Machine learning style rotation – evidence from the Johannesburg Stock Exchange

IF 2 Q2 ECONOMICS

Cogent Economics & Finance Pub Date : 2024-09-13 DOI:10.1080/23322039.2024.2402893

Daniel Page, David McClelland, Christo Auret

引用次数: 0

Abstract

This study evaluates naïve and advanced prediction models when applied to style rotation strategies on the Johannesburg Stock Exchange (‘JSE’). We apply 1- and 3-month style momentum as naïve predi...

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机器学习风格轮换--来自约翰内斯堡证券交易所的证据

本研究对约翰内斯堡证券交易所（'JSE'）的风格轮换策略应用的天真预测模型和高级预测模型进行了评估。我们采用 1 个月和 3 个月的风格动量作为天真预测模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cogent Economics & Finance ECONOMICS-

CiteScore

3.00

自引率

15.80%

发文量

309

审稿时长

12 weeks

期刊介绍： Cogent Economics & Finance, part of Taylor & Francis / Routledge, is a multidisciplinary open access journal publishing high-quality peer-reviewed research by authors from across the globe. Our inclusive nature ensures we cover the entire scope of economics and finance research – from financial economics to economic philosophy and everything in between, including replication studies – and we make sure this research is visible to everyone, anywhere, any time. Cogent Economics & Finance is headed up by an expert team of Senior Editors who, in keeping with our vision of inclusivity and sharing, evaluate submissions on scholarly merit and research integrity. Manuscripts are never rejected purely on the grounds of perceived importance or impact on the research community; article-level metrics allow the research to be assessed on its own merit.