This project involved developing a Python-based automated trading bot for daily swing trading of Solana (SOL) on the MEXC cryptocurrency exchange. The goal was to create a bot capable of identifying profitable trading opportunities and executing trades automatically. Two distinct versions, "Venus" and "Orion," were developed to explore different decision-making approaches.

Key Contributions & Impact

• Market Data Acquisition and Analysis: Developed a system to collect real-time and historical market data from the MEXC API. This data was used to calculate various technical indicators (e.g., RSI, MACD) and identify candlestick patterns, providing crucial signals for trade decisions.
• Trading Logic Implementation (Venus): Created "Venus," a version of the bot that relies on custom-built algorithms for trade execution. This involved defining precise conditions for buy and sell orders based on the calculated technical indicators and candlestick patterns, aiming for optimal profit maximization.
• AI-Powered Decision Making (Orion): Developed "Orion," a separate version of the bot that integrates OpenAI's APIs for enhanced decision-making. This allowed for exploring the potential of AI in predicting market movements and making more informed trading choices.
• Automated Trade Execution: Successfully implemented automated trade execution on the MEXC platform, allowing the bot to place buy and sell orders without manual intervention based on the defined strategies.

Challenges & Solutions

• High Volatility and Order Execution: The high volatility of the Solana market, particularly during rapid price swings, presented a challenge. Some orders failed to execute at the intended price due to the speed of market fluctuations. Solution: Currently refining the bot's algorithms to better account for rapid price changes, potentially incorporating techniques like limit orders with adjusted parameters or more sophisticated order placement strategies. Exploring faster execution methods and API optimization.
• API Integration and Rate Limits: Interacting with both the MEXC API (for market data and trading) and the OpenAI API required careful handling of API rate limits and potential connection issues. Solution: Implemented robust error handling and retry mechanisms to manage API rate limits and ensure data consistency. Optimized API calls to minimize latency and maximize efficiency.

Lessons Learned

• Understanding of Cryptocurrency Market Dynamics: Gained a deeper understanding of the intricacies of the cryptocurrency market, including volatility, liquidity, and the impact of various factors on price movements.
• Practical Application of Technical Analysis: Developed practical skills in applying technical analysis techniques, including the use of indicators and candlestick patterns, for making data-driven trading decisions.
• Experience with API Integration: Gained hands-on experience integrating with multiple APIs, including handling authentication, rate limits, and data parsing.
• Importance of Continuous Refinement: Recognized the need for continuous testing, refinement, and adaptation in the development of automated trading systems, particularly in dynamic and volatile markets.
• Exploration of AI in Trading: Gained initial experience in leveraging AI for financial decision-making, opening avenues for further exploration of AI-powered trading strategies.