A crypto trading bot designed for the TradeOgre exchange.

This trading bot is designed to automate trading on the TradeOgre exchange. It utilizes a sophisticated strategy combining a SSL (Support and Stop Loss) hybrid indicator with a slope indicator for efficient and effective trading decisions. Built in Rust, this bot offers exceptional performance and speed. Additionally, it leverages a vector store database for rapid data retrieval and management, ensuring quick response to market changes.

• SSL Hybrid Indicator: Combines support and resistance levels with stop-loss functionality for informed trading decisions.
• Slope Indicator: Helps in determining the trend's direction and strength, enhancing the decision-making process.
• TradeOgre Exchange Integration: Directly interfaces with TradeOgre's API for seamless trading.
• Vector Store Database: Utilizes a high-performance database for fast data access and storage.
• High-Speed Performance: Written in Rust, known for its speed and memory efficiency.
• Automatic Trading: Automates the trading process, from analysis to execution.

• Rust (latest stable version)
• API keys from TradeOgre
• Basic understanding of trading and cryptocurrency markets

1. Clone the repository:

   git clone [repository URL]

2. Navigate to the project directory:

   cd [project directory]

3. Build the project:

   cargo build --release

4. Configuration

   cargo run --generate-config

   Update config.toml with your TradeOgre API keys and other relevant configurations.

5. Usage To run the trading bot, use the following command:

   cargo run config.toml

This bot uses a combination of SSL hybrid and slope indicators. The SSL hybrid indicator identifies support and resistance levels, while the slope indicator determines the trend direction. The bot enters a trade when both indicators align, ensuring a high probability of success.

Please note that trading cryptocurrencies involves significant risk. This bot does not guarantee profits and should be used with caution. Always test trading strategies in a simulated environment before deploying real capital.

Contributions are welcome! Please fork the repository and submit a pull request with your proposed changes.

This project is licensed under MIT - see the LICENSE file for details.