中国因素模型比较

IF 2.1 2区 经济学 Q2 BUSINESS, FINANCE
Jinzhe Wang, Yifeng Zhu
{"title":"中国因素模型比较","authors":"Jinzhe Wang,&nbsp;Yifeng Zhu","doi":"10.1016/j.jempfin.2024.101548","DOIUrl":null,"url":null,"abstract":"<div><p>We evaluate the performance of eleven asset pricing models in the Chinese A-share market using a variety of test portfolios and statistical methodologies. To compile the test portfolios, we construct 105 anomalies and use the 23 significant anomalies as test assets for model comparison. The results indicate that, in time-series test and anomaly explanations, the Hou et al. (2019) five-factor <em>q</em> model demonstrates the best overall performance. The pairwise cross-sectional <span><math><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup></math></span> tests and multiple model comparison tests further affirm that the Hou et al. (2019) five-factor <em>q</em> model, the Fama and French (2018) six-factor (FF6) model, and the Kelly et al. (2019) five-factor Instrumented Principal Component Analysis (IPCA5) model are the top performers. Notably, the performance of the five-factor <em>q</em> model remains robust across various experimental designs.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"79 ","pages":"Article 101548"},"PeriodicalIF":2.1000,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comparison of factor models in China\",\"authors\":\"Jinzhe Wang,&nbsp;Yifeng Zhu\",\"doi\":\"10.1016/j.jempfin.2024.101548\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We evaluate the performance of eleven asset pricing models in the Chinese A-share market using a variety of test portfolios and statistical methodologies. To compile the test portfolios, we construct 105 anomalies and use the 23 significant anomalies as test assets for model comparison. The results indicate that, in time-series test and anomaly explanations, the Hou et al. (2019) five-factor <em>q</em> model demonstrates the best overall performance. The pairwise cross-sectional <span><math><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup></math></span> tests and multiple model comparison tests further affirm that the Hou et al. (2019) five-factor <em>q</em> model, the Fama and French (2018) six-factor (FF6) model, and the Kelly et al. (2019) five-factor Instrumented Principal Component Analysis (IPCA5) model are the top performers. Notably, the performance of the five-factor <em>q</em> model remains robust across various experimental designs.</p></div>\",\"PeriodicalId\":15704,\"journal\":{\"name\":\"Journal of Empirical Finance\",\"volume\":\"79 \",\"pages\":\"Article 101548\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Empirical Finance\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0927539824000823\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Empirical Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0927539824000823","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

摘要

我们使用各种测试组合和统计方法评估了 11 个资产定价模型在中国 A 股市场中的表现。为了编制测试组合,我们构建了 105 个异常值,并将 23 个显著异常值作为测试资产进行模型比较。结果表明,在时间序列测试和异常解释中,Hou 等(2019 年)的五因子 q 模型表现出最佳的整体性能。成对横截面 R2 检验和多模型比较检验进一步证实,Hou 等(2019 年)的五因子 q 模型、Fama 和 French(2018 年)的六因子(FF6)模型以及 Kelly 等(2019 年)的五因子工具化主成分分析(IPCA5)模型表现最佳。值得注意的是,在各种实验设计中,五因子 q 模型的表现依然稳健。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comparison of factor models in China

We evaluate the performance of eleven asset pricing models in the Chinese A-share market using a variety of test portfolios and statistical methodologies. To compile the test portfolios, we construct 105 anomalies and use the 23 significant anomalies as test assets for model comparison. The results indicate that, in time-series test and anomaly explanations, the Hou et al. (2019) five-factor q model demonstrates the best overall performance. The pairwise cross-sectional R2 tests and multiple model comparison tests further affirm that the Hou et al. (2019) five-factor q model, the Fama and French (2018) six-factor (FF6) model, and the Kelly et al. (2019) five-factor Instrumented Principal Component Analysis (IPCA5) model are the top performers. Notably, the performance of the five-factor q model remains robust across various experimental designs.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.40
自引率
3.80%
发文量
59
期刊介绍: The Journal of Empirical Finance is a financial economics journal whose aim is to publish high quality articles in empirical finance. Empirical finance is interpreted broadly to include any type of empirical work in financial economics, financial econometrics, and also theoretical work with clear empirical implications, even when there is no empirical analysis. The Journal welcomes articles in all fields of finance, such as asset pricing, corporate finance, financial econometrics, banking, international finance, microstructure, behavioural finance, etc. The Editorial Team is willing to take risks on innovative research, controversial papers, and unusual approaches. We are also particularly interested in work produced by young scholars. The composition of the editorial board reflects such goals.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信