Insider Trading in Hong Kong: Some Stylized Facts Man-Yin Cheuk Dennis K. Fan Raymond W. So Department of Finance Chinese University of Hong Kong Shatin, N.T., Hong Kong May, 2004 Address correspondence to Raymond W. Fan, Department of Finance, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, email: email@example.com, tel: (852) 2609-7640, fax: (852) 2603-6586. Insider Trading in Hong Kong: Some Stylized Facts ABSTRACT This paper examines the characteristics and price movements of legal insider transactions in Hong Kong. Abnormal returns are analyzed for intensive trading, as well as for samples grouped by industry classification, firm size, book-to-market ratio, price-earnings ratio, and relative trading volume of the insider transactions. Results show that insiders are able to earn abnormal profits from both buying and selling activities. The magnitude of and duration for abnormal profits depend significantly on firm-specific and transaction-specific factors. We also document the persistence of abnormal returns associated with insider sales, while abnormal profits associated with insider purchases are concentrated in certain transactions. Keywords: Insider Trading, Hong Kong, Information Asymmetry JEL Classification: G14, G34 Insider Trading in Hong Kong: Some Stylized Facts 1. Introduction Many studies (e.g. Jaffe, 1974; Finnerty, 1976a and 1976b; Seyhun, 1986, 1988a, 1988b; Rozeff and Zaman, 1988; Lin and Howe, 1990) conclude that insiders can earn abnormal profits through trading stocks of their own firms. Apart from investigating the abnormal performance of the stock price around insider transactions, research efforts also focus on whether outsiders are able to earn abnormal profits by mimicking the trades of corporate insiders (e.g. Seyhun, 1986; Rozeff and Zaman, 1988; and Chang and Suk, 1998). The conclusions on these issues, however, are mixed. The main objectives of this paper are to document the characteristics of legal insider transactions on the Hong Kong stock market, to examine the abnormal stock price movements associated with insider trading, and to comment on the profitability for insiders through insider transactions. We are interested in Hong Kong because most studies on insider trading are based on U.S. data, and the results of these studies may not be robust in the Asian or emerging markets. It has been widely accepted and supported that efficiency and transparency are low in most emerging markets. In many cases, especially in small firms, the separation of management and ownership is rare. Since manager-owners are, in general, more informed about the business prospects of their own firms, insider trading which involves the directors of small corporations is likely to be the most profitable. In a current study by Claessens et al. (2000), it is reported that about 60% of Hong Kong firms are group-affiliated, while 66% of Hong Kong firms are controlled by families. Hence, a study of insider trading in Hong Kong can shed light on the impact of information asymmetry on the profitability of insider transactions. 2 Our results show that insiders can make abnormal profits from both buying and selling activities. The magnitude of these abnormal profits associated with insider sales is considerably larger than that associated with insider purchases. When insider transactions are grouped by industry, firm size, book-to-market ratio, price-earnings ratio, and relative intensity of insider transactions, we find that both the magnitude of the abnormal profits and the duration for which these abnormal profits persists depend significantly on firm-specific and transaction-specific factors. Small firms are found to generate the largest and most persistent abnormal profits. In addition, abnormal returns can persist up to 20 days after an insider transaction has occurred. Outside investors can make abnormal profits by mimicking insider activities. The overall results imply that tougher regulations on insider trading may be necessary to enhance the efficiency of the Hong Kong stock market. The remainder of this paper is organized as follows. Section 2 contains a summary of the two Ordinances relating to insider trading in Hong Kong. Section 3 describes the data and provides the summary statistics. Section 4 describes the methodology, followed by results and discussions in Section 5. Section 6 concludes the study. 2. Insider Trading Regulations in Hong Kong Insider trading is criminalized in some parts of the world, but not in Hong Kong. The main provisions in Hong Kong relating to insider trading are contained in the Securities (Insider Dealing) Ordinance (SIDO), and the Securities (Disclosure of Interests) Ordinance (SDIO). Both ordinances were implemented on September 1, 1991 to replace the then existing provisions of the Securities Ordinance. The purpose of the current legislation is to ensure a “level 3 playing field” for all participants in the market, so that no one is allowed to benefit from trading a firm’s securities by making use of undisclosed private information about the firm. According to SIDO, insider dealing occurs when a person or corporation, either directly or indirectly connected to a listed corporation, uses relevant information about that corporation to deal in the securities, or their derivatives, of that corporation, or to counsel or procure any other person to trade the securities or their derivatives. Relevant information is defined as specific information, which is