基于多因素模型的基本定量投资理论与技术体系

Li Zhao, Nathee Naktnasukanjn, Lei Mu, Haichuan Liu, Heping Pan
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引用次数: 0

摘要

随着资本市场和智能金融技术的不断发展,量化投资正进入最关键、最具挑战性的领域——基本面量化投资。到目前为止,量化投资主要集中在技术分析和交易的自动化上,而基本面投资在很大程度上是自由裁量的。本文对定量投资和基本投资进行了概述,建立了基于多因素模型的基本定量投资理论和技术体系。我们首先回顾了现代金融量化投资和基础投资的相关文献。然后,我们介绍了多因素模型的理论基础和发展及其在股票选择中的应用,包括线性和非线性关系、机器学习、深度学习与神经网络、随机森林和支持向量机(svm)。我们将探索基础量化投资的前沿,并展望未来的研究前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fundamental Quantitative Investment Theory and Technical System Based On Multi-Factor Models
Along with the continuous development of capital markets and intelligent finance technologies, quantitative investment is entering into the most critical and challenging area – fundamental quantitative investment. So far, quantitative investment has been focused on automation of technical analysis and trading, while fundamental investment has been large discretionary. This paper provides an overview of quantitative investment and fundamental investment towards a fundamental quantitative investment theory and technical system based on multi-factor models. We start with reviewing relevant literature on modern financial quantitative investment and fundamental investment. Then we cover the theoretical basis and development of multi-factor models and their applications for stock selection, involving linear and non-linear relationships, machine learning, deep learning with neural networks, random forests, and Support Vector Machines (SVMs). We explore the frontiers of fundamental quantitative investment and shed light on the future research prospects.
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