國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
21
4. Empirical Results
4.1 Herding and feedback trading by individual investors and the effect of trade sizes
Table 4 shows herding and feedback trading by individual investors during the
entire sample period. In Panel A, we observe a significant positive correlation
between TAIEX Futures return in last period and the net buy orders by individual
investors. It demonstrates that individual investors are significant positive feedback
traders. They are less-informed traders, so they pay more attention to public
information such as market prices. They buy TAIEX futures when market price rises
and sell it when market price falls. On the other hand, we observe individual investors
tend to transact with lags and the opposing direction to institutional investors.
To examine the effect of trade sizes on herding and feedback trading behavior by
individual investors, we divide individual investors into large and small groups.
Table 2 shows descriptive statistics per contract by trade size categories. We define
two trade sizes of individual investors each as follows: individual investors whose
total trading volumes are above 3,864 contracts belong to the large group, individual
investors whose total trading volumes are below and equal to 3,864 contracts belong
to the small group. We can see that the average trade sizes of large individual
investors and small individual investors vary drastically. The average trade sizes of
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
22
large individual investors are over one hundred times more than the average trade
sizes of small individual investors
By looking at Panel B of Table 4, we find that only lag of the net buy orders by
large individual investors can explain TAIEX futures return in current period. The
statistics result is slightly significant. It implies that large individual investors are
informed traders and they have capability of predicting market returns. Besides, we
observe that large individual investors are neither positive feedback nor negative
feedback traders. It is interesting that we find that large individual investors tend to
transact with lags to small individual investors.
According to Panel C, we observe that small individual investors are significant
positive feedback traders. On the other hand, we observe small individual investors
tend to transact with lags and the opposing direction to large individual investors and
small institutional investors. The result is consistent with the result of Lee et al.
(1999).
In short, individual investors are significant positive feedback traders but engage
in herding not significantly. We find that large individual investors are informed
traders and their trading behavior is independent and different from average individual investors’ trading behavior. Small individual investors are less-informed traders, and
they tend to engage in positive feedback trading to get more attention.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
23
4.2 Herding and feedback trading by institutional investors and the effect of trade sizes
Table 8 shows herding and feedback trading by institutional investors during the
entire sample period. In Panel A, we observe a significant negative correlation
between TAIEX Futures return in last period and the net buy orders by institutional
investors. It demonstrates that institutional investors are significant negative feedback
traders. What is more, we find that they engage in herding to themselves. Because of
the competition among institutional investors and reception of similar information,
institutional investors have significant herding behavior.
To examine the effect of trade sizes on herding and feedback trading behavior by
institutional investors, we also divide institutional investors into large and small
groups. Table 2 shows institutional investors whose total trading volumes are above
577,850 contracts belong to the large group, and institutional investors whose total
trading volumes are below and equal to 577,850 contracts belong to the small group.
We can see that the average trade sizes of large individual investors and small
individual investors vary widely. The numbers of large institutional investors account
for 1.5% of the numbers of all institutional investors. However, the total trading
volumes of large institutional investors account for more than half of the total trading
volumes of all institutional investors.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
24
By looking at Panel B of Table 8, we observe that large institutional investors are
positive feedback traders. There is slight evidence to indicate that large institutional
investors follow their lag trading, but they would not follow other types of investors.
Meanwhile, Panel C shows that small institutional investors are significant negative
feedback traders. In addition, we find that they engage in herding not only to
themselves but also to large individual investors.
In brief, institutional investors have significant herding and negative feedback
trading behavior. Large institutional investors’ trading behavior is not consistent with average institutional investors’ trading behavior. Small institutional investors have the
most significant herding behavior among all types of investors because of competition
among them and reception of the similar information.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
25
4.3 Herding and feedback trading in different periods
We divide the entire sample period into a period of contraction and a period of
expansion and examine whether each type of investors change their trading behavior
in different phases of the business cycle. Table 3 and Table 7 present descriptive
statistics for all dependent variables of VAR models. We can see that average return
during the entire sample period is 0.03%, average return during a period of
contraction is -0.02%, and average return during a period of expansion is 0.05%.
Table 5 and Table 6 separately present individual investors’ trading behavior
during a period of contraction and a period of expansion. By looking at Panel A to
Panel C of Table 5, we find that herding almost disappears among individual
investors during a period of contraction. Panel A to Panel C of Table 6 discover that
herding prevails over individual investors during a period of expansion. Large
individual investors have no capability of predicting market returns during a
recession. Small individual investors are positive feedback traders both during
periods of contraction and expansion. However, the evidence of positive feedback
trading is much weaker during a period of contraction.
Table 9 and Table 10 present institutional investors’ trading behavior during
periods of contraction and expansion, respectively. According to Panel A to Panel C
of Table 9 and Table 10, we observe herding by institutional investors is more
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
26
significant during a period of expansion than a period of contraction except for large
institutional investors. Large institutional investors engage in herding and positive
feedback trading during a period of contraction but the phenomenon is slightly
significant. Small institutional investors herd to themselves and large individual
investors significantly during a period of expansion. Nevertheless, small institutional
investors do not follow themselves anymore and the evidence of herding to large
individual investors is weaker during a period of contraction. Besides, we observe
that small institutional investors are significant negative feedback traders both during
periods of contraction and expansion.
In sum, investors react asymmetrically to periods of contraction and expansion.
Herding and feedback trading prevail more over almost all types of investors during a
period of expansion except for large institutional investors. Chau et al. (2011) suggest
that feedback trading is largely caused by the presence of sentiment-driven trading.
Because the emotion of investors is stronger during a period of expansion than during
a period of contraction, the intensity of herding and positive feedback trading increase
during a period of expansion. Choe et al. (1999) suggest that investors are less capable
of trading as a result of market liquidity shortfall during a period of contraction.
Therefore, the phenomenon of herding is less significant during a period of
contraction than during a period of expansion.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
27
4.4 Herding and feedback trading by different institutional investors
In prior to the examination, we find that institutional investors have significant
herding and positive feedback trading behaviors. However, institutional investors can
be categorized into three types of investors: domestic institutional investors,
proprietary firm investors, foreign institutional investors. In this part, we discuss
whether these three types of institutional investors all engage in herding and negative
feedback trading.
Table 11 presents descriptive statistics for all dependent variables of VAR models
with these three types of institutional investors. We can discover that the range of FOREt is -0.99 to 1.00, and kurtosis is negative. It implies that foreign institutional
investors are better-informed traders, and that the direction of trading by them is
extremely the same.
Table 12 reports herding and feedback trading by different types of institutional
investors during the entire sample period. In Panel A, we observe that no lag of the net
buy orders by all types of institutional investors has significant evidence to explain
TAIEX futures return in current period.
In Panel B, we discover that domestic institutional investors tend to transact with
lags and the opposing direction to themselves. On the other hand, domestic
institutional investors are neither positive feedback nor negative feedback traders.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
28
In Panel C, we find that proprietary firm investors do not engage in herding and
feedback trading. In Panel D, we observe that foreign institutional investors have
significant herding and negative feedback trading behavior. They buy when market
prices falls and sell following increase in market prices. The intensity of herding
among foreign institutional investors is larger than other types of institutional
investors. The result is consistent with the evidence of Bowe and Domuta (2004).
In a word, only foreign institutional investors engage in herding. They are more
likely to follow the same type of institutional investors than different types of
institutional investors. The result accords with the result of Sias (2004). Moreover, we
observe that only foreign institutional engage in negative feedback trading among all
types of institutional investors.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
29