insider trading and performance of seasoned equity offering firms after controlling for exogenous...

Insider trading and performance of seasoned equityoffering firms after controlling for exogenous

trading needs

Inmoo Lee*

Department of Business Administration, Korea University, Seoul 136-701, Korea

Abstract

Insiders trade not only because they have private information about their companies but alsobecause of other exogenous reasons. Therefore, it is important to control for exogenous trading needsin empirical studies regarding insider trading. Lee (1997) shows that insider trading is not closelyrelated to the long-term performance of primary seasoned equity offering firms. This paper examineswhether the results hold after controlling for exogenous needs to trade by using an inequality test withinstrumental-variables technique. © 2002 Board of Trustees of the University of Illinois. All rightsreserved.

JEL classification: G000, G140, G300

Keywords: Insider trading; Exogenous trading needs; Inequality test with instrumental variables

1. Introduction

Insiders trade not only because they have private information about their companies’future performance but also because of many other exogenous needs to trade (e.g., housedown payments, college tuition payments for the kids, payments related to divorce settle-ments, seed money for a new business, and hostile takeover defenses). For example, Hulbertdiscusses the problems related to an investment strategy using inside trading information,and emphasizes that insider trading is motivated not only by inside information about the

* Tel.: �82-2-3290-1954; fax: �82-2-925-3681.E-mail address: [email protected] (I. Lee).

The Quarterly Review of Economics and Finance 42 (2002) 59–72

1062-9769/02/$ – see front matter © 2002 Board of Trustees of the University of Illinois. All rights reserved.PII: S1062-9769(01)00086-2

firm but also by personal reasons not related to special knowledge about the firm [Forbes(August 15, 1994, page 145)]. However, most empirical studies in the insider tradingliterature [Jaffe (1974), Finnerty (1976), Elliot, Morse, and Richardson (1984), Givoly andPalmon (1985), Seyhun (1986), Rozeff and Zaman (1988), Lin and Howe (1990), John andLang (1991), and Lee (1997) among others] do not control for exogenous trading needs. Thisis not because they do not recognize the importance of exogenous trading needs, but becauseit is hard to control for unobservable exogenous trading needs.

Here, an inequality test with instrumental variable method (ITIV) is introduced as one wayto control for exogenous trading needs in empirical studies regarding insider trading. As anexample, the ITIV method is used to control for exogenous trading needs in the examinationof the relation between pre-issue insider trading and the post-issue long-run performance ofprimary seasoned equity issuing companies. Lee (1997) shows that there is no close relationbetween insider trading and the long-run performance of primary seasoned equity issuingfirms. Lee points out that the poor relation might be due to the fact that exogenous tradingneeds are not controlled for in the study. It is shown that the ITIV method can be used toexamine this issue.

The rest of the paper is organized as follows. Section 2 describes the data and summarystatistics, and Section 3 presents the inequality test with instrumental variables methodology.Finally, Section 4 summarizes the results and presents some concluding remarks.

2. Data and summary statistics

The sample consists of primary seasoned equity offerings during 1976–1990 that havebeen recorded by the Securities Data Company (SDC). Similar to Lee (1997), the followingfirms are excluded from the original SEO sample: 1) firms which do not have price recordson the CRSP daily NYSE/Amex or Nasdaq tapes on their offering date; 2) utility companies(SIC codes 4910–4949), closed-end mutual funds (SIC codes 6720–6739) and real estateinvestment trusts (REITs: SIC code 6798); 3) firms which do not have any insider trading forthe 6 months ending on, and including, the issue date; and 4) firms that do not have bookequity value for the fiscal year before their SEOs in any of the following data sources:COMPUSTAT, Moody’s various manuals, and Standard and Poor’s Stock Report. An SEOis also excluded if more than half of the total offering consists of secondary shares (sharessold by existing shareholders). Finally, any SEOs by the firms that have issued seasonedshares during the prior 36-month period are excluded. 1,281 SEOs are in the sample. Fig. 1Apresents the annual volume of SEOs in the sample for each year during 1976–1990. Note thatthere are large variations in the volume of SEOs during this sample period.

The insider trading data is from the Securities and Exchange Commission’s (SEC)Ownership Reporting System (ORS) data file that contains all transactions by insiders subjectto disclosure according to the Securities and Exchange Act of 1934. Insiders are defined asofficers, directors and controlling persons, and insider trading activity includes both openmarket and private transactions.

