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Quantile regression, asset pricing and investment decision

机译:分数回归,资产定价和投资决策

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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.
机译:本研究比较了来自普通最小二乘(OLS)和分量回归的FAMA-French三因素系数估计,以及25个尺寸值的BSE 500的分类组合。研究,使用经验结果,残余图形和其他地块,证实了 ELS在结束分布估计中的效率低下。 分位数回归揭示了预测器变量的所有系数的斜向方向在横跨量子和时间之间不相同。 最后,该研究证明,定量回归估计估计提供了更加全面和更清楚地描绘了预测因子对分析师或投资者进行投资决策的响应变量的变化。

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