Trading Strategy Application

This application is designed to implement and visualize a trading strategy using the DHANHQ API. The strategy involves calculating the Relative Strength Index (RSI) and Moving Averages (MA) to make buy and sell decisions. The application also includes a backtesting feature to evaluate the strategy's performance using historical data.

Features

• Real-time Trading: Uses RSI and MA crossover strategies to make buy and sell decisions in real-time.
• Backtesting: Evaluate the performance of the trading strategy using historical data.
• Visualization: Plot the stock price along with short and long moving averages.
• GUI: User-friendly interface for setting parameters and viewing logs.

Requirements

• Python 3.7+
• Libraries: requests, pandas, numpy, matplotlib, tkinter, logging, asyncio, aiohttp
• DHANHQ API Key(@dhan-oss)

Installation

1. Clone the repository:

   git clone https://github.com/arshkumarsingh/rsi-dhanhq-strat
   cd rsi-dhanhq-strat

2. Install the required libraries:

   pip install requests pandas numpy matplotlib tkinter aiohttp

3. Set your DHANHQ API key: Replace 'YOUR_API_KEY' in the script with your actual API key.

Usage

1. Run the application:

   python masterfile.py

2. Using the GUI:

   • Stock Symbol: Enter the stock symbol you want to trade.
   • Timeframe: Enter the timeframe for the historical data (e.g., 5m, 1h, 1d).
   • Quantity: Enter the quantity of stocks to trade.
   • Start Date: Enter the start date for backtesting in YYYY-MM-DD format.
   • End Date: Enter the end date for backtesting in YYYY-MM-DD format.
   • Start Trading: Click to start the real-time trading strategy.
   • Start Backtesting: Click to start backtesting the strategy.

3. View Logs:

   • The logs will be displayed in the scrolling text widget in the GUI. It will provide information about the trading decisions and the backtesting results.

Strategy Details

• RSI Calculation: The Relative Strength Index (RSI) is calculated using a period of 14.
• MA Calculation: Short and long moving averages are calculated using periods of 9 and 21 respectively.
• Trading Logic:
  • Buy when RSI is below 30 (oversold) or when a short MA crosses above the long MA.
  • Sell when RSI is above 70 (overbought) or when a short MA crosses below the long MA.
• Max Trades: Limits the number of trades to 5 per day.
• Market Hours: Trades are only executed during market hours (9:15 AM to 3:30 PM).

Contributing

Contributions are welcome! Please fork the repository and submit a pull request for any improvements or bug fixes.

License

This project is licensed under the MIT License.

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Example

Here is an example of how to configure and start the trading strategy using the GUI:

1. Stock Symbol: RELIANCE
2. Timeframe: 5m
3. Quantity: 1
4. Start Date: 2023-01-01
5. End Date: 2023-12-31

Click "Start Trading" to begin real-time trading or "Start Backtesting" to evaluate the strategy using historical data.

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For any issues or questions, please open an issue on the GitHub repository or contact the maintainer.

Happy Trading!