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Keywords:

  • open market repurchases (OMR);
  • insider trading;
  • long-run performance

Abstract

  1. Top of page
  2. Abstract
  3. 1. INTRODUCTION
  4. 2. THE SAMPLE
  5. 3. EMPIRICAL TESTS AND FINDINGS
  6. 4. CONCLUSION
  7. REFERENCES

The long-run performance of equity securities subsequent to announcements of open market repurchases (OMR) remains a contentious topic. In this paper we propose the “dichotomous expectations hypothesis” which posits that insider trading following share repurchase announcements reveals private information concerning the future operating performance of announcing firms. In particular, insider abnormal purchases (abnormal sales) should predict an improvement (decline) in operating performance that leads to higher (lower) long-run stock returns. Our hypothesis offers a credible economic link between insider trading and subsequent long-run stock performance through the intervening variable of operating performance. The empirical results show consistency with this linkage.

1. INTRODUCTION

  1. Top of page
  2. Abstract
  3. 1. INTRODUCTION
  4. 2. THE SAMPLE
  5. 3. EMPIRICAL TESTS AND FINDINGS
  6. 4. CONCLUSION
  7. REFERENCES

The finance literature has largely focused on the value-enhancing nature of share repurchase programmes. Early studies document positive announcement-period returns and generally attribute the finding to a signal of undervaluation for open market repurchase (OMR) firms (e.g., Vermaelen, 1981, Asquith and Mullins, 1986 and Comment and Jarrell, 1991). A second phase of this research, motivated by Ikenberry et al. (1995, 2000), documents the presence of long-run abnormal returns available to investors who purchase after the share buyback announcement and hold for a period of up to 4 years.1

Borrowing from the law literature, Fried (2001) questions whether OMRs should uniformly be viewed from the perspective of undervaluation when private information related to mispricing motivates the programme. His analysis builds upon two well-known and significant absences in the conventional terms of OMR programmes to motivate his “managerial opportunism” hypothesis. Since firms are not bound by the programmes to subsequently purchase shares, nor are insiders precluded from selling shares after the announcement, an incentive may exist to announce an OMR programme due solely to an anticipated announcement effect. Firms could then refuse to subsequently repurchase shares while at the same time affording insiders an opportunity to sell at post-announcement prices. In a subsequent study focusing on public policy recommendations, Fried (2005) reiterates that an OMR announcement is not a credible signal of undervaluation due to private information concerns. In its place, he suggests that if the firm commits to repurchase its stock, and if insiders commit not to sell their shares, an OMR can then send a credible signal that share value exceeds the repurchase price. According to Bhattacharya and Dittmar (2008), about 27% of firms who announce OMR fail to purchase a single share within 4 fiscal years of the announcement.

The potential of such opportunistic selling has not been ignored by the popular press where it has been referred to as a buyback bonanza.2 However, such discussion in the academic finance literature has been limited. To the best of our knowledge, no empirical study exists testing whether OMR announcements may serve competing purposes as a function of private information. The purpose of the current study is to provide such an analysis using insider trading data as a proxy for private information. Further, given the recent emphasis in the literature exploring OMR announcements and long-run stock returns, we focus on the association of such trading with extended holding period returns.

We suggest that the direction of insider trading will depend upon the motivation for the repurchase. Consider first the traditional case where the OMR announcement is due to a perceived undervaluation by insiders. The generally positive return drifts observed by prior researchers up to 4 years after the event suggests that the initial market reaction to the announcement was incomplete. Thus, an incentive will exist for insiders to purchase shares of these firms as long as they believe investors have underreacted to the OMR announcement. Alternatively, the managerial opportunism hypothesis of Fried (2001), along with its concomitant buyback bonanzas, suggests that some OMR announcements may be motivated by an attempt to create overvalued equity. Managers could then take advantage of these bonanzas by selling shares prior to disappointing long-run operating performance. The dual nature of OMR announcements presented here motivates us to propose a unified hypothesis which relates post-OMR-announcement insider trading to subsequent long-run stock performance.3 Our “dichotomous expectations hypothesis” posits that insider selling activity subsequent to OMR announcements is associated with weak long-run stock performance. In a similar manner, as motivated by an incomplete market response to undervaluation, insider buying is assumed to be associated with strong long-term stock performance. Together, the hypothesis predicts a positive relationship between the net purchases of insiders and long-run buy-and-hold abnormal returns of OMR firms.