Five prior return, size and book-to-market equity ratio-adjusted matching firms are usedas a benchmark. The same selection procedures as those described in Lee (1997) are used.

60 I. Lee / The Quarterly Review of Economics and Finance 42 (2002) 59–72

Fig. 1B presents the distribution of SEO firms across size and book-to-market equity ratio(BM) quintiles. Notice that most issuing firms are in the lower BM quintiles (growth firms)and the middle size quintiles.

3-year buy-and-hold returns (BHRs) are used to measure the long-term performance. The

Fig. 1. The number of seasoned equity offerings (SEOs) during 1976–1990 in the sample. The sample consistsof 1,281 seasoned equity offerings (SEOs) of pure primary or combined primary and secondary shares (with theprimary proportion at least 50% of the total) by firms listed on the CRSP NYSE/Amex and Nasdaq tapes.Offerings by utilities (SIC codes 4910–4949), closed-end mutual funds, REITs, firms with any SEOs during theprior 3-year period, firms with no insider trading over the 6-month period ending on the issue date, and firms withno book value information in COMPUSTAT, Moody’s manuals, or Standard and Poor’s Stock Report, areexcluded. The cut-off points for size are based on the last day of the previous month (one month before issue)market capitalization of all CRSP-listed NYSE/Amex firms and the cut-off points for BM, the book-to-marketratio of equity, are based on the last day of the previous month BM of all CRSP-listed NYSE/Amex and Nasdaqfirms.

61I. Lee / The Quarterly Review of Economics and Finance 42 (2002) 59–72

BHRs are calculated by compounding daily returns over either 756 trading days or thenumber of trading days from the offering date until the delisting date, whichever is smaller.The same holding periods are used to calculate the BHRs of matching firms. If a matchingfirm is delisted before the end of the 3-year anniversary or the SEO firm’s delisting day,whichever is earlier, the CRSP value-weighted return1 is spliced into the calculation of theBHR from the removal date.

Table 1 reports summary statistics. There are 569 NYSE/Amex-listed firms and 712Nasdaq-listed firms in the sample. NYSE/Amex-listed issuing firms’ average market capi-talization ($1,299 million) is much larger than the average of Nasdaq-listed issuing firms($237 million) and the average book-to-market equity ratio (BM) of NYSE/Amex-listedfirms is higher than the average BM of Nasdaq-listed firms. The average one-year holdingperiod return of SEO firms before issuing [86.2%: median (60.0%)] is extremely high, whichis consistent with previous studies.

3-year buy-and-hold returns (BHR) of SEO firms and matching firms for differentexchanges (for a given SEO firm, its matching firm may or may not be from the sameexchange) are also reported in Table 1. Consistent with previous studies [e.g., Loughran andRitter (1995) and Lee (1997)], the results show that SEO firms significantly underperformtheir matching firms. The wealth relatives (WR), defined as {1 � average BHR of SEO firms}divided by {1 � average BHR of matching firms}, are less than 1. We can observe noticeabledifferences in WRs between NYSE/Amex-listed companies and Nasdaq-listed companies.The average WR of NYSE/Amex-listed companies is 0.94 and that of Nasdaq-listed com-panies is 0.85. The smaller average 3-year WR of Nasdaq-listed firms may result from thefact that more informational asymmetry is present in smaller and younger companies, mostof which are listed on the Nasdaq exchange.2

Table 2 reports the summary statistics of insider trading before and after SEOs by bothissuing firms and matching firms. For the 6-month period prior to, and including issue dates,SEO firms’ insiders bought 1.81 times and sold 5.53 times, whereas the matching firms’insiders bought 1.34 times and sold 3.73 times. While the average ratio of purchasetransaction3 [i.e., the number of purchases/(the number of purchases � the number of sales)]of SEO firms (0.32) is larger than that of matching firms (0.29), the median of SEO firms(0.12) is smaller than the median of matching firms (0.22). The Wilcoxon rank-sum testresult shows that the ratio of issuing firms is statistically significantly lower than the ratio ofmatching firms, implying that even though the prior annual returns of issuing firms and thoseof matching firms are similar by construction, the issuers’ purchase transactions proportionis significantly smaller than the matching firms’ purchase proportion.4 This suggests that onaverage, the issuing firms’ insiders consider their shares as more overvalued than theirmatching firms’ insiders do. Still, the difference is surprisingly small.