not generally known to investors who might deal in the securities concerned, and is likely to materially affect the price of those securities. While insider dealing is not a criminal offence in Hong Kong, the Insider Dealing Tribunal (the Tribunal) is empowered to inquire into insider dealing cases and to impose orders to penalize insider dealers. A person who is identified as an insider dealer may be prohibited from being a director, liquidator, receiver, or manager of a company for a period not exceeding five years, required to pay to the government an amount not exceeding the profit made or the loss avoided relating to the insider dealing, and/or penalized for an amount of up to three times the profit made or the loss avoided as a result of the insider dealing. Any persons who contravene the investigation or the orders made by the Tribunal may be liable for a fine of up to $200,000 and to a term of imprisonment of one year. The SDIO requires the disclosure of interests for substantial shareholders, directors, and chief executives of a corporation. The Ordinance is applicable to interests in all companies listed on the Stock Exchange of Hong Kong (SEHK), regardless of where the companies are incorporated. A substantial shareholder is defined as anyone holding at least 10% of the share capital of a corporation listed on the SEHK. Under the SDIO, directors and chief executives of corporations face more stringent requirements than substantial shareholders. Directors and chief 4 executives of a listed company are obligated to declare any interest in shares or debentures in the listed company or any associated corporation, and their acquisition or disposal. Any shares or debentures owned by the spouses, or any children under the age of 18, of directors and chief executives are also taken to be interests of the directors or chief executives. Failure to comply with the SDIO is a criminal offence. If a listed company is in default in complying with the Ordinance, then every officer concerned is liable to a fine of $2,000, and in the case of continuing offence, to a further fine of $200 per day on each day the offence continues. An individual who fails to make a timely notification, or makes a notification which is false in material particulars, is subject to a fine of up to $100,000 and to a term of imprisonment of up to two years. 3. Data and Summary Statistics As described in the previous section, directors, and chief executives of a listed company are under an obligation to disclose any interests in the listed company, as well as the acquisitions and disposals of such interests. Information on each notification received by the Stock Exchange is disseminated to the general public through The Securities (Disclosure of Interests) (SDI) Daily Summaries – Directors’/Chief Executives’ Notifications Report published by the Hong Kong Exchanges and Clearing Limited (HKEx). Information in the SDI includes the company name, the name of the insider, the type of securities, transaction date, reporting date, and publication date. Data on the trading activities of corporate insiders used in this study are obtained from Inside Trade Asia (ITA) of PRIMARK-DISCLOSURE. The ITA data are compiled based on the original Securities (Disclosure of Interests) Daily Summaries – Directors’/Chief Executives’ Notifications Report published by the HKEx. 5 The sample period of this study is January 1993 through December 1998. To measure returns to insider transactions, only open market purchases and open market sales, which are represented by the transaction types P and S, respectively, in the ITA, are included for analysis in this study. Many possible motivations exist behind an insider transaction. For insider sales, the insider may sell stocks for liquidity reasons, or they may sell to diversify the risk of their investment. For insider purchases, these occur naturally when directors buy shares for qualification purposes. Insiders also acquire shares as a result of exercising options. However, the general public and researchers tend to think that the more likely and intriguing reason behind insider transactions is private information. If directors and chief executives are allowed to trade in the securities of their own companies, then it is very likely that they trade the stocks of their own firms to make a profit or to avoid a loss as soon as good news or bad news of the firm reaches them. Even though insider trading is restricted or made illegal in many circumstances, insiders are still likely to trade based on private, price sensitive information. Data on daily cash-dividend-adjusted stock returns (daily stock returns) and daily value- weighted cash-dividend-adjusted market returns are obtained from the Pacific-Basin Capital Markets (PACAP) Databases compiled by the University of Rhode Island. Other general information, such as total stockholders’ equity, net income, industry type, daily trading volume in shares, daily closing price of common stock, month-end common stock closing price, month- end number of common stock outstanding, and month-end market value of stocks, are also collected from the PACAP databases. For the sample period, there are 23,675 open market insider transactions. Table 1 provides the summary statistics of the insider trading data used in the study. In the sample, 541 6 listed companies were involved in insider trading with 507 firms involved in open market purchases and 458 involved in open market sales. The