Overall, the size disaggregation effort in Table 5 lends further credence to our interpretation of the evidence. It makes it clear that the earlier numbers in Table 4 are not an artifact of imperfect size matching in the full sample. And it is comforting to know that analyst coverage has more of an impact on momentum in precisely those parts of the size distribution where one a priori suspects that gradual information diffusion is likely to be important and where momentum effects are most pronounced to begin with.
Table 5 also helps put into perspective the extent to which firm size and residual coverage might each be capturing something related to the phenomenon of gradual information flow. On the one hand, it is natural to focus most of the attention on residual coverage as a proxy for this phenomenon-it makes for a cleaner test of our hypothesis because it is less likely than size to be bringing in other confounding factors. But in gauging the quantitative significance of the results, it is important to recognize that, if we hold size fixed, we cannot hope to capture the full magnitude of any gradual-information-flow effect.
To be specific, return to the results for the smallest set of firms in Table 5–those in the 20th-40th percentile range. Among these firms, those with the fewest analysts have momentum of 1.51 % per month; those with the most analysts have momentum of 1.15% per month. While the difference of 0.36% is good-sized, it is still just a fraction of the total momentum effect. One reading of this might be that gradual information diffusion can only “explain” a fraction of the overall momentum in stock returns. However, such an inference is at best superficial. Recall that even the most heavily-covered stocks in this class have only three or four analysts, and only average $60 million in market cap. Thus they might naturally be expected to have slower information diffusion than, say, a $10 billion company with 25 analysts. The bottom line is that residual analyst coverage, viewed in isolation, is unlikely to provide a full picture of the importance of gradual information flow. This is where the cuts on raw size in Tables 3 and 5 add potentially useful evidence.