The present study compares the Fama-French three factor coefficient estimates obtained from both ordinary least squares (OLS) and quantile regression for 25 size-value sorted portfolios of BSE 500. The study, using empirical results, residual graphs and other plots, confirms the inefficiency of OLS in end distribution estimation. Quantile regression reveals that the slope direction for all coefficients of predictor variables is not the same across the quantiles and time. Finally, the study shows, empirically, that quantile regression estimates give a more comprehensive and clearer picture of the varying effect of predictors on response variables to analysts or investors in making investment decisions.

本研究比较了从普通最小二乘法 (OLS) 和分位数回归获得的 Fama-French 三因子系数估计值，用于 BSE 500 的 25 个大小值排序投资组合。该研究使用实证结果、残差图和其他图，证实了OLS 在末端分布估计中的低效率。分位数回归表明预测变量的所有系数的斜率方向在分位数和时间上并不相同。最后，该研究根据经验表明，分位数回归估计可以更全面、更清晰地了解预测变量对分析师或投资者在做出投资决策时的响应变量的不同影响。