total number of open market purchases and sales transactions are 16,221 and 7,574, respectively. In general, there are more insider purchases than insider sales. The ratio of insider purchases to insider sales is about 2.15:1, such that two out of three insider transactions are purchases`. For the entire sample, the average number of shares traded per transaction is 5.1 million and, on average, the value of the shares traded in each transaction is HK$11.5 million. A comparison by type of transaction shows that both the average number of shares per transaction and the average value of the shares traded per transaction are larger for sales than for purchases. Seyhun (1998) finds that insiders in the U.S. are likely to break up purchases into smaller transactions for fear of insider trading sanctions. It is suggested that an insider purchase provides a stronger signal to both the authority and the general public than does an insider sale. However, insiders are not as concerned with insider trading regulations in sales transactions. It might be taken by the authority that the motivations for profiting from the private information behind insider sales are less obvious. Our results seem to lend support to this claim. Table 2 shows the frequency distribution of insider trading activity by industry classification. The ratio of purchases to sales is the largest for the hotels industry group. Directors and executives of consolidated enterprises are the most intensive sellers of their companies’ stocks, while insiders of the properties group are the most intensive buyers. Overall, relative to the insiders of other industries, corporate insiders of the properties industry are the most active in trading the stocks of their own firms. Table 3 shows the frequency distribution of insider trading activities by firm size, book- to-market ratio, price-earnings ratio and relative trading volume. Rozeff and Zaman (1988) argue 7 that firm size is a contributing factor to the abnormal returns to outside investors. In a study by Wong et al. (2000), it was found that the abnormal return on insider trading in Hong Kong is significantly different for firms of different sizes and relative trading volume. To test for the differences in firm size, the sample firms are classified into three groups according to their market capitalization at the time of the insider transactions. Statistics show that insider purchases are more commonly found among small firms. The ratio of purchases to sales for the small size firm group is 3.232:1. In contrast, directors in large firms are more likely to sell. The ratio of purchases to sales for the large firm size group is 1.605:1. Fama and French (1995) argue that growth stocks are typically associated with a low book-to-market ratio, whereas value stocks are typically associated with a high book-to-market ratio. Since a high book-to-market ratio signifies under-valuation of a stock and positive future returns, while a low book-to-market ratio indicates over-valuation and negative future returns of a stock, it is likely that insiders purchase more when the stock’s book-to-market ratio is high and sell more when the stocks’ book-to-market ratio is low (Seyhun, 1998). In our sample, each transaction is ranked by the book-to-market ratio of the stock concerned and is assigned to one of the three groups: low book-to-market ratio group, medium book-to-market ratio group, and high book-to-market ratio group. The statistics of Table 3 are consistent with the hypothesis stated above. There are far more purchases among the high book-to-market ratio group than among the low book-to-market ratio group. Insider purchases increase in frequency with increasing book-to-market ratio, while insider sales decrease in frequency with increasing book-to-market ratio. This is consistent with the findings in Rozeff and Zaman (1998) and Seyhun (1998). In the sample, the ratio of 8 purchases-to-sales is 4.052:1 for the high book-to-market ratio group, while it is 1.061:1 for the low book-to-market ratio group. The price-earnings ratio of a firm is another widely used indicator of future stock returns. Similar to the previous sections, each transaction is ranked by the price-earnings ratio of the stock concerned and is assigned to one of three groups: low price-earnings ratio group, medium price-earnings ratio group, and high price-earnings ratio group. Table 3 shows the frequency distribution of insider trading activity by the price-earnings ratio of the firms concerned. The statistics are consistent with the assumptions made regarding the relationship between the price-earnings ratio and insider trading activity. On the one hand, insider purchases are more frequent in the low price-earnings ratio group, while fewer sales are found. On the other hand, insider sales are more prominent in the high price-earnings ratio group, while fewer purchases are found. The ratio of purchases to sales for the low price-earnings ratio group is 2.566:1, while that for the high price-earnings ratio group is 1.307:1. Trading volume is found to be positively associated with the quality of information (see Karpoff, 1987, for example). Wong et al. (2000) suggest that the trading volume of individual transactions affects the post-event abnormal stock prices. Similar to Wong et al. (2000) and other studies, relative trading volume is calculated by the total number of shares traded in the insider transaction divided by the total number of outstanding shares of the stock. Relative trading volume is used as an indicator of the quality of information associated with insider trading. Each transaction is ranked by the relative trading volume in shares and is assigned to one of three groups: low relative trading volume ratio group, medium relative trading volume group, and high relative trading volume group. 