本书面向广大资产管理者和各类研究人员,基于机器学习和人工智能,指明从一个投资理念和理论到成功的投资策略具体实施的量化途径。作者认为一个缺乏理论依据的投资策略很可能是错误的。为此,资产管理者应致力于发展理论,而不仅是回测潜在的交易规则。本书就是从帮助资产管理者发现经济和金融理论的角度出发,介绍机器学习的工具。机器学习不是一个黑匣子,也不一定会过拟合。机器学习的工具与经典统计方法是互补关系而不是替代关系。本书认为机器学习的一些优点包括:注重样本外的可预测性,而不是样本内的方差判断;使用计算方法避免依赖一些(或许不切实际的)假设;能够“学习”复杂的规范,包括高维空间中的非线性、分层和非连续的交互效应;能够将变量搜索与设定搜索分离,并能很好地防止多重线性和其他替代效应。
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Seller: liu xing, Nanjing, JS, China
Hardcover. Condition: New. HardCover.Pub Date:2022-02-01 Pages:248 Language:Chinese Publisher:Machinery Industry Press This book is aimed at asset managers and researchers of all kinds. Based on machine learning and artificial intelligence. it points out that from an investment concept and theory to A quantitative approach to the concrete implementation of successful investment strategies. The author believes that an investment strategy that lacks theoretical basis is likely to be wrong. To this end. asset managers sho. Seller Inventory # NX014270
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