By comparing the prior and post insider trading of SEO firms, we notice that the averagenumber of sell transactions has significantly dropped, while the average purchase ratio hassignificantly increased after issuing. Moreover, the insider trading patterns of SEO firms afterissuing are not statistically significantly different from those of matching firms. Again, thisis consistent with managers intentionally “timing” their issues. These results, however, raisethe question of whether insiders really know how much their shares are overvalued. BothLoughran and Ritter (1995) and Spiess and Affleck-Graves (1995) show that even one year


after issuing, the shares of SEO firms are substantially overvalued, indicating that the optimalinsider purchase ratio should be lower even after issue.5

Table 3 reports the different characteristics of SEO firms depending on the previousinsider trading. As in Lee (1997), a pure insider trading criterion is used to classify SEOs intobuyer vs. seller groups. Pure insider purchasing firms (PP) are companies with insiders only

Table 1Summary statistics: mean and median

NYSE/Amex Nasdaq Total

# of SEOs 569 712 1,281Market Capitalization 1,299 237 709

(in million)a [345] [106] [163]B/M ratiob 0.64 0.47 0.55

[0.59] [0.38] [0.46]SEO Prior 78.2% 92.6% 86.2%

1-year Returnc [58.6%] [60.7%] [60.0%]MF Prior 69.8% 80.9% 76.0%

1-year returnd [53.2%] [56.7%] [55.1%]SEO Post 48.2% 24.8% 35.2%

3-year Returne [21.7%] [0.0%] [10.1%]MF Post 58.0% 47.4% 52.3%

3-year Returnf [53.4%] [35.9%] [43.7%]Wealth Relatives 0.94 0.85 0.89

[0.79] [0.74] [0.77]

The sample consists of 1,281 seasoned equity offerings (SEOs) of pure primary or combined primary andsecondary shares (with the primary proportion at least 50% of the total) during 1976–1990 by firms listed on theCRSP NYSE/Amex and Nasdaq tapes. Offerings by utilities (SIC codes 4910–4949), closed-end mutual funds,REITs, firms with any SEOs during the prior 3-year period, firms with no insider trading over the 6-month periodbefore issues (including issue dates), and firms with no book value information in COMPUSTAT, Moody’smanuals, or Standard and Poor’s Stock Report, are excluded. At the time of a new issue, each SEO firm ismatched with 5 seasoned firms which have the closest prior annual returns among the firms in the same size andBM quintiles. If any of these matching firms are delisted prior to the end of the corresponding SEO firms’ holdingperiods, the CRSP value-weighted returns are spliced into the calculation of the returns from the removal dates.The mean number is reported on top and the median number is in the bracket.

a The market capitalization of an SEO firm is calculated by multiplying the number of shares outstanding afterissue by the offering date closing price, and converted into dollars of 1993 purchasing power using the USconsumer price index (CPI).

b The book to market ratio (BM) of an SEO firm is calculated by dividing the book equity value after issue bythe market value of equity at the close of the issue day.

c The prior return of an SEO firm is the raw buy-and-hold return of the SEO firm for the 252 trading daysending on the day before the issue date, or the number of days between the first listed date and the day beforethe issue date, whichever is smaller.

d The prior return of matching firms is the average of the raw buy-and-hold return of 5 matching firms for thesame holding period as the corresponding SEO firm’s. The median is the median of 1,281 mean prior returns.

e The 3 year buy-and-hold % return (BHR) of SEO firms. If an SEO firm is delisted before its 3rd anniversary,the buy-and-hold return from the issue date to the delisting date is used as the BHR.

f The 3 year buy-and-hold % returns of matching firms. The daily returns are compounded over the sameholding periods as the corresponding SEOs’ holding periods. If any of matching firms are delisted prior to the endof the corresponding SEO firm’s holding period, the CRSP value-weighted index returns are spliced into thecalculation of the returns from the removal date.


purchasing their shares without any selling for the previous 6-month period including issuedates. Pure insider selling firms (PS) are similarly defined. Firms that are neither PP nor PSare classified as mixed insider trading firms (MT).

Even though the average prior annual return of buyers is high (63.4%), the average ofsellers is much higher (97.1%). This is consistent with the conjecture that after a huge pricerun-up, insiders will want to sell more either to diversify their portfolios or to lock up theprofits. On average, there is no significant relative (relative to their matching firms) perfor-mance differences among the firms in different insider trading groups.