9 Table 3 shows the frequency distribution of insider transactions by relative trading volume in shares. As discussed before, insiders might tend to sell in larger lots, and buy in smaller lots. This pattern is indeed found in the sample. The ratio of purchases to sales is 2.357: 1 for smaller relative trades while it is 1.828:1 for larger relative trades. 4. Methodology Standard event study methodology is applied to examine the profitability for insiders from the buying or selling of the stocks of their own firms. One main assumption behind insider trading activity is that insiders buy and sell the stocks of their firms because insiders have private information. However, it is still very possible that insiders trade for other reasons. Jaffe (1974) suggests that information can initiate simultaneous buying and selling activities by insiders of the same firm. During these periods, when insiders of a firm trade intensively, these insiders are more likely to take advantage of having private information. Similar to many previous studies (e.g. Jaffe, 1974; Lin and Howe, 1990), we will select a sample based on an intensive trading criterion to reduce noise from trades not initiated by private information. In this study, a firm with at least 2 times more purchases in dollar value than sales in dollar value in a month is classified as an intensive buying firm for that month. Conversely, a firm with at least 2 times more sales in dollar value than purchases in dollar value in a month is classified as an intensive selling firm for the month. In event time, day 0 is the transaction date of an “intensive” trading event. An estimation period from day –280 to day –21 is used to calculate the parameters, αj and βj of the market model: R jt = α jt + β j Rmt + ε jt , (1) 10 where Rjt is the daily dividend-adjusted stock return for firm j on day t; Rmt is the daily value- weighted dividend-adjusted market return on day t; αj is the estimated intercept; βj is the estimated market risk of the stock j; and εjt, the error term on day t, is assumed to be normally distributed with mean zero and constant variance σj2. The abnormal return to firm j on day t, ARjt, is then calculated from day –20 to day +20 for each day as follows: AR jt = R jt − α j − β j Rmt , ˆ ˆ (2) where α j and β are the estimates of α j and β j . The average abnormal return (AAR) across ˆ ˆ j firms for each day is: 1N AARt = ∑ AR jt , (3) N j =1 where N is the number of firms with insider trading on day t. The significance of the average abnormal return is tested by the statistic: AARt t AARt = . (4) σ AAR t The cumulative average abnormal return (CAAR) to the insider trading firms from day – D to day D is the sum of the average abnormal returns between day –D and day D. The formula is: 11 D CAARt = ∑ AAR t =− D t , (5) and the significance of the cumulative average abnormal return is: CAARt t CAARt = . (6) σ CAARt Insiders are required to report any insider transactions to the SEHK within 5 days following the transaction. Here we make the prudent assumption that the average outsider would not know of any occurrence of insider trading on day 1 to day 5 after the insider transaction day, and that by day 20 after the transaction day, the SEHK should have disseminated information about the transaction to the public through the SDI report. To assess the performance of stocks traded by insiders and the degree of market efficiency in the stock market, we will examine the cumulative average abnormal returns associated with insider purchases and sales for post-event periods of day 1 to day 5, day 1 to day 10, and day 1 to day 20. The CAARs of the transactions will be analyzed as a whole, by industry classification of the transaction firm, by size of the transaction firm, by price-earnings ratio of the transaction firm, by book-to-market ratio of the transaction firm, and by relative trading volume of the transaction. If we find persistent abnormal returns after the day on which the public is informed of any insider trading, then the market reacts to the dissemination of such information. Also, if such abnormal returns exist, then it is likely that outsiders can actually earn abnormal profits by mimicking the trades of insiders. 12 5. Results and Discussion Table 4 shows the cumulative average abnormal returns surrounding insider purchases and insider sales. The overall result shows that within the 20-day post-event period prices increase after insider purchases and decrease after insider sales. For insider purchase transactions, the 20-day pre-event CAAR is statistically significantly negative, which means that insider purchases occur after a period of persistently low stock price. On day 0, the AAR is –0.056% (t = -1.37), which is not significantly different from zero. However, the 5-day, 10-day, and 20-day CAARs are 0.19%, 0.43% and 0.58% respectively, which are all significantly positive. In the aggregate, stocks purchased by insiders do perform well within the 20-day period after the transaction. Insiders are able to make abnormal profits from insider purchases. Since the CAARs of insider purchases are