi-Analyst Intelligence: Real-time insights from 4 specialist analysts with judge consensus
• Technical Charts: Price, RSI, MACD with real-time updates
• Position Management: Open positions with risk metrics
• Trade Proposals: AI-generated recommendations with approval workflow
• Market Intelligence: Multi-asset price and indicator data

Update Frequencies

• Main Dashboard: 3-second refresh cycle
• Technical Charts: 1-second updates
• Market Data: 5-minute collection cycle

Development

Project Structure

src/
├── backend/
│   ├── agent/           # AI decision making
│   ├── analysts/        # Multi-analyst ensemble system
│   ├── core/            # Portfolio optimization
│   ├── indicators/      # Technical analysis
│   ├── trading/         # Exchange integration
│   └── utils/           # Helper functions
├── gui/
│   ├── components/      # Reusable UI widgets
│   ├── pages/           # Dashboard pages
│   ├── services/        # Data services
│   └── themes/          # UI styling
└── database/            # Data persistence

Key Dependencies

• NiceGUI: Web-based GUI framework
• aiohttp: Async HTTP client for APIs
• plotly: Interactive charting
• sqlite3: Local data storage
• cryptography: Wallet operations

Risk Warnings

• Financial Risk: Cryptocurrency trading involves substantial risk of loss
• API Security: Protect your private keys and API credentials
• Testing: Use testnet for initial testing and development
• Capital: Only trade with funds you can afford to lose

License

MIT License - see LICENSE file for details.

Documentation

• SETUP.md - Detailed installation guide
• ARCHITECTURE.md - Technical architecture
• TRADING_STRATEGIES.md - Strategy documentation
• SECURITY_CHECKLIST.md - Security guidelines