Fig. 2 shows the average annual returns of both SEO firms and their matching firms duringthe 4 years before and after issue. Panel A presents the average annual returns of buyers andPanel B presents those of sellers. Both buyers and sellers do not significantly underperformtheir matching firms during the first year, but they start to do so during the second year. Theaverage annual return of buyers is 9% per year, compared to 14% for their matching firms,

Table 2Insider trading

Summary statistics of insider trading

SEO Matching

Average[median]ratioa

Average[median]# ofpurchases

Average[median]# ofsales

Average[median]ratio

Average[median]# ofpurchases

Average[median]# ofsales

Prior 0.32 1.81 5.53 0.29 1.34 3.73[0.12] [1.00] [3.00] [0.22] [0.80] [2.80]

Post 0.40 2.03 4.11 0.36 1.33 2.76[0.50] [0.00] [2.00] [0.29] [0.60] [1.60]

Wilcoxon Rank Sum Test results: Z-statistics (two-sided P-values are in parentheses)

Prior vs. post SEO vs. matching (ratio only)

Ratio # ofpurchases

# of sales Prior Post

6.18 �2.20 �9.34 5.18 �1.18(0.00) (0.03) (0.00) (0.00) (0.23)

The sample consists of 1,281 seasoned equity offerings (SEOs) of pure primary or combined primary andsecondary shares (with the primary proportion at least 50% of the total) during 1976–1990 by firms listed on theCRSP NYSE/Amex and Nasdaq tapes. Offerings by utilities (SIC codes 4910–4949), closed-end mutual funds,REITs, firms with any SEOs during the prior 3-year period, firms with no insider trading over the 6-month periodbefore issues (including issue dates), and firms with no book value information in COMPUSTAT, Moody’smanuals, or Standard and Poor’s Stock Report, are excluded. At the time of a new issue, each SEO firm ismatched with 5 seasoned firms which have the closest prior annual returns among the firms in the same size andBM quintiles. Insiders are defined as officers, directors and controlling persons and insider trading activityincludes both open market and private transactions. All insider trading during the 6-month period ending on theissue date is defined as the prior insider trading and all insider trading during the 6-month period starting on theday after the issue date is defined as the post insider trading.

a Ratio is defined as (number of Purchases)/(number of Purchases � number of Sales). If there is no insidertrading, the ratio is set equal to 0.5.


during the 3 years following the offering. For sellers, the average annual return is 11% peryear, compared to 15% for their matching firms.

The results indicate that there is no strong relation between insider trading during the 6 monthsending at the time of the SEO and the long-run stock price performance of SEO firms. This poorperformance of insider trading as a signal of the future prospects can be attributed to the fact thatconsumption shocks are not controlled for in this section. To examine this possibility, aninequality test with instrumental variables is used in the following section.

Table 3The long-run performance and insider trading of SEO firms

NYSE/Amex Nasdaq TOTAL

PP MT PS PP MT PS PP MT PS

SEO BHRa 33.7% 55.1% 47.4% 22.7% 33.2% 19.4% 27.2% 43.6% 31.5%MF BHRb 59.3% 60.7% 55.2% 37.5% 55.8% 45.1% 46.3% 58.1% 49.5%WRc 0.84 0.96 0.95 0.89 0.86 0.82 0.87 0.91 0.88SEO PRd 51.9% 76.3% 89.3% 71.2% 90.0% 103.0% 63.4% 83.4% 97.1%MF PRe 46.1% 69.5% 78.5% 65.0% 76.5% 90.4% 57.3% 73.2% 85.2%Market Cap

$ millionsf1,714 1,494 982 206 226 257 819 830 571

# of SEOs 91 223 255 133 245 334 224 468 589

The sample consists of 1,281 seasoned equity offerings (SEOs) of pure primary or combined primary andsecondary shares (with the primary proportion at least 50% of the total) during 1976–1990 by firms listed on theCRSP NYSE/Amex and Nasdaq tapes. Offerings by utilities (SIC codes 4910–4949), closed-end mutual funds,REITs, firms with any SEOs during the prior 3-year period, firms with no insider trading over the 6-month periodbefore issuing (including issue dates), and firms with no book value information in COMPUSTAT, Moody’smanuals, or Standard and Poor’s Stock Report, are excluded. Pure insider purchases firms (PP) are companieswith only insider purchases and no insider sales for the previous 6-month period including issue dates. Pureinsider sales firms (PS) are similarly defined. Firms without PP or PS are classified as mixed insider trading firms(MT).

