Mining High-Frequency Risk Factor Collections End-to-End via Transformer for Improved Quantitative Trading

This paper introduces IRFT, a novel Transformer-based model that automates the mining of high-frequency risk factors from stock data, outperforming existing methods in both accuracy and speed, and demonstrating significant potential for enhancing quantitative trading strategies.