Trading Bot Integration

Complete trading bot implementations for automated cryptocurrency trading using Vedicquant cosmic signals.

🚀 Overview

Automate your trading with cosmic intelligence! This section covers:

Multi-Exchange Support: Binance, Bybit, Kraken integration
Risk Management: Position sizing and portfolio protection
Real-time P&L Tracking: Live profit/loss monitoring
Vedic Phase Filtering: Trade only during favorable cosmic periods

📦 Exchange Support

Binance Integration

Spot and futures trading
OCO (One-Cancels-Other) orders
Advanced order types
Testnet support for safe development

Bybit Integration

Derivatives trading
Perpetual contracts
Advanced risk management
High-frequency trading support

Multi-Exchange Architecture

Unified trading interface
Portfolio diversification
Cross-exchange arbitrage opportunities
Centralized risk management

🎯 Quick Start

Basic Trading Bot Structure

python

from vedicquant_client import VedicquantSSEClient
import ccxt

class CosmicTradingBot(VedicquantSSEClient):
    def __init__(self, exchange_config):
        super().__init__(api_key='free-week-demo123')
        
        # Initialize exchange
        self.exchange = ccxt.binance({
            'apiKey': exchange_config['api_key'],
            'secret': exchange_config['secret'],
            'sandbox': True,  # Use testnet for safety
            'enableRateLimit': True
        })
        
        # Trading parameters
        self.risk_per_trade = 0.02  # 2% risk per trade
        self.max_positions = 5
        self.allowed_symbols = ['BTC', 'ETH', 'SOL', 'ADA']
        self.favorable_phases = ['Amrita', 'Shubha', 'Labha']
        
    def default_signal_handler(self, signal_data):
        if signal_data.get('event_type') == 'new_signal':
            if self.should_trade_signal(signal_data):
                self.execute_trade(signal_data)
    
    def should_trade_signal(self, signal):
        # Signal validation logic
        symbol = signal.get('symbol')
        strength = signal.get('signal_strength')
        phase = signal.get('phase_name', '')
        
        # Check symbol allowlist
        if symbol not in self.allowed_symbols:
            return False
            
        # Check signal strength
        if strength != 'strong':
            return False
            
        # Check Vedic phase
        if not any(phase_name in phase for phase_name in self.favorable_phases):
            self.logger.info(f"⚠️ Unfavorable phase: {phase}")
            return False
            
        # Check position limits
        if len(self.get_open_positions()) >= self.max_positions:
            return False
            
        return True
    
    def execute_trade(self, signal):
        try:
            symbol = f"{signal['symbol']}/USDT"
            signal_type = signal['signal_type']
            
            # Calculate position size based on risk
            position_size = self.calculate_position_size(signal)
            
            if signal_type == 'BUY':
                order = self.exchange.create_market_buy_order(symbol, position_size)
            else:
                order = self.exchange.create_market_sell_order(symbol, position_size)
            
            self.logger.info(f"✅ Order executed: {symbol} {signal_type}")
            
            # Set stop loss and take profit
            self.set_exit_orders(signal, order)
            
        except Exception as e:
            self.logger.error(f"❌ Trade execution failed: {e}")
    
    def calculate_position_size(self, signal):
        # Risk-based position sizing
        portfolio_value = self.get_portfolio_value()
        risk_amount = portfolio_value * self.risk_per_trade
        
        entry_price = signal['price_at_signal']
        stop_price = signal['stop_loss_price']
        
        price_risk = abs(entry_price - stop_price) / entry_price
        position_value = risk_amount / price_risk if price_risk > 0 else 0
        
        return position_value / entry_price
    
    def set_exit_orders(self, signal, entry_order):
        # Set stop loss and take profit orders
        try:
            symbol = f"{signal['symbol']}/USDT"
            amount = entry_order['amount']
            
            # Stop loss order
            stop_order = self.exchange.create_stop_market_order(
                symbol,
                'sell' if signal['signal_type'] == 'BUY' else 'buy',
                amount,
                signal['stop_loss_price']
            )
            
            # Take profit order
            profit_order = self.exchange.create_limit_order(
                symbol,
                'sell' if signal['signal_type'] == 'BUY' else 'buy',
                amount,
                signal['target_price']
            )
            
            self.logger.info(f"✅ Exit orders set for {symbol}")
            
        except Exception as e:
            self.logger.error(f"❌ Failed to set exit orders: {e}")

# Usage
exchange_config = {
    'api_key': 'your_binance_api_key',
    'secret': 'your_binance_secret'
}

bot = CosmicTradingBot(exchange_config)
bot.start()