a 3-year buy-and-hold % return (BHR) of SEO firms. If an SEO is delisted before its 3-year anniversary, an SEOBHR is the buy-and-hold return from the issue date to the delisting date.

b 3-year buy-and-hold % returns of matching firms. The daily returns are compounded over the same holdingperiods as the corresponding SEOs’ holding periods. At the time of a new issue, each SEO firm is matched with5 seasoned firms (listed on the CRSP for at least five years) which have the closest prior annual returns amongthe firms in the same size and B/M quintiles. If any of these matching firms are delisted prior to the end of thecorresponding SEO firm’s holding period, the CRSP value-weighted index returns are spliced into the calculationof the returns from the removal date. The universe of firms from which matching firms are picked includes alloperating companies (excluding utilities) listed on the NYSE/Amex and Nasdaq CRSP tapes, that have notconducted any equity issue during the prior 5-year period.

c The wealth relatives (WR) are defined as [(1 � average SEO firms’ BHR)/(1 � average matching firms’BHR)].

d The prior return of an SEO firm is the raw buy-and-hold return of the SEO firm for the 252 trading daysending on the day before the issue date, or the number of days between the first listed date and the day beforethe issue date, whichever is smaller.

e The prior return of matching firms is the average of the raw buy-and-hold returns of 5 matching firms for thesame holding period as the corresponding SEO firm’s.

f The market capitalization of an SEO firm is calculated by multiplying the number of shares outstanding afterissue by the offering date closing price, and converted into dollars of 1993 purchasing power using the USconsumer’s price index (CPI).


3. Statistical tests with control for exogenous needs to trade

In this section, an inequality test with instrumental variables methodology (ITIV) isintroduced to examine whether or not the poor relation between insider trading and the

Fig. 2. Annual returns for SEO firms and matching firms. The sample consists of 1,281 seasoned equity offerings(SEOs) of pure primary or combined primary and secondary shares (with the primary proportion at least 50% ofthe total) during 1976–1990 by firms listed on the CRSP NYSE/Amex and Nasdaq tapes. Offerings by utilities(SIC codes 4910–4949), closed-end mutual funds, REITs, firms with any SEOs during the prior 3-year period,firms with no insider trading over the 6-month period before issuing (including issue dates), and firms with nobook value information in COMPUSTAT, Moody’s manuals, or Standard and Poor’s Stock Report, are excluded.Pure insider purchases firms are companies with only insider purchases and no insider sales for the previous6-month period including issue dates. Pure insider sales firms are similarly defined. There are 224 pure purchasingSEOs and 589 pure selling SEOs in the sample. The offering date is the beginning of year 0. Matching firms arenon-issuers chosen on the basis of offer date market capitalization, book-to-market equity ratio, and prior annualreturn.


long-run performance of issuing firms is caused by the fact that exogenous trading needs arenot controlled for in the previous section. Boudoukh, Richardson and Smith (1993: BRShereafter) and the references therein describe this ITIV methodology in detail. BRS test thepositivity of the ex ante risk premium by employing an instrumental variables approach totake into account the unobservability of expected returns. Similar to BRS, an instrumentalvariables approach is used to control for unobservable consumption shocks. In this section,it is examined whether buyers outperform their matching firms. If only those insiders in theSEO firms with good quality projects buy shares, the average performance of buyers will bebetter than their matching firms’ average performance.

When we do not control for consumption shocks, the outperformance of SEO firms withprior insider purchases corresponds to the following hypothesis.

H0 : E �SEO BHR � MF BHR� � AR � 0

HA : E �SEO BHR � MF BHR� � AR � R

where SEO BHR is the 3-year holding period return of a buyer and MF BHR is the averageBHR of the matching firms. R represents the real domain. To control for consumption shocks,both sides of the equation are multiplied by nonnegative instrumental variables representingeach factor of the consumption shocks.

H0 : E ��SEO BHR � MF BHR� � Z�� AR � Z� � 0

HA : E ��SEO BHR � MF BHR� � Z�� AR � Z� � RN

Z� is a vector with N nonnegative instrumental variables. Note that the inequality relationholds since nonnegative instrumental variables are multiplied in both sides. Instrumentalvariables that proxy for a big consumption shock are chosen because the insiders with bigconsumption shocks (i.e., exogenous needs to sell their shares) will not purchase their firms’shares unless they have favorable inside information. By using instrumental variables, wecan focus on the firms with insiders who are more likely to have bought the stocks becauseof the inside information regarding the future prospects of the company, rather than someexogenous needs to trade.

