摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据新闻报道NewsRx记者从中华人民共和国苏州报道，研究称，随着金融领域对机器学习(ML)方法的日益依赖，对其长期发展的理解其有效性和潜在机制有待进一步研究。我们记录了不同的时间变化的重要性18年（1998-201 6）样本外期的库存特征，以确定ML模型是否，当在大量的公司和交易特征上接受培训时，可以持续优于要素模式LS。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating from Suzhou, Peop le’s Republic of China, by NewsRx correspondents, research stated,“With the gro wing reliance on machine-learning (ML) methods in finance, an understanding of t heir longtermefficacy and underlying mechanism is needed. We document the time -varying importance of differentstock characteristics over an 18-year (1998-201 6) out-of-sample period to determine whether ML models,when trained on a large set of firm and trading characteristics, can consistently outperform factor models.”
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NSTL