YOLOFin: Research on a Novel Optimization Model in the Cryptocurrency Sector

6000

Cryptocurrency markets' volatility challenges investors as traditional models fail to predict dynamics. 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.