The instrumental variables used in the test are listed in Table 4. First, the exogenous needsto sell will be related to diversification needs. As diversification needs increase, insiders’current consumption needs also increase. The previous good performance of the companyrelative to the market would suggest that the portion of wealth invested into the company’sstock increased more than was desired. Two instrumental variables, APR {SEO firm’s priorannual return (SEO PR) � CRSP value-weighted index’s prior annual return (VWPR)} andSAPR {APR standardized by variances: SEO PR/Var(SEO PR) � VWPR/Var(VWPR)}, areused to measure the relative performance of SEO firms and the market.

Second, the exogenous need to sell is a function of insiders’ unexpected consumptionneeds. For example, unexpected medical expenses would increase the exogenous need tosell. Since it is difficult to believe that an unexpected consumption need will occur to allinsiders in a company, the total number of insider transactions is used as a proxy variable for


emergency needs. The larger the number of insider transactions, the less likely there is anemergency.

Third, the exogenous need to trade will depend on any kinds of threats to the safety ofinsiders’ positions at the company. For instance, if there is any hostile takeover threat thatinsiders want to defend against, insiders will increase their holdings. Therefore, the firms thathave taken any anti-takeover measure during the 1-year period before and after SEOs aretreated as a group of companies with insiders’ exogenous need to buy their shares (i.e., theymight purchase their shares not because of favorable insider information but because theywant to defend against the hostile takeover attempt). As a first step to incorporate this idea,600 companies listed in the appendix of Jarrell and Poulsen (1987) are used as the populationof firms with any anti-takeover measure.6 Notice that this variable is the only instrumentalvariable that is not publicly available at the time of issue.

For an instrumental variable (Zi) which has a positive (negative) prior relation with theexogenous need to sell, the value is transformed by setting Z*i � 1 if the value of theinstrumental variable is larger (smaller) than the average, and Z*i � 0 otherwise. This is touse only those firms with insiders who are more likely to have great needs to sell their shares.

Using these instrumental variables, the inequality tests are conducted. Detailed descriptionof test procedures appears in Appendix.

The results are reported in Table 5. The null hypothesis of a positive abnormal return of

Table 4Instrumental variables used in the inequality test

Factor InstrumentalVariables

Expecteda

RelationValue ofInstrument

1) Diversification APR �[SEO PRb � VWPRc]

Positive Z*i � 1 if Zi � Z� � 0.60� 0 otherwise

SAPR �[SEO PR/Var(SEO PR)d

� VWPR/Var(VWPR)]

Positive Z*i � 1 if Zi � Z� � �1.08� 0 otherwise

2) Emergencies NIT �Total # ofinsider transactions

Negative Z*i � 1 if Zi Z� � 7.33� 0 otherwise

3) Control ANTI �Any takeover actione

Negative Z*i � 1 if there is noannouncement

� 0 otherwise

Table shows the list of instrumental variables used in the inequality test described in Section 3. Eachinstrumental variable proxies for a big exogenous consumption shock.

a Represents expected correlation between instrumental variables and exogenous trading needs to sell.b SEO PR is the raw buy-and-hold return of an SEO firm for 252 trading days ending on the day before issue

date, or the number of days between the first listed date and the day before issue date, whichever is smaller.c VWPR is the PR of the CRSP value-weighted index.d The variance of SEO PR (and VWPR) is calculated by using the daily returns over the same holding period

as the one used to calculate SEO PR.e If there exists no anti-takeover measure announcement during the one year period before and after SEO, the

instrument is set to 1 and 0 otherwise. Only the anti-takeover measure announcements in Jarrell and Poulsen(1987: by 600 firms in the period 1979–1985) are used.


issuing firms with prior insider purchases is rejected at a 10% significance level in every case.Notice that there is no case in which the average transformed (by multiplying instrumentalvariables) abnormal return is positive. These results strongly suggest that insider purchasesare not a credible signal of the issuing firms’ good future stock price performance even whenwe focus on those firms the insiders of which would have not purchased due to someexogenous needs to trade. We cannot pick better quality issuing firms just by looking at thenumber of prior insider purchases.

4. Summary and conclusion

Previous empirical studies in the insider trading literature have not controlled for insiders’exogenous trading needs because it is difficult to measure those exogenous needs. Forexample, Lee (1997) documents a poor relation between pre-issue insider trading and thepost-issue long-run performance of primary seasoned equity issuing firms, and points out thatthe poor relation might be due to no control of exogenous trading needs in his tests.

