Fama and French three and six-factor models: Evidence from Indian stock exchange

IF 0.6 Q4 BUSINESS, FINANCE International Journal of Financial Engineering Pub Date : 2023-07-20 DOI:10.1142/s2424786323500172
H. R. Tejesh, V. Jeelan Basha
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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.
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Fama和French的三因素和六因素模型:来自印度证券交易所的证据
本研究试图比较Fama - French三因素模型(FFTFM)和Fama - French六因素模型(FFSFM)在预测Nifty-100上市公司股票预期收益变化方面的表现。只有5/6的上市公司被选中,而剩下的1/6被忽略,因为它们在整个研究期间都没有上市。股票被分为两个大小组和三个组基于B/M, OP, Inv和MOM使用独立排序创建24个投资组合。MC-MOM组合的月平均收益随着动量的增加而增加,与MC-B/M和MC-Inv组合相反。除了规模和盈利能力方面的BM投资组合外,几乎所有高回报的投资组合都伴随着重大风险。结果表明,FFSFM在所有GRS测试参数上都优于FFTFM。然而,与FFTFM相比,解释力没有显著提高。
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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