{"title":"Fama and French three and six-factor models: Evidence from Indian stock exchange","authors":"H. R. Tejesh, V. Jeelan Basha","doi":"10.1142/s2424786323500172","DOIUrl":null,"url":null,"abstract":"This study attempts to compare the performance of Fama–French three-factor model (FFTFM) and Fama and French six-factor model (FFSFM) in predicting the variations in expected returns of Nifty-100 listed stocks. Only 5/6 of the total listed companies are chosen, while the remaining 1/6 are ignored because they are not listed for the whole study period. The stocks are divided into two size groups and three groups based on B/M, OP, Inv and MOM using independent sorts to create 24 portfolios. The monthly average returns of the MC-MOM portfolios increase as momentum increases, in contrast to MC-B/M and MC-Inv portfolios. Almost all the portfolios with high returns are paired with significant risk, apart from the BM portfolio in size and profitability group. The findings prove that the FFSFM outperforms FFTFM on all the GRS test parameters. However, there is no significant improvement in explanatory power over the FFTFM.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Financial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s2424786323500172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
This study attempts to compare the performance of Fama–French three-factor model (FFTFM) and Fama and French six-factor model (FFSFM) in predicting the variations in expected returns of Nifty-100 listed stocks. Only 5/6 of the total listed companies are chosen, while the remaining 1/6 are ignored because they are not listed for the whole study period. The stocks are divided into two size groups and three groups based on B/M, OP, Inv and MOM using independent sorts to create 24 portfolios. The monthly average returns of the MC-MOM portfolios increase as momentum increases, in contrast to MC-B/M and MC-Inv portfolios. Almost all the portfolios with high returns are paired with significant risk, apart from the BM portfolio in size and profitability group. The findings prove that the FFSFM outperforms FFTFM on all the GRS test parameters. However, there is no significant improvement in explanatory power over the FFTFM.