AI股票分析何时值得刷新？有限研究预算的分配策略
原标题：When Is Fresh AI Stock Analysis Worth It? Allocating a Limited Research Budget Across Price Updates, Deep Forecast Refreshes, and Editorial Reviews of Top Stock Picks
AI 摘要
该论文研究多智能体AI投资研究平台在有限算力预算下如何分配研究资源，基于203只股票、8120份生产报告的数据，比较了价格更新、机械路径重置和深度刷新三种策略。结果显示，在3个月持有窗口内，带波动保护的旧目标价复用策略平均收益2.25%，高于SPY的1.66%，且无需新增推理成本；但延长至近6个月不刷新则降至-11.26%，而深度刷新报告为+9.12%。研究还发现机械重置可消除98%的预测误差差距，但前10名单换手率仍达60%-90%。
正文节选
When Is Fresh AI Stock Analysis Worth It? Allocating a Limited Research Budget Across Price Updates, Deep Forecast Refreshes, and Editorial Reviews of Top Stock Picks Abstract Must long-horizon AI investment research be rewritten every time stock prices move? For multi-agent platforms covering hundreds of equities, rerunning deep reasoning workflows after every market close is costly and often redundant. Solving this resource-allocation problem is the foundational reason we built iPulse AI. Usin