Trading-Bot

🤖 Robinhood Trading Bot Dashboard

A Python-based trading bot with a real-time web dashboard for monitoring and managing your Robinhood portfolio.

Python Flask License

✨ Features

🚀 Quickstart

Prerequisites

Step 1: Clone or Download

# Clone the repository (or download the files)
git clone <your-repo-url>
cd robinhood-trading-bot

Step 2: Install Dependencies

pip install -r requirements.txt

Or install packages individually:

pip install flask robin-stocks python-dotenv pandas

Step 3: Run the Dashboard

python Trading_Bot_Dashboard.py

That’s it! The dashboard will open automatically in your browser.

Step 4: Enter Credentials (First Run Only)

On first run, you’ll see a setup page. Enter your Robinhood credentials:

  1. Enter your Robinhood email/username
  2. Enter your Robinhood password
  3. Click “Save & Continue to Dashboard”

Your credentials are stored locally in a .env file and never sent anywhere.

Note: You may need to complete 2FA verification on first login.

Step 5: Select Your Strategy

After credentials are set, you’ll see the Strategy Selection screen:

  1. The bot analyzes current market conditions (SPY performance, volatility)
  2. It recommends an optimal strategy based on market state
  3. Choose the recommended strategy, your saved settings, or any preset
  4. If no selection is made within 30 seconds, the recommended strategy is auto-applied

📊 Market Condition Presets

The bot includes 6 pre-configured strategies optimized for different market conditions:

Preset Condition ETFs Strategy
🚀 Bullish Growth Rising markets QQQ, VGT, SMH, XLK, SOXX Aggressive growth, larger positions
🛡️ Bearish Defense Declining markets SH, GLD, TLT, XLU, VPU Defensive/inverse ETFs, smaller positions
⚡ High Volatility Turbulent markets SPLV, USMV, VYM, SCHD, XLP Low-vol ETFs, tight position sizing
📊 Sideways Income Flat markets VYM, SCHD, HDV, DVY, JEPI Dividend focus, income generation
📈 Market Recovery Recovering markets VTI, SPY, IWM, XLF, VB Broad market + small caps
🎯 Correction Mode Pullback markets VOO, QQQ, VTI, SCHG, VUG Quality ETFs for dip-buying

How Market Detection Works

The bot analyzes:

📁 Project Structure

robinhood-trading-bot/
├── Trading_Bot_Dashboard.py   # Main application (all-in-one)
├── requirements.txt           # Python dependencies
├── .env                       # Credentials (auto-created)
├── bot_settings.json          # User settings (auto-created)
└── README.md                  # This file

🖥️ Using the Dashboard

Dashboard URL

http://127.0.0.1:5000

Available Pages

Page URL Description
Dashboard / Main portfolio view with controls
Strategy Select /select-strategy Choose trading strategy
Settings /settings Configure stocks and parameters
Setup /setup Credential configuration

Dashboard Controls

⚙️ Configuration

On startup, select from market-optimized presets or your saved strategy.

Via Web Interface

  1. Click Settings in the dashboard
  2. Modify any settings
  3. Click Save Settings

Via Settings File

Edit bot_settings.json directly:

{
  "stocks": ["QQQ", "SPY", "NVDA", "AAPL", "MSFT"],
  "trading_buffer": 0.02,
  "sma_window": 12,
  "max_cash_per_stock": 0.25,
  "min_shares_to_buy": 1,
  "check_interval": 30,
  "preset_applied": "bullish"
}

Configuration Options

Setting Default Description
stocks Varies by preset Stock/ETF symbols to monitor
trading_buffer 0.015 - 0.035 Price deviation from SMA to trigger trades
sma_window 8 - 15 Number of data points for SMA calculation
max_cash_per_stock 0.12 - 0.30 Max portfolio % per single trade
min_shares_to_buy 1 Minimum shares to execute a buy
check_interval 20 - 60 Seconds between price checks

📈 Trading Strategy

The bot uses a Simple Moving Average (SMA) strategy:

  1. Tracks price history for each configured stock
  2. Calculates the SMA over the configured window
  3. Generates signals based on price deviation:
    • BUY when price drops below SMA by more than the buffer
    • SELL when price rises above SMA by more than the buffer
    • HOLD when price is near the SMA

Signal Example

With trading_buffer = 0.02 (2%):

⚠️ Important Notes

Paper Trading Mode (Default)

The bot runs in paper trading mode by default. Trades are logged but not executed.

To enable live trading, uncomment the trade execution code in Trading_Bot_Dashboard.py:

# Find these sections and uncomment:
# rh.orders.order_buy_limit(...)
# rh.orders.order_sell_limit(...)

Market Hours

The bot only operates during market hours (9:30 AM - 4:00 PM ET). Outside these hours, it waits automatically.

Security

🛠️ Troubleshooting

“Missing credentials” error

  1. Delete the .env file
  2. Restart the application
  3. Re-enter your credentials on the setup page

2FA Issues

If you use 2FA on Robinhood:

  1. The first login may prompt for a code in the terminal
  2. Enter the code from your authenticator app
  3. Session is cached for future logins

Port Already in Use

If port 5000 is busy, modify the last line in Trading_Bot_Dashboard.py:

app.run(host='0.0.0.0', port=5001, debug=False)  # Change 5000 to 5001

Dashboard Won’t Load

  1. Check if the terminal shows any errors
  2. Ensure all dependencies are installed: pip install -r requirements.txt
  3. Try accessing http://127.0.0.1:5000 directly in your browser

Skip Strategy Selection

To go directly to dashboard without strategy selection:

http://127.0.0.1:5000/?skip_strategy=1

🔧 Windows Quick Launch

Double-click run_dashboard.bat to start the bot, or create one:

@echo off
cd /d "%~dp0"
python Trading_Bot_Dashboard.py

📋 API Endpoints

Endpoint Method Description
/api/status GET Current bot state and portfolio data
/api/settings GET/POST Read or update settings
/api/market-condition GET Detect current market condition
/api/apply-strategy POST Apply a strategy preset
/api/presets GET Get all available presets
/api/bot/start POST Start the trading bot
/api/bot/stop POST Stop the trading bot
/api/refresh GET Refresh data from Robinhood
/api/setup/credentials POST Save Robinhood credentials
/api/shutdown POST Shutdown the server

⚖️ Disclaimer

This software is for educational purposes only.

📄 License

MIT License - Feel free to modify and distribute.

🤝 Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.