This project implements an automated trading bot in Python that utilizes a moving average crossover strategy to make buy/sell decisions in financial markets. The bot is designed to execute trades based on the crossing of short-term and long-term moving averages, a popular strategy used by traders to identify potential trend reversals.
- Fetches real-time market data using the Alpaca API.
- Calculates short-term and long-term moving averages of asset prices.
- Generates buy signals when the short-term moving average crosses above the long-term moving average.
- Generates sell signals when the short-term moving average crosses below the long-term moving average.
- Implements risk management measures to control position sizing and minimize losses.
- Provides backtesting functionality to evaluate the bot's performance using historical data.
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Clone the repository:
git clone https://github.com/tshepomaredi/tradingBot.git cd tradingBot -
Install dependencies:
pip install -r requirements.txt
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Obtain API keys:
- Sign up for an account on Alpaca and obtain your API key and secret key.
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Update configuration:
- Replace
'your_api_key'and'your_secret_key'in the code with your actual Alpaca API key and secret key.
- Replace
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Run the bot:
python main.py
- Customize the asset symbol and moving average periods in the code according to your preferences.
- Monitor the bot's output to receive buy/sell signals and execute trades accordingly.
- Backtest the bot's performance using historical data to evaluate its effectiveness.
This project is licensed under the MIT License. See the LICENSE file for details.
- This project utilizes the Alpaca API for accessing real-time market data and executing trades.
- This project is for educational and informational purposes only. Automated trading bots involve risks, and past performance is not indicative of future results. Use at your own risk.