(1.13%) for the highest and 0.85% (0.81%) for the lowest BE/ME quintile across all firms, and 0.99% (1.04%) and 0.57% (0.51%), respectively, within large firms. However, there seems to be no association between BE/ME and returns within small firms. For example, average equal- (value-) weighted monthly stock return is 1.51% (1.41%) and 1.58% (1.46%) for the highest and the lowest BE/ME quintile within small firms, respectively. This evidence seems to contradict the previous finding that the value effect is strongest among small firms. Moreover, stocks tend to consistently outperform large stocks in our sample. For instance, average equal- (value-) weighted monthly stock returns are 1.46% (1.36%) for the smallest and 0.82% (0.85%) for the largest quintile across all firms, 1.58% (1.46%) and 0.57% (0.51%), respectively, within the low-BE/ME quintile, and 1.51% (1.41%) and 0.99% (1.04%), respectively, within the quintile. In Table 2 and graphically in Figure 2, we report AdjDITH estimates by BE/ME and size groups. A clear negative association exists between AdjDITH and BE/ME. Unconditionally, AdjDITH estimates decrease monotonically from 0.38% to -0.04% as BE/ME increases from the lowest to the highest quintile. Depending on the market value, AdjDITH estimates decrease from 0.23% to 0.03% across BE/ME quintiles within small stocks and from 0.24% to 0.11% across BE/ME quintiles within large stocks. However, there seems to be a weak positive association between AdjDITH and size. <Insert Table 2 and Figure 2 about here> As for individual trading in Table 2 and graphically in Figure 3, there is evidence of a positive association between AdjDIND and BE/ME. Unconditionally, AdjDIND estimates increase monotonically from -0.67% to 0.73% as BE/ME
stratified portfolio that shows a largest increase in institutional (or individual) ownership. Similarly, firms within each of the other nine portfolios are re-aggregated in the same manner. In Table 5, we report the average monthly stock returns by deciles based on adjusted changes in institutional ownership (AdjDITH). The portfolios are constructed to isolate them from any possible influence of level of institutional ownership. This sorting procedure produces 10 portfolios with similar institutional ownership levels. Similar to Kim and Nofsinger (2005), the average level of shares held by all institutions is about 61%. The average ownership of individual investors is around 32%. The reported returns are the monthly averages in the 12 months following each June. The portfolio returns are equal and value weighted. We adopt two methods to adjust the monthly stock returns. First, we measure the abnormal returns for each portfolio with the intercept of the Carhart (1997) four-factor model. The second method is the benchmark-adjusted procedure. Abnormal returns are calculated using size- and BE/ME-adjusted average portfolio returns. To construct the benchmark portfolios, we independently sort whole-listed stocks into size and BE/ME deciles. Next, we compute a monthly value-weighted average return for each of the 100 (10 x 10) portfolios. The monthly abnormal return for each stock is the difference between the stock’s monthly raw return and its monthly benchmark portfolio return. Evidence indicates that the with higher AdjDITH earn lower subsequent returns. Equal- (value-) weighted monthly raw returns decrease from an average of 1.12% (0.90%) for the lowest to 0.66% (0.45%) for the highest AdjDITH decile. The equal- (value-) weighted average of the monthly raw return difference between stocks in the highest decile and stocks in the lowest decile is -0.46% (-0.45%), which is