significantly positive within a 20-day period after the transaction, a period long enough for outsiders to know of the occurrence of insider purchases and to mimic the trades, outsiders are also capable of making abnormal profits from following insider purchases. Price movements around insider sale transactions are more dramatic. The pre-event CAAR is significantly positive. While the AAR for day 0 is 0.76% (t = 8.78), all the post-event CAARs are significantly negative. Within a 5-day period after the sales transaction, the CAAR is -1.14%. The 10-day and 20-day CAARs are both significantly negative, at around -2.28% and - 4.14%, respectively. The results suggest that stocks sold by insiders do indeed perform poorly after the transactions have taken place. Insiders are able to obtain profits (or avoid losses) when they enter into transactions to sell the stocks of their own firms. Since the CAARs exist in a prolonged period of 20 days after the transactions have occurred, it is also very likely that outsiders who sell stocks following insiders can make abnormal profits. 13 When insider trading of the Hong Kong stock market is examined in the aggregate sense, contrary to the widespread belief that corporate insiders are making huge profits from their insider purchase transactions, we find that insiders actually obtain more profits from insider sales transactions. The result shows that in the aggregate, although insiders are able to earn abnormal profits from both insider buying and selling activities, the magnitude of short-run abnormal profits associated with insider sales is considerably larger than that associated with insider purchases. Table 5 presents the cumulative average abnormal returns for insider trading events according to industry classifications of the transaction firm. Only insiders of the finance and industrials industries are able to make significant abnormal profits through insider purchases. For finance industry insider purchases, the CAARs over the 5 days, 10 days, and 20 days after the transaction day are all significantly positive at around 0.96%, 1.26%, and 2.81%, respectively. For the industrial industry, the 5-day post-event CAAR is not significantly different from zero, but the CAARs over 10 days and 20 days after the transaction day are significantly positive at around 0.75% and 0.17%, respectively. Insiders of the utility, properties, consolidated enterprises, and hotels industrials are not able to gain abnormal profits from insider purchases. In terms of sale transactions, insiders of the properties, consolidated enterprises, and industrials industries tend to sell when prices are high. The pre-event CAARs associated with sales for these three industry groups are significantly positive, and all post-event CAARs are significantly negative. The post-event CAAR associated with insider sales is the most negative for the industrials group. The 5-day, 10-day, and 20-day post-event CAARs are all significantly negative at around –2.83%, -6.12%, and -9.95% respectively. For the properties industry, the post-event CAARs for 5 days, 10 days, and 20 days after the transaction day are significantly 14 negative at about –1.41%, -2.16%, and -3.99% respectively. For the consolidated enterprises industry, the post-event CAARs for 5 days, 10 days, and 20 days are significantly negative at about –1.13%, -2.42%, and -4.01% respectively. Insiders of the finance, utility, and hotels industries, however, are not found to be able to gain significant abnormal profits from insider sales. On the whole, the results show that abnormal profits are mainly associated with insider transactions in the finance, industrial, consolidated enterprises, and properties industries. As far as profit opportunity for outsiders is concerned, they are more likely to make abnormal profits when buying by following insiders who belong to the finance and industrial industries, and when selling by following insiders of the properties, consolidated enterprises, and industrial industries. Panel A of Table 6 shows the cumulative average abnormal returns associated with insider trading grouped by the size of firms involved in the trading. For insider purchases, only the small firms indicate significantly positive post-event CAARs. For this group, the 10-day, and 20-day post-event CAARs are all significantly positive at 1.19%, and 2.65% respectively. Insiders of medium-size firms and large-size firms are not able to make abnormal profits from purchasing stocks of their own firms. The findings here regarding the relationship between firm size and insider purchases are consistent with those reported in Wong et al. (2000). They also find that insider purchases in small firms show the largest abnormal returns. Relating firm size to insider sales, regardless of the size of the firm, insiders of all firms are selling stocks at high prices. All the pre-event CAARs are positive before the transaction day, while all the post-event CAARs are negative. Comparing the three firm size groups, the post- event CAARs are found to be the most negative for the small-size firms and the least negative for the large-size firms. For the small-size firms group, all post-event CAARs are significantly 15 negative. The 5-day, 10-day, and 20-day CAARs are 2.06%, 3.97%, and 6.90% respectively. For the large-size firms group, however, only the 10-day and 20-day CAARs are significantly negative at 0.83% and 2.22%, respectively. When transactions are grouped