An inequality test with instrumental variables (ITIV) method is introduced as a way tocontrol for exogenous consumption shocks in empirical studies on insider trading. This ITIVmethod has been used in statistical tests involving unobservable factors. For example,Boudoukh, Richardson, and Smith (1993) use the ITIV method in their test of the positivityof the ex ante risk premium to take into account the unobservability of expected returns.

This ITIV method is used to examine whether or not there is any close relation betweenpre-issue insider trading and the post-issue long-run performance of primary seasoned equityissuing firms after controlling for exogenous consumption shocks. It turns out that we cannot

Table 5Inequality test results

Mean of ARa (in %) W-statistics p-value

APR SAPR NIT ANTI

Total �6.5 �16.4 �21.1 �17.7 11.66 0.001NYSE/Amex �10.9 �23.8 �27.7 �23.8 8.58 0.005Nasdaq �3.4 �11.3 �16.5 �13.5 4.16 0.060

This table reports the results of the inequality test described in Section 3. The hypothesis of the test is; H0:E(SEO BHR � Average Matching Firms’ BHR) V Z� � 0; and HA : E(SEO BHR � Average Matching Firms’BHR) V Z� � R, where SEO BHR is the 3-year holding period return of SEO firms with prior pure insiderpurchases (PP). The matching firms are 5 firms that have the closest prior annual returns among the firms in thesame size and BM quintiles. W-statistic is defined in the paper and is distributed as a weighted sum of chi-squareddistribution. The weights are estimated by using the Monte Carlo simulation method with 10,000 draws. PP firmsare the ones with only insider purchases and no insider sales for the previous 6-month period including issuedates.

a The mean of abnormal return (SEO’s BHR � the average BHR of the matching firms) after multiplyinginstrument values for each observation. APR � [SEO prior annual return � CRSP value-weighted index’s priorannual return], SAPR � [SEO prior return/Var(SEO prior return) � CRSP value-weighted index’s priorreturn/Var(CRSP value-weighted index’s return)], NIT is the number of total insider trading, and ANTI is antitakeover measure announcement.


observe a close relation even after indirectly controlling for exogenous consumption shocks. Thissupports the Lee’s (1997) contention that the poor relation is likely to be due to increased freecash flow problems after primary seasoned equity offerings rather than due to exogenousconsumption shocks. In addition, the decrease in insider sales right after primary SEOs alsosupports this since primary SEO firms are substantially overvalued right after the primary SEOs.

In summary, this paper emphasizes the importance of exogenous consumption shocks ininsider trading, and stresses the needs to control for exogenous needs to trade in empirical studieson insider trading. It would be interesting to see whether or not the indirect control of exogenoustrading needs change the empirical results documented in the insider trading literature.

Notes

1. Throughout the paper, the value-weighted NYSE/Amex index return is used for theNYSE/Amex-listed firms and the value-weighted Nasdaq index return is used for theNasdaq-listed firms.

2. Related to the differences between NYSE/Amex SEO firms and Nasdaq SEO firms,Loderer, Sheehan and Kadlec (1991) report that there is virtually no evidence ofshort-run underpricing for NYSE SEOs, mixed evidence for Amex SEOs, and strongevidence for Nasdaq SEOs.

3. If there is no insider trading, the ratio of purchase transaction is set equal to 0.5.4. Both Karpoff and Lee (1991) and Kahle (1995) also show that the number of insider

sales significantly increases before SEOs.5. It is possible that the lock-up provision (usually 90 days or 180 days) has caused the

results since the insiders of issuing firms are not allowed to sell their shares without theprior written consent of underwriters within this period. To see whether this is the maincause, several different 6-month periods (including the one starting 3 months afterissuing) were examined and the results were similar to the one reported in Table 2.

6. These are the companies that adopted antitakeover amendments in the period 1979–1985.

Acknowledgments

I would like to thank Narasimhan Jegadeesh, Tim Loughran, Neil Pearson, GeorgePennacchi, and Jay Ritter for many helpful comments. I am also grateful to seminarparticipants at the University of Waterloo, University of Illinois, Purdue University, Uni-versity of Arizona, University of New Orleans, Case Western Reserve University andMichigan State University for useful discussions.

Appendix A. Statistical test procedures using the inequality test withinstrumental variables methodology

First, the sample mean, ARZ� is estimated. Each element of the vector ARZ� is estimatedas follows.