Differences in perceived valuation between informed insiders and uninformed outside investors can largely be expected to derive from differing expectations of future operating performance. Relying upon actual share repurchases, Lie (2005) argues that the undervaluation of OMR firms probably stems from managers expecting future operating performance to exceed uninformed expectations. Extending this argument to the potential dual nature of OMR announcements, we posit that if insider trading following OMR announcements is an effective proxy for revealing private information for the future operating performance of OMR firms, then insider abnormal purchases (abnormal sales) should predict an improvement (decline) in operating performance that leads to higher (lower) long-term stock returns. Therefore, our dichotomous expectations hypothesis offers a credible economic link between insider trades and subsequent long-run stock returns through the intervening variable of operating performance. Our empirical findings show consistency with this linkage.

Using a sample of 5,204 OMR announcements over the period of 1987 through 2006, we test the dichotomous expectations hypothesis. Since the amount and quality of private information may differ across insider type, we classify each insider trader in our sample as either “senior” or “other” in the manner of Seyhun (1998) and Allen (2001). Our tests show that the direction of insider trades is significantly correlated with the future operating performance of our sample firms regardless of insider seniority. However, only the trades of senior insiders appear to be significantly related to long-run holding period returns. These findings suggest that senior insiders in our sample may have access to a more refined information set than other insiders.

Our study complements the existing literature which links share repurchases to insider trading. Lee et al. (1992) suggest that managers increase their purchasing and decrease their selling prior to fixed price tender offers that do not follow takeover attempts. In contrast, they report that no abnormal trading occurs prior to Dutch auction repurchases. They also posit that the accumulation of shares for fixed price offers conveys favorable information to outsiders. Core et al. (2006) examine whether managers’ trading decisions are correlated with either the operating accruals or the post-earnings announcement drift anomalies. The authors present corroborative evidence for the operating accruals anomaly only whereby low (high) accruals firms repurchase more (fewer) shares, and managers of low (high) accruals firms buy more (fewer) shares for their personal accounts. Bonaimé and Ryngaert (2013) report that simultaneous stock purchases by insiders and actual repurchases by firms predict higher long-term returns than simultaneous insider sales and actual repurchases in the same quarter. Babenko et al. (2012) find that announcement returns are positively related to insider purchases prior to repurchasing announcements. The announcement effects are magnified for firms that are priced less efficiently and for those engaged in repurchases for reasons other than deploying cash or increasing leverage.

Louis et al. (2010) focus on liquidity trades and report that such activity is associated with insider selling after fixed-price repurchase tender offer (RTO) announcements since there is no close relationship between insider selling and future performance. They posit that mispricing exploitation by informed traders drives insider selling, particularly in the special case of Dutch-auction RTOs, due to subsequent poor performance. In the case of open market repurchases, however, we argue that the associated buyback announcements may give rise to either insider buying or selling behavior based upon private information regarding future operating performance.

Overall, what distinguishes our study from the existing literature is the informational setting linked to repurchase announcement events. Our dichotomous expectations hypothesis offers an economic interpretation of information flows around the repurchase announcement. The hypothesis reflects two types of insider expectations concerning corporate prospects following repurchase announcements. One is related to the creation of buyback bonanzas, suggesting that some insiders may use private information to sell their shares at attractive prices following the announcements of share repurchases. The other is related to informed buying, suggesting that some insiders of repurchasing firms may expect an improvement in future operating performance and use this information to initiate purchases for their own accounts. Our empirical results support the dichotomous expectations hypothesis and suggest the non-homogeneity of open market repurchase announcements. That is, post-announcement insider purchases (sales) predict an improvement (decline) in abnormal operating performance that leads to higher (lower) long-term abnormal stock returns.

The rest of the paper proceeds as follows. Section 'THE SAMPLE' describes our sample characteristics and insider trading activity. Section 'EMPIRICAL TESTS AND FINDINGS' presents the empirical tests and findings involving operating and financial market performance. Finally, Section 'CONCLUSION' summarizes our work and concludes the study.