by firm size, the overall result shows that the abnormal returns associated with both insider buying and selling activities are concentrated in small firms. Insiders in small firms are more likely to buy or sell stocks to take advantage of private information, and they do earn abnormal profits from such trading. This result is in line with findings that information asymmetry is more severe among small firms, e.g. Wong et al. (2000). Outsiders who wish to make abnormal profits by following insiders in buying or selling should only follow the insiders of small firms. If outsiders wish to follow insiders in selling, then the outsiders are likely to make abnormal profits in most circumstances, but following insiders in small-firms when selling is likely to bring the highest amount of abnormal profits. As stated previously, the future prospect of a firm is associated with its book-to-market (B/M) ratio. Low book-to-market ratio predicts bad performance, while large book-to-market ratio predicts good performance. It is hypothesized that insiders tend to sell at periods of low B/M ratio and buy at high B/M periods. Now we examine the relationship between the cumulative average abnormal returns associated with insider trading and the B/M ratio. Panel B of Table 6 shows the CAARs for insider trading events grouped by the B/M ratio of the firm involved in the trading. The results show that stocks bought by insiders of large B/M ratio firms perform better than the stocks bought by low and medium B/M ratio firms in the 20-days after the transaction day. The 10-day and 20-day post-event CAARs associated with insider purchases are significantly positive at around 0.43% and 0.78%, respectively. For low and medium B/M firms, the CAARs for stocks bought by insiders are not significantly different from zero. 16 Therefore, the combination of large book-to-market ratio and insider buying gives a signal to predict positive stock price performance in the 20 days after the transaction. For stocks sold by insiders, the CAARs are all significantly negative for the small and medium B/M groups up to a 20-day period after the transaction day. The small B/M group shows the most negative abnormal returns. The 5-day, 10-day, and 20-day CAARs are –1.21%, -3.19% and –6.00%, respectively. Compared to these results, the 20-day CAARs for the medium and high B/M ratio firms are relatively lower at just –3.80% and –0.99%, respectively. This is consistent with the hypothesis that a small book-to-market ratio predicts bad future performance. In general, an insider transaction combined with the value of the book-to-market ratio of the firm involved in the insider trading provides a stronger indicator of the stock performance than insider trading alone. In terms of the profitability to outsiders, mimicking insider purchases are profitable if the firm involved has a large B/M ratio. Following insiders when selling brings abnormal returns to outsiders regardless of the book-to-market ratio of the firm, but outsiders who follow selling transactions involving small B/M firms are likely to obtain the greatest amount of abnormal profits. A low price-earnings (P/E) ratio is associated with a high future stock return, while high P/E is associated with a low future stock return. Therefore, it is likely that insiders buy when the P/E of the stock is low, and sell when the P/E is high. Panel C of Table 6 shows the CAARs for insider trading events grouped by the P/E ratio of the firms involved in the insider trading. Overall, positive post-event CAARs associated with insider purchases are found only in the small P/E group, but only the 10-day post-event CAAR is significantly positive at 0.60%. For the medium P/E group, the 5-day CAAR is positive while the 10-day and 20-day CAARs are 17 negative. However, none of the CAARs for this group are significantly different from zero. For the large P/E group, the 5-day and 10-day CAARs are not significantly different from zero, but the 20-day CAAR is significantly negative at –1.40%. For sales transactions, post-event CAARs are all significantly negative for all P/E groups. Contrary to the hypothesis that insiders tend to sell high P/E stocks since those stocks are more likely to perform poorly in the future, the results show that the post-event CAARs associated with insider sales are the most negative for the low P/E firms. The 5-day, 10-day, 20-day post- event CAARs are –1.69%, -3.42%, and –5.44% respectively. For the medium and high P/E groups, the 20-day CAARs are around just –3.23% and –4.33% respectively. In general, when the insider transactions are grouped by P/E ratios, insider purchases among the low P/E firms are likely to generate the largest amount of abnormal profits for the insiders. Insider sales are signals of negative stock performance in the future, but the P/E ratio of the firm concerned does not enhance the predictability of the insider sale signal. In terms of profit opportunities for outside investors, outsiders are most likely to make abnormal profits by mimicking the insiders of small firms when purchasing. Karpoff (1987) suggests that the quality of private information is positively related to trading volume. Relative trading volume, calculated by the total number of shares traded in the insider transaction divided by the total number of outstanding shares of the stock, is used as an indicator of the quality of private information associated with insider trading. The relation between relative trading volume and the abnormal price performance of the stock following insider transactions is examined next. Panel D of Table 6 shows the cumulative average abnormal returns for insider trading grouped by the relative trading volume of the transaction. 