significantly different from zero at the 1% level. Moreover, the four-factor model risk-adjusted returns and benchmark-adjusted returns show similar results. That is, institutional trading is significantly and negatively related to future stock returns. Moreover, consistent with the results in the previous section, Panel B of Table 5 shows that the BE/ME of net-selling portfolio (P01) is higher than that of net-buying portfolio (P10). Moreover, there is a negative relationship between AdjDIND and AdjDITH. There seems to be no clear association between AdjDITH and size. AdjDITH is also positively associated with prior returns, indicating that they are positive feedback traders. They tend to net-buy past winners and net-sell past losers. The portfolio results based on adjusted changes in individual ownership (AdjDIND) are reported in Table 6. Evidence indicates that firms with higher AdjDIND earn higher subsequent raw returns. However, the equal- (value-) weighted average of the monthly raw return difference between stocks in the highest decile and stocks in the lowest decile is an insignificantly positive 0.28% (0.17%). Consistent with the results in the previous section, Panel B reveals that there is an increasing pattern of BE/ME and a decreasing pattern of size as AdjDIND increases. Moreover, individual investors are contrarian investors; that is, they net-buy prior losers and prior winners. <Insert Tables 5 and 6 about here> As robustness checks, we use a second method to examine the relation between institutional trading (individual trading) and stock returns. In Table 7, we present a cross-sectional regression analysis at the firm level. Using the Fama and MacBeth (1973) procedure, we report the time-series averages of slopes from the monthly cross-sectional regressions of stock returns on BE/ME, size, AdjDITH, and AdjDIND. The model 8 shows that the coefficients on BE/ME and size are 0.16 and -0.14, which
returns. In this section, we examine the interactive relation between AdjDITH premium (or AdjDIND premium) and BE/ME (or size) premium. We use independent double on BE/ME (or size) and AdjDITH (or AdjDIND) to explore the effect of institutional trading (or individual trading) on BE/ME and size premiums. Specifically, at the end of each June, we sort all stocks into 25 portfolios independently based on BE/ME (or size) and AdjDITH (or AdjDIND). The results are shown in Table 8. the evidence indicates that BE/ME and size premiums appear to have a weak relation to AdjDITH and AdjDIND. For example, Panel A indicates that there is no systematic pattern of BE/ME premium (returns on stocks with high BE/ME minus returns on stocks with low BE/ME) across AdjDITH and AdjDIND portfolios. The size premium in Panel B also shows similar evidence. Second, AdjDITH and AdjDIND premiums have little association with BE/ME and size. For instance, AdjDITH and AdjDIND premiums show no systematic pattern across BE/ME and size portfolios. As a result, although stocks with high (low) BE/ME tend to experience institutional (net-buying), the influences of BE/ME and institutional trading on stock returns seem to be weakly related. For a robustness check, we use the dependent sorting procedure (i.e., AdjDITH (or AdjDIND) is sorted first followed by BE/ME (or size)) to explore the effect of AdjDITH (or AdjDIND) on BE/ME and size premiums. The results shown in Table 9 suggest that BE/ME and size premiums are not driven by AdjDITH and AdjDIND. Specifically, holding AdjDITH constant, value and size premiums remain significantly different from zero. <Insert Tables 8 and 9 about here>
Table 4. Average parameter values from the cross-sectional regressions of annual book-to-market ratio and size on changes in institutional and individual ownership The annual logarithm of book-to-market ratio (size) is regressed on the adjusted changes in institutional ownership (AdjDITH) and adjusted changes in individual ownership (AdjDIND). Average parameter values are the time series averages, and t-statistics are time-series averages divided by the time-series standard errors (198 months). Ln denotes the natural logarithm. The variable definitions are presented in Table 1. t-statistics are shown in parentheses. The asterisks *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively. Regression Specification, Average Parameter Values (%) and t-statistics Dependent variable Intercept AdjDITH AdjDIND Ln(BE/ME) -0.61*** -0.70*** (-7.36) (-2.79) -0.61*** 0.74*** (-7.40) (4.77) Ln(ME) 10.40*** 0.42 (98.95) (0.54) 10.41*** -1.94*** (99.49) (-4.90)
(2) – (4) -90 -57 1300 300 (2) – (4) -23 -18 10 -11 (2) – (5) -90 -63 -240 -233 (2) – (5) 66 80 -466 700 (2) – (6) -94 -77 -333 -900 (2) – (6) 233 80 1000 700