To compare trading preferences for investors with different backgrounds, we investigate the various preference structures for investors with different characteristics. In addition to comparing the trading preferences of institutional vs. individual investors, we select five dimensions about various investors’ backgrounds in our thesis: gender, wealth, region, trading frequency, and trading experience.
(2) Gender
From the number of the identification card of the individual investors in our data set, we can identify the gender of the individual investors. Then we divide the individual investors into two groups based on their gender.
Table VI summarizes the grouping results of the data. We can find that the number of female investors is greater than male investors. However, the trading volume and mean trading value of female investors are both smaller than those of male investors. Besides, the maximum trading value in one stock investment of male is much larger than female. It appears to be in conformity with the existing studies documenting that women are more conservative and invest less than men.
< Table VI Inserted Here>
(2) Wealth
In order to examine whether the investors’ trading preferences will vary with different levels of wealth, we separate the individual investors in the data set into five groups. By referring to Ng and Wu (2006), we use the investor’s maximum trading value in one trading record as the measure of this investor’s wealth. The larger the trading value in one stock trading the investor can afford, the greater the wealth he may own. There may be the
problem that the wealthier investors do not invest large amount of money in the stock each time, and that the less wealthy investors may put a high proportion of their property into one stock investment based on the psychology of gambling. However, logically thinking, the possibility of the behavior mention above is relatively smaller. Besides, because of privacy, it is impossible for us to obtain the real and detailed data about each investor’s wealth. Therefore, the maximum trading value in one trading record is the best way we can find to measure the wealth of each individual investor.
First, we find the maximum trading value of each individual investor, and divide the data into five groups: Group W1, Group W2, Group W3, Group W4, and Group W5. Group W1 contains the individual investors with the least wealth, and Group W5 is those with the greatest wealth.
Based on the distribution of our sample, we set the separation criteria as follows: Group W1 is the investors whose maximum trading value lies in between 0 and 100,000, Group W2 is between 100,001 and 1,000,000, Group W3 is between 1,000,001 and 5,000,000, Group W4 is between 5,000,001 and 10,000,000, and Group W5 is those whose maximum trading value is larger than 10,000,000. Table VII presents the statistics for each group. We can find that most of the investors are located at Group W2. In addition, the number of investors in Group W1 and Group W2 accounts for 87.11% of the total, and the number of trading in Group W1, Group W2 and Group W3 is about 86.20%. Thus, the pattern of stock trading in Taiwan is mainly composed of investors with less wealth.
< Table VII Inserted Here>
(3) Region
On the basis of the existing studies, investors located in different regions may have different trading preferences. Hence, we want to investigate whether the investors who live in different regions will have different preferences for stocks with certain characteristics. However, the area of Taiwan is small, and there are different characteristics between different regions in Taiwan. For example, the North region of Taiwan is more urbanized than the other regions, and the differences between the cities and the countries are large. There are aborigines living in the East region in Taiwan, and they have their own specific culture and customs.
Besides, they may have different preferences for stock trading. Therefore, in our thesis, we separate the investors based on a broader region instead of being on the basis of cities or districts. After identifying the address of each investor, we partition the individual and institutional investors into four groups: North, Central, South, and East. Table VIII shows the trading data of individual and institutional investors in different regions. Among all of the investors in our sample, about 64.20% of them live in the North region.
Because the North region is the most developed in Taiwan, it is easier for people to receive news and contact innovation. Besides, generally speaking, people lived in the North region in Taiwan are wealthier than the others. Thus, they are more willing to take the risk and make stock investments.
< Table VIII Inserted Here>
(4) Trading Frequency
In order to analyze whether the trading frequency has an influence on the stock buying and selling behavior of individual and institutional investors, we separate the investors into three groups based on how often they make the stock trading. There are 5 trading days in a week, and about 250 trading days in one year. Thus, we define that Group F1 contains the investors whose trading frequency is between 5 and 50 (i.e., on average, they make one stock trading in a week.). Group F2 is investors with trading frequency between 51 and 250 (i.e., their trading frequency is about once every day). Group F3 includes investors whose trading frequency is between 251 and 1,000, Group F4 is between 1,001 and 10,000, and investors whose trading frequency is above 10,000 belong to Group F5.
Table IX summarizes the trade records of individual and institutional investors in different groups. We can find that most of the investors make stock trading less than five times in a week.
< Table IX Inserted Here>
(5) Trading Experience
In order to measure the impact of trading experience on investors’
preferences, we use the years of opening the accounts as the proxy because it can represent the experience of making stock investments. Earlier date of opening account means longer years of trading stocks, and that the investor
is more experienced. We divide the investors into three groups: Group Y1, Group Y2, and Group Y3. Investors in Group Y1 are the least experienced, and investors in Group Y3 are those with greatest experiences. The grouping criteria are that the investor’s year of opening accounts in Group Y1 is between 1 and 5, Group Y2 is between 6 and 10, and Group Y3 contains investors with experiences in excess of 10 years. Table X shows the trade records of investors in each group. We find that most of the investors are not experienced. It also indicates that stock investors in Taiwan are increasing in recent years.
< Table X Inserted Here>