金融中的机器学习:主要应用、问题、指标和未来趋势

IF 0.6 Q4 BUSINESS, FINANCE
Nawaf Almaskati
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引用次数: 1

摘要

本文总结了当前与在金融领域应用机器学习算法相关的文献,重点关注三个主要领域:资产定价、破产预测和财务报告异常检测。本文还简要讨论了金融中最流行的机器学习技术,并提供了一些重要概念的总体概述,如泛化和过拟合和欠拟合,以及潜在补救措施的讨论。最后,本文总结了各种可用来评估和比较回归和分类机器学习模型性能的指标和度量,然后讨论了一般的研究趋势和潜在的未来研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning in finance: Major applications, issues, metrics, and future trends
This paper provides a summary of the current literature related to applying machine learning algorithms in the field of finance with a focus on three main areas: asset pricing, bankruptcy prediction and detection of financial reporting anomalies. The paper also briefly discusses the most popular machine learning techniques used in finance and provides a general overview of some important concepts such as generalization and over- and under-fitting as well as a discussion of potential remedies. Last, the paper summarizes the various indicators and metrics available to evaluate and compare the performance of regression and classification machine learning models before discussing general research trends and potential future research.
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