CryptoTraderAI: AI-Powered Trading System

CryptoTraderAI is an open-source project that aims to develop an AI-powered trading system. It leverages artificial intelligence, machine learning, and algorithmic trading techniques to provide intelligent trading strategies, automated trade execution, and risk management capabilities.

WARNING

WARNING: CryptoTraderAI is an experimental, AI-powered trading project, developed with the objective of learning and exploring AI in trading contexts. Use of this system is at your own risk. We are not responsible for any trading decisions or outcomes associated with its use. Always conduct thorough research and consult professionals before making any financial decisions.

Goal

Increase user account value. Increase success of signal. Minimize risk.

Key Objectives (The Plan)

Maximize Account Growth: CryptoTraderAI aims to generate consistent profits and increase the overall value of your trading account. It achieves this by identifying high-potential trading opportunities and executing trades with favorable risk-reward ratios.

Intelligent Execution: With CryptoTraderAI, trades are executed in the most optimal and intelligent manner. Market conditions, liquidity, timing, and trade execution costs are carefully considered to ensure efficient and effective execution.

Signal Analysis: CryptoTraderAI employs sophisticated algorithms and machine learning techniques to analyze and evaluate trading signals. It filters out noise and identifies the strongest signals with the highest probability of success, enhancing the accuracy and reliability of your trading decisions.

Risk Management: Protecting your trading account is a top priority for CryptoTraderAI. It incorporates robust risk management strategies, including factors such as risk-reward ratio, position sizing, stop-loss levels, and diversification, to mitigate potential losses and manage risk effectively.

Continuous Learning and Improvement: CryptoTraderAI is constantly learning and adapting to changing market conditions. It leverages historical data, market trends, and user interactions to enhance its trading strategies and algorithms, ensuring continuous improvement over time.

Prerequisites

Before you begin, ensure you have met the following requirements:

• You need a TradingView account with a PRO, PRO+, or PREMIUM subscription to receive alert signals. The API endpoint /webhook will receive alerts from TradingView.

• You need a Crypto.com Exchange account to execute trades and manage your trading account. The API endpoint /order will handle the order placement and management on the Crypto.com Exchange.

Getting Started

Follow these steps to get the CryptoTraderAI up and running:

1. Clone the repository:

   git clone https://github.com/CLOVI-IO/CryptoTraderAI.git
   

2. Install the dependencies using pip:

   pip install -r requirements.txt
   

3. Set up the environment variables:

   • Create a .env file in the project root directory.
   • Open the .env file and add the necessary environment variables. Refer to the provided .env.example file for reference.

4. Run the application:

   python main.py
   

5. The application will start running and will be accessible at http://localhost:8000.

Usage

The CryptoTraderAI API provides the following endpoints:

• /webhook (POST): Receives alert signals from TradingView. Make sure to set up the webhook in your TradingView account to send alerts to this endpoint.
• /viewsignal (GET): Retrieves the last received signal from TradingView.
• /order (POST): Places an order on the Crypto.com Exchange based on the last received signal.

API Endpoints

The CryptoTraderAI API work on providing the following endpoints to access its functionality:

TODO

License

This project is licensed under the MIT License.

Contributing

Contributions are welcome! Please read the Contributing Guidelines for more information.

Support

For support or inquiries, please create an issue on the GitHub repository.

Acknowledgements

Special thanks to TradingView and Crypto.com Exchange for their services and APIs used in this project.