AI-Powered Cryptocurrency Trading Enhancing Decision-Making and Market Predictions

Abstract

Cryptocurrency trading has become sophisticated by the day as market volatility and information are continuously enhanced. The reliance of traditional trading systems on historical data and human prediction result in inefficiency and risk for both investors and stockbrokers. The paper provides Imagine using Artificial Intelligence for trading cryptocurrency, which can provide better results than human trading. The machine learning-based approach uses real-time information, whether it be a buy or sell action, while considering real-time information such as social media for sentiment analysis, and adapting trading to achieve better results. The model will use advanced machine learning models including supervised, unsupervised learning, exploratory models, and reinforcement learning to provide tangible results such as improved accuracy in predicting price and sentiment analysis. The results show that the model has significantly improved its efficiency and performance, yielding a Root Mean Squared Error of 0.032 and a Sharpe Ratio of 2.1. These means that it has demonstrated the capability to yield superior risk-adjusted returns and higher reliability, making it a perfect alternative for investors.