发表于2025-04-06
DR. MARCOS LÓPEZ DE PRADO manages several multibillion-dollar funds for institutional investors using ML algorithms. Marcos is also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). One of the top-10 most read authors in finance (SSRN's rankings), he has published dozens of scientific articles on ML in the leading academic journals, and he holds multiple international patent applications on algorithmic trading. Marcos earned a PhD in Financial Economics (2003), a second PhD in Mathematical Finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a Financial ML course at the School of Engineering. Marcos has an Erdös #2 and an Einstein #4 according to the American Mathematical Society.
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Advances in Financial Machine Learning 下载 mobi pdf epub txt 电子书 格式 2025
Advances in Financial Machine Learning 下载 mobi epub pdf 电子书##全书废话,而且大小错误一大把,叙事没有前因后果,读到最后完全无法相信这个人。浪费时间。 扫码关注公众号 「图灵的猫」,点击“学习资料”菜单,可以获得海量python、机器学习、深度学习书籍、课程资源,以及书中对应习题答案和代码。后台回复SSR更有机场节点相送~ 入门避坑指南 自学三年,基本无人带路,转专业的我自然是难上加难,踩过无数坑,走过很多弯路。这里我...
评分##以自己从事相关工作虽不短仍浅薄的经验,这是一本在量化投资有框架有总结有细节有诚意的书。作者并没有在最top的公司(AQR虽在中国有名声,但并不是这行业最前沿的地方)有过成功实战经验,即使有他也不会写出书来,却有实践结合理论的认知。不要期待在书里找到策略最核心的东西,但是框架和应有的态度执行力已经很重要。其他在于悟性努力,平台,和运气。 谁不期待年少成名,难的是在领域高峰之时,能坚持不停止好奇心求知欲。与其用某些方法取得他人的策略回到国内赚钱,不如扎实去理解一个领域里的核心和渐进过程。由out smart他人到out smart狭隘的自己。
评分 评分##以自己从事相关工作虽不短仍浅薄的经验,这是一本在量化投资有框架有总结有细节有诚意的书。作者并没有在最top的公司(AQR虽在中国有名声,但并不是这行业最前沿的地方)有过成功实战经验,即使有他也不会写出书来,却有实践结合理论的认知。不要期待在书里找到策略最核心的东西,但是框架和应有的态度执行力已经很重要。其他在于悟性努力,平台,和运气。 谁不期待年少成名,难的是在领域高峰之时,能坚持不停止好奇心求知欲。与其用某些方法取得他人的策略回到国内赚钱,不如扎实去理解一个领域里的核心和渐进过程。由out smart他人到out smart狭隘的自己。
评分##除了HPC的内容都看了,对于金融任务的特定理解非常值得学习!感觉先看这本书可以少踩很多弯路了。
评分 评分##1)启发性的话题给的多,但是解决问题的方法给了一半,浅尝辄止 2)符号标注或者解释不清晰,举例也不清楚,本身一个实例就可以解释清楚的,但是没有。 优点就是,此类书很少,他提到的很多点给我以启发。总体上我觉得这本书值得一读的。 2018-01-05想读
评分##翻过一点点。主要是讲量化
Advances in Financial Machine Learning mobi epub pdf txt 电子书 格式下载 2025