书籍介绍
在金融科技高速发展的时代,传统的金融分析方法已经无法满足复杂多变的市场需求。这本书如同一位引领者,带领读者踏入金融机器学习的新领域,揭示了金融领域与机器学习技术结合的无限可能。
作者简介
Dr. Marcos López de Prado is a distinguished financial economist who manages multibillion-dollar funds using machine learning algorithms. A research fellow at Lawrence Berkeley National Laboratory, he is among the top-10 most read authors in finance and has authored numerous scientific articles on machine learning. Holding a PhD in Financial Economics and another in Mathematical Finance, he is a recipient of Spain's National Award for Academic Excellence. He has also contributed to algorithmic trading through patent applications and teaches a Financial ML course at Harvard and Cornell Universities.
推荐理由
《金融机器学习进展》这本书深入剖析了金融领域与机器学习技术的结合,揭示了传统金融分析方法的局限性,并提供了利用机器学习技术优化金融决策的实用路径。书中不仅涵盖了机器学习在金融领域的广泛应用,如数据挖掘、预测模型和算法,还结合实际案例和理论分析,展示了机器学习如何推动金融行业的创新与发展。
适合哪些人读
适合对金融领域和机器学习技术感兴趣的读者,尤其是金融专业人士、量化分析师、金融工程师、对机器学习在金融领域应用感兴趣的学者和学生,以及希望了解金融科技发展趋势的普通读者。
目录
About the Author
Preamble
1. Financial Machine Learning as a Distinct Subject
Part 1: Data Analysis
2. Financial Data Structures
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