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Advances in Financial Machine Learning

Advances in Financial Machine Learning

作者：Marcos Lopez de Prado

分类：生活

ISBN：9781119482086

出版时间：2018-2-22

出版社：John Wiley & Sons

标签： 金融 

章节目录

About the Author
Preamble
1. Financial Machine Learning as a Distinct Subject
Part 1: Data Analysis
2. Financial Data Structures
3. Labeling
4. Sample Weights
5. Fractionally Differentiated Features
Part 2: Modelling
6. Ensemble Methods
7. Cross-validation in Finance
8. Feature Importance
9. Hyper-parameter Tuning with Cross-Validation
Part 3: Backtesting
10. Bet Sizing
11. The Dangers of Backtesting
12. Backtesting through Cross-Validation
13. Backtesting on Synthetic Data
14. Backtest Statistics
15. Understanding Strategy Risk
16. Machine Learning Asset Allocation
Part 4: Useful Financial Features
17. Structural Breaks
18. Entropy Features
19. Microstructural Features
Part 5: High-Performance Computing Recipes
20. Multiprocessing and Vectorization
21. Brute Force and Quantum Computers
22. High-Performance Computational Intelligence and Forecasting Technologies
Dr. Kesheng Wu and Dr. Horst Simon
Index

内容简介

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.

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热门评论

  • 阿道克的评论
    神作，需要N刷。核心是讨论一般机器学习方法在金融时间序列这种特定数据类型上应用的一些问题，比如交叉验证、回测过拟合等等。不是讲策略开发或者投资方法的书。大部分内容作者都发表过，可以看作者主页http://www.quantresearch.info/或者SSRN。
  • 志PENG哥的评论
    我就是这条gai最量的仔
  • Cat Helix的评论
    贵司真的就靠这本书赚到钱吗？我拭目以待
  • Chon的评论
    AQR的head of machine learning
  • 子珂的评论
    翻过一点点。主要是讲量化
  • 本杰明的评论
    购买链接：https://item.taobao.com/item.htm?spm=0.7095261.0.0.71a11debf7UsVf&id=568847882964
  • 瀛台的评论
    呵呵，基本看不懂
  • Foe的评论
    很多想法还是很少见的，挺有参考价值的
  • 哈蛤铪哈的评论
    还是蛮神奇的书，，很多部分说是论文改的，主要处理金融时间序列分析，想把这里头的方法实现一下，这学期的计量论文就有着落了。
  • 浮生会少的评论
    提到的分析都很实际， 虽然理论部分有难度，但是仅仅思路就很值得借鉴
  • henryu￥拉丝裤的评论
    就刚刚入门的水平吧。。。
  • SS的评论
    实习中阅读并实践了书里的一些内容，忍不住感叹：Masterpiece！
  • 穿刺狗的评论
    神书，有很多学术文章，其他书籍里见不到的方法手段，即使不做machine learning，里面研究的方法也很有可借鉴的地方
  • 小号冲锋的评论
    第一遍
  • Luque的评论
    神作 自己也在写这本书的读书笔记博客
  • NightShade的评论
    这本书的重点在advances 想看机器学习的还是换其他的看吧

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