Non-standard errors in asset pricing: Mind your sorts
研究发现资产定价因子模型的研究设计选择差异导致非标准误差，其与标准误差之比平均超过1；改用NAN断点排序可将夏普比率从0.46提升至0.63，其他关键选择包括剔除微盘股、行业调整和再平衡频率。
Non-standard errors capture variation due to differences in research design choices. We document large variation in design choices in the context of asset pricing factor models and find that the average ratio of the non-standard error to the standard error across factors exceeds one. Using NAN breakpoints instead of NYSE breakpoints improves the average Sharpe ratios the most, from 0.46 to 0.63. Other important design choices relate to excluding microcaps, industry-adjusting, and the rebalancing frequency, which highlights the need for researchers to clearly describe and motivate these choices.