2. THE SAMPLE

  1. Top of page
  2. Abstract
  3. 1. INTRODUCTION
  4. 2. THE SAMPLE
  5. 3. EMPIRICAL TESTS AND FINDINGS
  6. 4. CONCLUSION
  7. REFERENCES

(i) Data Sources and Characteristics of the Sample

We obtain our sample of open market repurchases from the Securities Data Company's (SDC) US Mergers and Acquisitions database. The sample is constructed based on original announcement dates between January 1, 1987 and December 31, 2006. Our procedures require listing on the Center for Research in Security Prices (CRSP), COMPUSTAT, and the Thomson Reuters Insider Filing database. We exclude announcements with stock prices less than US$ 3, insider transactions for fewer than 100 shares, and insider transactions with transaction prices more than 200% of the prior day's closing price. Industry exclusions contain utility companies (COMPUSTAT SIC codes 4910–4949), closed-end funds (SIC codes 6720–6739), and real estate investment trusts (SIC code 6798). Finally, we exclude share repurchases from the fourth quarter of 1987 in order to reduce clustering due to the large amount of activity observed during this period. These restrictions result in a final sample of 5,204 OMR announcements.

Panel A of Table 1 provides the sample distribution by calendar year. During the period 1994–99, the OMR volume increased substantially with a peak of 789 announcements in 1998. Panel B reports industry distribution based on two-digit SIC codes. We find that 55% of our announcements derive from the following industrial segments presented in descending order of frequency: depository institutions (SIC code 60, 1,136 firms), business services (SIC code 73, 456 firms), electronic and other electrical equipment (SIC code 36, 339 firms), machinery and computer equipment (SIC code 35, 318 firms), chemicals and allied products (SIC code 28, 309 firms), and measuring instruments (SIC code 38, 307 firms). Depository institutions alone account for almost 22% of the entire sample.4

Table 1. OMR Sample Distribution and Firm Characteristics
Panel A: Number of OMRs by Calendar Year
OMR YearFreq.%Cum. Freq.%
1987470.91470.91
19881001.931472.83
19891593.063065.90
19902464.7455210.64
1991731.4162512.04
19921502.8977514.93
19931673.2294218.15
19943326.401,27424.55
19954137.961,68732.50
199655210.642,23943.14
19974829.292,72152.43
199878915.203,51067.63
199958511.274,09578.90
20001923.704,28782.60
20011242.394,41184.99
20021132.184,52487.17
20031402.704,66489.87
20041603.084,82492.95
20051883.625,01296.57
20061783.435,190100.00
Total5,190100.00  
     
Panel B: Industry Distribution
IndustryTwo-digit SIC CodesFreq.%
Depository Institutions601,13621.83
Business Services734568.76
Electronic, other Electrical Equipment and Components, except Computer Equipment363396.51
Industrial and Commercial Machinery and Computer Equipment353186.11
Chemicals & Allied Products283095.94
Measuring, Analyzing, and Controlling Instruments; Photographic, Medical and Optical Goods; Watches and Clocks383075.90
Insurance Carriers631382.65
Food and Kindred Products201332.56
Transportation Equipment371292.48
Durable Goods-Wholesale501102.11
Security & Commodity Brokers621062.04
Oil and Gas Extraction131011.94
Printing, Publishing & Allied27961.84
Eating and Drinking Places58961.84
Miscellaneous Retail59851.63
Communication48831.59
Primary Metal Industries33701.35
Paper and Allied Products26691.33
Fabricated Metal Products, except Machinery and Transportation Equipment34631.21
Engineering, Accounting, Research, Management, and Related Services87631.21
Apparel and Accessory Stores56631.21
Rubber & Miscellaneous Plastics Products30521.00
Health Services80510.98
Miscellaneous Manufacturing Industries39460.88
Apparel & Other Finished Products23450.86
Non-durable Goods-Wholesale51430.83
Furniture and Fixtures25410.79
Petroleum Refining & Related Industries29390.75
General Merchandise Stores53370.71
Motor Freight Transportation & Warehousing42370.71
Lumber and Wood Products, except Furniture24350.67
Amusement & Recreation Services79350.67
Insurance Agents, Brokers & Service64330.63
Food Stores54320.61
Textile Mill Products22310.60
Building Construction General Contractors and Operative Builders15310.60
Others 3326.40
Total 5,190100.00
Panel C: Firm Characteristics
VariablesMeanMedian
Note
  1. The sample consists of 5,204 open market repurchases (OMRs) during 1987–2006 announced by firms listed on NYSE, AMEX and NASDAQ. Each of the industries listed in Panel B has more than 30 OMRs. Regulated utilities (SIC codes 4910–4949), closed-end funds (SIC codes 6720–6739), real estate investment trusts (SIC code 6798), firms absent book value information from COMPUSTAT, and firms not contained within the Thomson Reuters Insider Filing database are excluded. Shares sought are the number of shares to be repurchased. Amount sought is the dollar amount of a repurchase plan. PSought is the percentage of outstanding shares announced to be repurchased. Size is the firm's market value of total common equity at the end of the prior month and converted into 2006 prices. B/M ratio is the ratio of book equity value at the prior fiscal year-end to total market value at the month-end prior to the announcement. Free Cash Flow is defined as in Lehn and Poulsen (1989) at the end of the prior fiscal year. Leverage is long-term debt to total assets and minus the median leverage ratio of all firms with the same two-digit SIC code at the end of the prior fiscal year. Abnormal Accruals is the average of the industry performance-adjusted abnormal total accruals in the quarter of the announcement and the preceding quarter. Actual Buy is the actual share buyback in the year after the repurchase announcement divided by the number of shares sought, and we use the monthly decrease in adjusted shares outstanding reported by CRSP as the proxy of actual share buyback.

