{"title":"投资组合特征的因子择时","authors":"Anastasios Kagkadis, Ingmar Nolte, Sandra Nolte, Nikolaos Vasilas","doi":"10.1093/rapstu/raad010","DOIUrl":null,"url":null,"abstract":"Abstract In a factor timing context, academic research has focused on identifying a set of predictors that can explain the dynamics of factor portfolios. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce the number of both predictors and portfolios to predict. Characteristic-based models outperform existing methods in terms of exact predictability, as well as investment performance. (JEL G10, G11, C52, C55) Received November 9, 2021; editorial decision March 23, 2023 by Editor Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"1 1","pages":"0"},"PeriodicalIF":2.2000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Factor Timing with Portfolio Characteristics\",\"authors\":\"Anastasios Kagkadis, Ingmar Nolte, Sandra Nolte, Nikolaos Vasilas\",\"doi\":\"10.1093/rapstu/raad010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In a factor timing context, academic research has focused on identifying a set of predictors that can explain the dynamics of factor portfolios. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce the number of both predictors and portfolios to predict. Characteristic-based models outperform existing methods in terms of exact predictability, as well as investment performance. (JEL G10, G11, C52, C55) Received November 9, 2021; editorial decision March 23, 2023 by Editor Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.\",\"PeriodicalId\":21144,\"journal\":{\"name\":\"Review of Asset Pricing Studies\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2023-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Asset Pricing Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/rapstu/raad010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Asset Pricing Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/rapstu/raad010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Abstract In a factor timing context, academic research has focused on identifying a set of predictors that can explain the dynamics of factor portfolios. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce the number of both predictors and portfolios to predict. Characteristic-based models outperform existing methods in terms of exact predictability, as well as investment performance. (JEL G10, G11, C52, C55) Received November 9, 2021; editorial decision March 23, 2023 by Editor Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
期刊介绍：
The Review of Asset Pricing Studies (RAPS) is a journal that aims to publish high-quality research in asset pricing. It evaluates papers based on their original contribution to the understanding of asset pricing. The topics covered in RAPS include theoretical and empirical models of asset prices and returns, empirical methodology, macro-finance, financial institutions and asset prices, information and liquidity in asset markets, behavioral investment studies, asset market structure and microstructure, risk analysis, hedge funds, mutual funds, alternative investments, and other related topics.
Manuscripts submitted to RAPS must be exclusive to the journal and should not have been previously published. Starting in 2020, RAPS will publish three issues per year, owing to an increasing number of high-quality submissions. The journal is indexed in EconLit, Emerging Sources Citation IndexTM, RePEc (Research Papers in Economics), and Scopus.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
