{"title":"股票特征和股票收益的实际应用:对预期收益横截面的怀疑","authors":"Bradford Cornell","doi":"10.3905/pa.8.2.411","DOIUrl":null,"url":null,"abstract":"In Stock Characteristics and Stock Returns: A Skeptic’s Look at the Cross Section of Expected Returns, in the July 2020 multi-asset special issue of The Journal of Portfolio Management, Bradford Cornell of the University of California in Los Angeles (UCLA) questions the dependability, and thus the investment utility, of correlations between stock characteristics and anticipated returns. How much can really be known about these relationships? His answer is, very little. Because these characteristics do not persist or recur predictably, any observed correlation between them and the future changes in average returns across asset classes has only limited practical use. Cornell identifies several impediments that undermine the reliability of stock characteristics as predictors of returns—including nonpersistence, model uncertainty, data snooping, and, especially, nonstationarity. These conditions make it difficult for investors to discern the real drivers of returns and to confidently forecast returns and relative future risk. The author advises market participants to be wary of investment approaches, including smart beta, that assume robust correlations between characteristics and future returns. TOPICS: Portfolio management/multiasset allocation, performance measurement","PeriodicalId":179835,"journal":{"name":"Practical Application","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Practical Applications of Stock Characteristics and Stock Returns: A Skeptic’s Look at the Cross Section of Expected Returns\",\"authors\":\"Bradford Cornell\",\"doi\":\"10.3905/pa.8.2.411\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Stock Characteristics and Stock Returns: A Skeptic’s Look at the Cross Section of Expected Returns, in the July 2020 multi-asset special issue of The Journal of Portfolio Management, Bradford Cornell of the University of California in Los Angeles (UCLA) questions the dependability, and thus the investment utility, of correlations between stock characteristics and anticipated returns. How much can really be known about these relationships? His answer is, very little. Because these characteristics do not persist or recur predictably, any observed correlation between them and the future changes in average returns across asset classes has only limited practical use. Cornell identifies several impediments that undermine the reliability of stock characteristics as predictors of returns—including nonpersistence, model uncertainty, data snooping, and, especially, nonstationarity. These conditions make it difficult for investors to discern the real drivers of returns and to confidently forecast returns and relative future risk. The author advises market participants to be wary of investment approaches, including smart beta, that assume robust correlations between characteristics and future returns. TOPICS: Portfolio management/multiasset allocation, performance measurement\",\"PeriodicalId\":179835,\"journal\":{\"name\":\"Practical Application\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Practical Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3905/pa.8.2.411\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Practical Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/pa.8.2.411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Practical Applications of Stock Characteristics and Stock Returns: A Skeptic’s Look at the Cross Section of Expected Returns
In Stock Characteristics and Stock Returns: A Skeptic’s Look at the Cross Section of Expected Returns, in the July 2020 multi-asset special issue of The Journal of Portfolio Management, Bradford Cornell of the University of California in Los Angeles (UCLA) questions the dependability, and thus the investment utility, of correlations between stock characteristics and anticipated returns. How much can really be known about these relationships? His answer is, very little. Because these characteristics do not persist or recur predictably, any observed correlation between them and the future changes in average returns across asset classes has only limited practical use. Cornell identifies several impediments that undermine the reliability of stock characteristics as predictors of returns—including nonpersistence, model uncertainty, data snooping, and, especially, nonstationarity. These conditions make it difficult for investors to discern the real drivers of returns and to confidently forecast returns and relative future risk. The author advises market participants to be wary of investment approaches, including smart beta, that assume robust correlations between characteristics and future returns. TOPICS: Portfolio management/multiasset allocation, performance measurement