AI Powered Real Time Crypto Currency Price Disparancy Scanner

The cryptocurrency market is highly fragmented, with trades taking place on multiple centralized and decentralized exchanges. This fragmentation, coupled with differences in liquidity, trading volume, transaction costs, and network conditions, often results in temporary discrepancies in the price of the same cryptocurrency. The identification of potential arbitrage opportunities in this volatile and rapidly moving market is a huge challenge when real-world constraints are not considered. This study proposes a smart real-time system for identifying and analyzing the differences in cryptocurrency prices using a hybrid artificial intelligence approach. The proposed method integrates Long Short- Term Memory (LSTM) networks for analyzing price variations over time, Autoencoders and Isolation Forests for identifying anomalies in an unsupervised manner, Gradient Boosting for filtering profitable trades, and Reinforcement Learning for improving decision-making. The proposed system retrieves real-time prices from different centralized and decentralized exchanges and analyzes arbitrage opportunities by considering transaction costs, blockchain network charges, and transfer times. Experiments conducted on multi-exchange price data, data from decentralized exchanges, and blockchain network data reveal that the proposed system significantly improves the accuracy of detection and suppresses false positives compared to the conventional rule-based and single-model approaches. By integrating multiple AI approaches with real-world market assumptions, this system provides a scalable and realistic solution for cryptocurrency arbitrage detection and market analysis using AI.