Development of YOLOFin: An Advanced YOLO-Based Optimization Framework for Financial Trading

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Cryptocurrency markets are too volatile for traditional methods to predict.This project proposes YOLOFin, a novel (You Only Look Once) YOLO-based trading optimization model, pioneering its use in cryptocurrency analysis. Leveraging YOLOv8, it classifies financial data and predicts price trends for major cryptocurrencies (BTC, ETH, BNB, XRP). By integrating image-processing techniques to capture multi-term trends, YOLOFin facilitates adaptive strategies. Unlike accuracy-focused models, YOLOFin balances classification accuracy with robust compound annual growth rate (CAGR), addressing volatility and long-term profitability gaps. Students learn practical solution for navigating uncertain crypto markets, providing a robust tool for investors.