本研究提出一種新聞驅動的混合式自動交易框架，能將非結構化市場資訊轉化為具操作性的量化信號。該框架結合語意分析與風險評估模組，以萃取市場情緒與潛在影響因子，進而提升系統對短期波動及異常事件的即時感知與反應能力。同時，決策流程採用模組化與可擴展設計，使系統能靈活適應多變的市場條件並優化動態風險管理，顯示出新聞訊息驅動交易策略的研究潛力。;This study proposes a news-driven hybrid automated trading framework that can transform unstructured market information into actionable quantitative signals. The framework combines semantic analysis and risk assessment modules to extract market sentiment and potential impact factors, thereby enhancing the system’s real-time perception and responsiveness to short-term volatility and abnormal events. At the same time, the decision-making process adopts a modular and scalable design, enabling the system to flexibly adapt to changing market conditions and optimize dynamic risk management, demonstrating the research potential of news-driven trading strategies.