🛡️ Risk Management

Position Sizing

python

def calculate_position_size(self, signal, portfolio_value, risk_percentage=0.02):
    """
    Calculate position size based on:
    - Total portfolio value
    - Risk percentage per trade
    - Distance to stop loss
    """
    risk_amount = portfolio_value * risk_percentage
    entry_price = signal['price_at_signal']
    stop_price = signal['stop_loss_price']
    
    # Price risk as percentage
    price_risk = abs(entry_price - stop_price) / entry_price
    
    # Position value that risks only the specified amount
    position_value = risk_amount / price_risk if price_risk > 0 else 0
    
    # Convert to position size in base currency
    return position_value / entry_price

Portfolio Limits

python

class RiskManager:
    def __init__(self):
        self.max_positions = 5
        self.max_portfolio_risk = 0.10  # 10% total portfolio risk
        self.max_single_position = 0.05  # 5% per position
        
    def can_open_position(self, signal, current_positions):
        # Check position count limit
        if len(current_positions) >= self.max_positions:
            return False, "Maximum positions reached"
            
        # Check portfolio concentration
        total_risk = sum(pos['risk_amount'] for pos in current_positions.values())
        if total_risk >= self.max_portfolio_risk:
            return False, "Portfolio risk limit exceeded"
            
        return True, "Position approved"

Vedic Phase Filtering

python

class VedicFilter:
    def __init__(self):
        self.favorable_phases = {
            'Amrita': 1.0,    # Best - take full position
            'Shubha': 0.8,    # Very good - reduce position by 20%
            'Labha': 0.6,     # Good - reduce position by 40%
            'Chara': 0.0,     # Neutral - no trading
            'Kala': 0.0,      # Dangerous - no trading
            'Roga': 0.0,      # Disease - no trading
            'Udvega': 0.0     # Anxiety - no trading
        }
        
    def get_position_multiplier(self, phase_name):
        """Get position size multiplier based on Vedic phase"""
        for phase, multiplier in self.favorable_phases.items():
            if phase in phase_name:
                return multiplier
        return 0.0  # Unknown phase - no trading
    
    def should_trade_in_phase(self, phase_name):
        """Check if trading is allowed in current phase"""
        return self.get_position_multiplier(phase_name) > 0

📋 Available Examples

From your migrated documentation:

binance_bot.py - Complete Binance trading implementation
bybit_bot.py - Bybit derivatives trading
README.md - Original trading documentation

🎯 Features

🔄 Real-time Trading: Instant signal execution
🛡️ Risk Management: Advanced position sizing
📊 Performance Tracking: P&L monitoring
🌙 Cosmic Intelligence: Vedic phase filtering
🔄 Auto-reconnection: Robust connection handling

🔧 Development Setup

Environment Variables

bash

# Exchange API credentials
BINANCE_API_KEY=your_api_key
BINANCE_SECRET=your_secret
BYBIT_API_KEY=your_api_key
BYBIT_SECRET=your_secret

# Vedicquant
VEDICQUANT_API_KEY=free-week-demo123

# Trading parameters
RISK_PER_TRADE=0.02
MAX_POSITIONS=5
USE_TESTNET=true

Dependencies

bash

pip install ccxt requests python-dotenv pandas numpy

🚨 Safety First

Always Start with Testnet

Use exchange testnet/sandbox environments
Test with small amounts
Validate signal processing logic
Monitor bot performance

Risk Controls

Never risk more than you can afford to lose
Start with very small position sizes
Use stop losses on every trade
Monitor bot performance continuously

🎯 Best Practices

Gradual Scaling: Start small and increase size slowly
Diversification: Don't put all capital in one strategy
Monitoring: Track all trades and performance metrics
Vedic Respect: Honor the cosmic timing wisdom

Ready to automate cosmic trading! 🌙✨

Trading Bot Integration ​

🚀 Overview ​

📦 Exchange Support ​

Binance Integration ​

Bybit Integration ​

Multi-Exchange Architecture ​

🎯 Quick Start ​

Basic Trading Bot Structure ​

🛡️ Risk Management ​

Position Sizing ​

Portfolio Limits ​

Vedic Phase Filtering ​

📋 Available Examples ​

🎯 Features ​

🔧 Development Setup ​

Environment Variables ​

Dependencies ​

🚨 Safety First ​

Always Start with Testnet ​

Risk Controls ​

🎯 Best Practices ​

Trading Bot Integration

🚀 Overview

📦 Exchange Support

Binance Integration

Bybit Integration

Multi-Exchange Architecture

🎯 Quick Start

Basic Trading Bot Structure

🛡️ Risk Management

Position Sizing

Portfolio Limits

Vedic Phase Filtering

📋 Available Examples

🎯 Features

🔧 Development Setup

Environment Variables

Dependencies

🚨 Safety First

Always Start with Testnet

Risk Controls

🎯 Best Practices