18 For insider purchases, only the 10-day post-event CAAR for the medium relative trading volume group is significantly positive, at around 0.56%. Purchases in the large relative trading volume group do not predict good performance within a 20-day post-event period. Therefore, the relative trading volume of insider purchases per se may contain little information. For sales transactions, post-event CAARs for the small, medium, and large relative trading volume groups are all statistically significant. Post-event day CAARs are the most negative for the large relative trading volume group. The 5-day, 10-day and 20-day CAARs are -1.59%, -3.44%, and –6.29% respectively. In general, the relative trading volume combined with insider selling seems to convey more information, and the worst future stock performances are followed by larger insider sales. Regardless of the relative trading volume of the transactions, insiders are all able to earn abnormal profits from selling the stocks of their firms. Outsiders are able to obtain abnormal profits when they follow insiders in selling regardless of the relative trading volume of that transaction, but following insiders who sell in large lots is likely to bring the highest abnormal profits for the outsiders. Yet, outsiders who mimic insiders when buying, following large purchases by insiders, are not likely to earn abnormal profits. 6. Concluding Remarks Reported insider trading on the Hong Kong stock market between the period of 1993 and 1998 is examined in the study. The overall result shows that, even though there exists legislation to regulate transactions by corporate insiders, the directors, chief executives and substantial shareholders are still able to make abnormal profits from insider trading activities. In the aggregate, we find that insiders are able to earn abnormal profits from both insider buying and 19 selling activities in the short-run of up to 20 days after the transaction day. By examining the abnormal performance of stocks traded by insiders according to industry classification, firm size, book-to-market ratio of the firm, price-earnings ratio of the firm, and relative trading volume of the insider transactions, we see that some insider purchases produce large and persistent abnormal profits; the characteristics of these purchases are that the firm concerned is a finance or industrials company, the firm is small in terms of market value, the book-to-market ratio of the firm is large, the price-earning ratio of the firm is small, and the relative trading volume of the purchase is large. In terms of the profit opportunities for outsiders, they should be able to make abnormal profits by following most of the insider sales transactions when selling, but only selected insider purchase transactions when buying. 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Wu, 2000, “Insider Trading in the Hong Kong Stock Market,” Asia-Pacific Financial Markets 7, 275-288. 21 TABLE 1 Summary Statistics on Insider Trading Data from January 1993 to December 1998 Purchases Sales All Transactions Number of Transactions 16,221 7,574 23,675 Number of Firms with Insider Trading 507 458 541 Average Number of Shares Traded per Transaction 4,427,747 5,589,757 5,136,724 Average Value of Shares Traded per Transaction $9,225,137 $17,124,634 $11,487,213 Note: Purchases and Sales refer to open market purchases and open market sales, respectively, by company directors, chief executives and substantial shareholders. 22 TABLE 2 Frequency Distribution of Insider Trading Events by Industry Classification Industry group Purchases Sales All transactions Ratio of purchases to Number of sales companies* Finance 701 433 1,134 1.619 60 Utilities 123 87 210 1.414 15 Properties 5,276 1,666 6,942 3.167 108 Consolidated 4,299 2,772 7,071 1.551 207 Enterprises Industrials 4,838 2,196 7,034 2.203 259 Hotels 921 158 1,079 5.829 15 Miscellaneous 63 132 195 0.477 10 Source: Various issues of SEHK Monthly Bulletin published by The Stock Exchange of Hong Kong. Note: * The figures in the column refer to the number of companies in that industry classification as of the end of January 1998. Industry classification is assigned by the Stock Exchange according to the nature of the business of the company. 23 TABLE 3 Frequency Distribution of Insider Trading Events by Firm Size, Book-To-Market Ratio, Price- Earnings Ratio, and Relative Trading Volume Firm Size Book-To-Market Ratio Lowest Middle Largest Lowest Middle Largest 1/3 1/3 1/3 1/3 1/3 1/3 Purchase 6,141 5,291 4,784 3,387 4,425 5,203 Sales 1,900 2,571 2,981 3,191 2,030 1,284 All Transactions 8,041 7,862 7,765 6,578 6,455 6,487 Ratio of Purchase to Sales 3.232 2.058 1.605 1.061 2.180 4.052 Price-Earnings Ratio Relative Trading Volume Lowest Middle Largest Lowest Middle Largest 1/3 1/3 1/3 1/3 1/3 1/3 Purchase 4,712 4,607 3,691 5,527 5,586 5,103 Sales 1,836 1,842 2,825 2,345 2,318 2,791 All Transactions 6,548 6,449 6,516 7,872 7,904 7,894 Ratio of Purchase to Sales 2.566 2.501 1.307 2.357 2.410 1.828 Note: Firm size is measured by market capitalization. The firm size of an insider trading firm is calculated for every transaction based on the month-end figures of the month prior to that when the