Yuri Murayama

Event-driven hypergraph convolutional networks for financial news-based stock selection

Stock selection remains one of the most challenging tasks in quantitative trading due to the complex dependencies and dynamic nature of financial markets. Most existing studies rely on predefined inter-stock relations, which may fail to adapt to regime shifts or to incorporate short-horizon spillovers triggered by news...

Earnings forecasting by LLMs enhanced via reinforcement learning with synthetic financial reports