Trading volume around event day

In this section and the sections that follow, we use a similar approach in the event study. The long event window [−120, 120] is used so that any indication of leaking of information or insider trading could be detected. We examine the pattern of movement of the variables and compare with the ‘normal’ period or the estimation period. Basically, it examines whether there is any significant change that occurs during the event window.

Eventually, the test of significance assumes that the observations are drawn from the same population. The null hypothesis we are going to test is that the variable under the study during the particular event window is significantly higher than the normal period.

Moreover, since we have verified that there is no other event that occurs in the shorter

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Figure 6.10: Market valuation around event date - buy vs. hold recommendations event window [−30, 30], the pattern of movement in this event window is of particular interest and will be examined.

We have shown earlier in Section 6.4.3 that it is evidence that there is no significant increase of trading volume prior to and after the release of analysts’ initial reports. Using a similar approach in event study, we examine the pattern of trading volume surrounding the event window [-120,120]. We test the significance of turnover in the event window [-120,120] against the estimates using 100 trading days period as mentioned earlier in Section 5.4.2.

Basically, we compare daily turnover in the event window with the mean of the esti-mated turnover in the estimation period which we assume as a normal period. Assuming that the turnover is withdrawn from the same population, the null hypothesis we are testing is that there is no difference of trading volume between the event window and the normal period.

We examine the pattern of daily movement of trading volume around the event window [−120, 120] shown in Figure 6.11. We find that there is no indication that trading volume

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Figure 6.11: Trading volume - participating vs. control

in the participating group has increased after the analysts reports are released. Due to the difference in the composition between the participating companies and the control group, trading volume in the control group is inherently and consistently higher than the participating group during the entire event window [−120, 120]. Nevertheless, the pattern of daily movement of trading volume between the participating companies and the control group is closed with each other. It is indicated from the statistical tests of cross-section of mean difference of trading volume between the participating companies and the control group. The results show that the difference significant from zero in only some of the days in the event window [−120, 120].

The event window [−30, 30] is of particular interest due to the fact that there is no other event in most of the companies except the release of the analysts reports. Since the trading volume is not significantly higher than normal and the difference is not significant from zero at the 5% significant level during the event window [−30, 30], it means that the analysts reports are not influential to generate more interest in investors to trade.

As a result, there is no significant improvement in trading volume after the release of the analysts reports. This result support our earlier findings that the analysts reports do not

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Figure 6.12: Trading volume - buy vs. hold recommendations

have a significant impact on trading behaviour. However, there are more occurrences of significant turnover in the control group which is due to the composition of control group which has more big companies than the participating group.

We replicate our examination on stock turnover by dividing the companies into the type of recommendations they received. It is noted that turnover in the buy companies is higher than the hold companies in almost the whole event window [−120, 120] as shown in Figure 6.12. Statistical tests show that turnover within the buy and hold companies are not significantly higher than the normal period in most of the days in the event window [−120, 120. Similarly, cross-section mean difference test of turnover between the buy and hold companies is statistically significant from zero only a few days in the event window [−120, 120]. Earlier, we have verified that there is no other important event that occurs during the event window [−30, 30], so there is no other event that could have affected the results. Therefore we do not find evidence that trading activities have increased after the release of analysts recommendations. Neither the buy nor the hold recommendations are influential to attract traders to trade more after the recommendations are released.

In summary, the analysis reveals that the analysts reports and their accompanying

recommendations are not able to generate or influence higher interest in the market to trade, otherwise we will be able to detect a significant increase in trading volume continuously after the reports are released. It means that the release of analysts’ initial reports is not really an event.