ARZ�i

�1

T�j�1

T

�Rj � Rjm� � zji

�, @i � 1, . . . N

where Rj is the 3-year buy-and-hold return of buyer j, Rjm is the average 3-year holding

period return of the matching firms, Zji� is the ith instrumental variable for buyer j, and T is

the total number of SEOs. The covariance matrix () is estimated by using White’s (1980)heteroskedasticity-consistent estimator. Then, the following quadratic programming problemis solved and ARZ�

R , a restricted (to be positive) estimator of ARZ�, is estimated.

MinARZ�

�ARZ� � ARZ��1�ARZ� � ARZ��

s.t. ARZ� � 0

Finally, the test statistic, W, is defined as

W � T�ARZ�R � ARZ��1�ARZ�

R � ARZ��

Wolak (1989) shows that the asymptotic distribution of W-statistic satisfies

supARz��0

Pr�W � c� � �k�0

N

Pr��k2 � c�w�N, N � k,

T � ,

where c � R� is the critical value for a given size; Pr (W � c) is the probability of W greaterthan a critical value c given ARZ

� and /T; Pr[�k2 � c] is the probability of chi-squared

variable with k degrees of freedom being greater than c; and w(N, N�k, /T) is theprobability that ARZ�

R has exactly N�k positive elements. A Monte Carlo simulation methodis used to estimate the weight, w, and is described in the following [see also Wolak (1989)and Boudoukh, Richardson and Smith (1993)].

1. Generate 10,000 random N � 1 vectors (Xs) from the multivariate normal distributionwith zero mean and covariance matrix (/T).

2. For each random vector, X, the following minimization problem is solved to get XR

MinX

�X � X��/T��1�X � X�

s.t. X � 0

3. The weights are estimated as the fraction of 10,000 XRs which have exactly N � kelements exceeding 0.

Note: IMSL (FORTRAN) subroutines are used to generate the random vectors and to solvethe minimization problems.

References

Boudoukh, J., Richardson, M., & Smith, T. (1993). Is the ex ante risk premium always positive? A new approachto testing conditional asset pricing models. Journal of Financial Economics, 34, 387–408.


Elliot, J., Morse, D., & Richardson, G. (1984). The association between insider trading and informationannouncements. Rand Journal of Economics, 15, 521–536.

Finnerty, J. E. (1976). Insiders and market efficiency. Journal of Finance, 31, 1141–1148.Givoly, D., & Palmon, D. (1985). Insider trading and the exploitation of inside information: some empirical

evidence. Journal of Business, 58, 69–87.Jaffe, J. F. (1974). Special information and insider trading. Journal of Business, 47, 410–428.Jarrell, G. A., & Poulsen, A. B. (1987). Shark repellents and stock prices: the effects of antitakeover amendments

since 1980. Journal of Financial Economics, 19, 127–168.John, K., & Lang, L. H. P. (1991). Insider trading around dividend initiation: theory and evidence. Journal of

Finance, 46, 1361–1390.Kahle, K. M. (1995). Insider trading and new securities issues. Working paper, Ohio State University.Karpoff, J. M., & Lee, D. (1991). Insider trading before new issue announcements. Financial Management, 20,

18–26.Lee, I. (1997). Do firms knowingly sell overvalued equity? Journal of Finance, 52, 1439–1466.Lin, J., & Howe, J. (1990). Insider trading in the OTC market. Journal of Finance, 45, 1273–1284.Loderer, C. F., Sheehan, D., & Kadlec, G. (1991). The pricing of equity offerings. Journal of Financial

Economics, 29, 35–57.Loughran, T., & Ritter, J. R. (1995). The new issues puzzle. Journal of Finance, 50, 23–51.Rozeff M. S., & Zaman, M. A. (1988). Market efficiency and insider trading: new evidence. Journal of Business,

61, 25–44.Seyhun, H. N. (1986). Insiders’ profits, costs of trading, and market efficiency. Journal of Financial Economics,

16, 189–212.Spiess, D. K., & Affleck-Graves, J. (1995). The long-run performance following seasoned equity offerings.

Journal of Financial Economics, 38, 243–267.White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroske-

dasticity. Econometrica, 48, 817–838.Wolak, F. A. (1989). Testing inequality constraints in linear econometric models. Journal of Econometrics, 41,

205–235.


insider trading and performance of seasoned equity offering firms after controlling for exogenous...

Documents