insider trading occurred. Book-to-market ratio is the ratio of the book value (i.e. total stockholders’ equity) to market value. The book value of the insider trading firm, for every transaction, is based on the fiscal year-end figures of the year prior to that year when insider trading occurred. The price-earnings ratio is the ratio of the current share price to earnings per share over the past year. Earnings-per-share of the insider trading firm for every transaction is based on the fiscal year-end figure of the year prior to that year when insider trading occurred. Relative trading volume in shares is defined as the number of shares traded in the insider trading transaction divided by the total shares outstanding. Total shares outstanding is based on the month-end figure of the month prior to that month when insider trading occurred, and is obtained from the PACAP databases. 24 TABLE 4 Cumulative Daily Abnormal Returns for Insider Trading Events Insider Purchase Insider Sales Event Window CAAR t-statistic Return t-statistic Pre-event Window (-20, -1) -0.0311 -15.37** 0.0258 7.53** Transaction Day (0) -0.0006 -1.37 0.0076 8.78** Post-event Window (+1, +5) 0.0019 2.01* -0.0114 -8.41** Post-event Window (+1, +10) 0.0043 3.14** -0.0228 -11.29** Post-event Window (+1, +20) 0.0058 2.72** -0.0414 -13.42** * Significant at the 5% level. ** Significant at the 1% level. 25 TABLE 5 Cumulative Daily Abnormal Returns for Insider Trading by Industry Classification Finance Utilities Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat (-20, -1) -0.065 -7.17** 0.061 6** 0.004 0.36 0.025 1.25 Transaction (0) -0.003 -1.41 0.008 4.07** -0.003 -1.16 0.006 1.36 (+1, +5) 0.010 2.35* 0.001 0.39 -0.001 -0.27 0.005 0.74 (+1, +10) 0.013 1.82 0.003 0.55 -0.003 -0.7 -0.008 -0.68 (+1, +20) 0.028 3.2** 0.002 0.18 0.001 0.07 -0.024 -1.61 Properties Consolidated Enterprises Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat (-20, -1) -0.014 -5.95** 0.015 1.94 -0.043 -10.06** 0.014 2.77** Transaction (0) 0.000 0.14 0.003 1.8 -0.002 -1.92 0.009 5.45** (+1, +5) 0.002 1.49 -0.014 -5.09** 0.003 1.37 -0.011 -4.95** (+1, +10) 0.003 1.49 -0.022 -5.01** 0.004 1.12 -0.024 -7.43** (+1, +20) 0.004 1.26 -0.040 -5.83** -0.004 -0.79 -0.040 -8.51** Industrials Hotels Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat (-20, -1) -0.044 -8.34** 0.039 5.55** -0.007 -1.62 0.028 1.9 Transaction (0) 0.000 0.2 0.010 6.83** -0.001 -1.2 0.003 0.77 (+1, +5) -0.000 -0.21 -0.014 -5.37** 0.004 1.37 -0.001 -0.09 (+1, +10) 0.008 2.49* -0.031 -7.64** 0.001 0.17 -0.002 -0.2 (+1, +20) 0.017 3.54** -0.060 -9.24** -0.000 -0.02 0.025 1.4 * Significant at the 5% level, ** Significant at the 1% level. 26 TABLE 6 Cumulative Daily Abnormal Returns for Insider Trading Events by Size, Book-to-Market Ratio, Price Earnings Ratio and Relative Trading Volume of the Firm Panel A: Firm Size Smallest 1/3 Middle 1/3 Largest 1/3 Insider Purchase Insider Sales Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat ** ** ** ** (-20, -1) -0.062 -12.04 0.016 1.79 -0.022 -5.75 0.025 4.16 -0.019 -9.01 0.031 6.94** Transaction (0) 0.001 0.74 0.005 2.14* -0.001 -0.87 0.009 6.76** -0.002 -3.61** 0.008 8.37** (+1, +5) 0.003 1.52 -0.021 -6.21** 0.001 0.75 -0.015 -6.21** 0.001 1.15 -0.003 -1.77 (+1, +10) 0.012 3.57** -0.040 -7.73** -0.000 -0.1 -0.029 -8.23** 0.002 1.43 -0.008 -3.33** (+1, +20) 0.027 5.07** -0.069 -8.61** -0.003 -0.69 -0.049 -9.19** -0.000 -0.1 -0.022 -5.59** Panel B: Book-To-Market Ratio Smallest 1/3 Middle 1/3 Largest 1/3 Insider Purchase Insider Sales Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat (-20, -1) -0.0338 -7.06** 0.0354 5.98** -0.0230 -6.81** 0.0210 4.01** -0.0307 -10.25** 0.0196 3.27** Transaction (0) -0.0014 -1.66 0.0104 8.3** -0.0015 -2.13* 0.0095 6.83** 0.0002 0.37 0.0044 2.96** (+1, +5) -0.0020 -1.1 -0.0121 -5.14** -0.0005 -0.31 -0.0097 -4.66** 0.0015 1.14 -0.0097 -3.55** (+1, +10) -0.0047 -1.69 -0.0319 -9.41** 0.0000 0 -0.0191 -6.07** 0.0043 2.14* -0.0129 -3.5** (+1, +20) -0.0200 -4.6** -0.0600 -11.75** -0.0030 -0.73 -0.0380 -7.99** 0.0078 2.56* -0.0099 -1.62 27 Panel C: Price Earnings Ratio Smallest 1/3 Middle 1/3 Largest 1/3 Insider Purchase Insider Sales Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat (-20, -1) -0.0437 -9.9** 0.0173 2.36* -0.0208 -7.32** 0.0153 3.14** -0.0237 -6.68** 0.0430 7.56** Transaction (0) -0.0010 -1.33 0.0082 5.05** -0.0009 -1.32 0.0063 4.8** -0.0002 -0.23 0.0111 9.07** (+1, +5) 0.0016 0.98 -0.0170 -5.57** 0.0003 0.21 -0.0078 -3.77** -0.0026 -1.61 -0.0084 -3.89** (+1, +10) 0.0060 2.2* -0.0343 -8.12** -0.0011 -0.57 -0.0207 -6.71** -0.0039 -1.7 -0.0183 -5.64** (+1, +20) 0.0052 1.16 -0.0544 -8.57** -0.0018 -0.66 -0.0303 -6.77** -0.0140 -3.48** -0.0433 -8.22** Panel D: Relative Trading Volume Smallest 1/3 Middle 1/3 Largest 1/3 Insider Purchase Insider Sales Insider Purchase Insider Sales Insider Purchase Insider Sales Event Window CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat CAAR t-stat (-20, -1) -0.036 -14.71** 0.018 4.72** -0.035 -12.44** 0.019 3.85** -0.018 -4.95** 0.031 5.73** Transaction (0) -0.002 -2.97** 0.007 8.06** -0.002 -3.71** 0.009 8.43** 0.001 1.91 0.011 6.86** (+1, +5) 0.002 1.56 -0.008 -4.99** 0.002 1.08 -0.011 -5.53** 0.000 -0.03 -0.016 -7.33** (+1, +10) 0.004 1.79 -0.012 -5.82** 0.006 2.69** -0.021 -7.07** 0.003 1.2 -0.034 -10.65** (+1, +20) 0.003 1.06 -0.031 -9.56** 0.003 1.02 -0.039 -7.77** 0.006 1.68 -0.063 -12.39** * Significant at the 5% level, ** Significant at the 1% level.