Shares Sought (million)3.700.98
Amount Sought (million)148.7714.00
PSought (%)6.435.00
Size (million)2,580.71239.44
Size Decile4.223.00
B/M Ratio0.620.54
B/M Decile5.055.00
Free Cash Flow (FCF) (%)6.466.95
Industry-Adjusted Leverage (Leverage) (%)4.631.96
Abnormal Accruals (ABACC) (%)−0.15−0.06
Actual Buy (%)55.8859.32

Summary characteristics of the repurchasing firms are presented in Panel C of Table 1. Our sample firms have a median market capitalization of US$ 239 million and a mean of US$ 2.58 billion. The sample firms possess leverage ratios similar to their respective industry medians and appear in the 5th decile of book-to-market ratios.5 The median percentage of shares sought relative to the number of outstanding shares is 5.1%, and of these shares, the median actual buyback percentage for 1 year following the repurchase announcement is 73.19%.6

(ii) Insider Trading Activity

Insider trading data are obtained from the Thomson Reuters Insider Filing database. Following Allen (2001), we define insiders as officers, directors, general partners, controlling persons, and general counsels. Further, insiders are grouped into “senior” and “others” categories. Top executives (chief executive officer, president, chairman of the board, chief financial officer, officer and a member of the board of directors, officer or director and beneficial owner, general partner, controlling person, and vice president) are classified as “senior” (Seyhun, 1998; Allen, 2001), and “others” are insiders who are not “senior.”

Our empirical design measures abnormal insider trading against a control firm for each share repurchase observation. We use procedures similar to Eberhart et al. (1999) and Chhaochharia and Grinstein (2007) to construct our control sample. The first step matches by four-digit (three- or two-digit if no more than one firm is available) SIC codes. These firms are then sorted by their respective market capitalization and book-to-market ratios. Market capitalization and book-to-market ratios are measured at the end of the month prior to the share repurchase announcement with the book value determined as of the prior fiscal year-end. We require that the market capitalization of the matched firm be within ±30% of the OMR firm, and of the firms within this range, we select the firm with the closest book-to-market ratio.

Table 2 reports the average number of insider trades per quarter before and after the share repurchase announcement for our OMR sample and their respective matching firms. The variable of interest, net purchases (NP), is calculated as the number of insider purchases minus the number of insider sales and then divided by the number of total insider trades in each quarter.7 Abnormal trading measures the difference in this measure between the OMR firms and the matching firms. As is typically the case due to option exercise, portfolio rebalancing and consumption needs, the data show insider sales transactions as outnumbering purchases for each time period and within each respective table category.8 While the data show a slight peak in insider buying during the quarter before and after each announcement, the primary insight from Table 2 accrues from the high frequency of sales transactions. Such abnormal activity is evident during every quarter and over every multiple-quarter interval presented. The magnitude of this abnormal trading is roughly similar across the prior and post periods with normalized net purchase averages of −0.11 and −0.09, respectively, across the two 4-quarter intervals.

Table 2. Insider Trading Around Open Market Repurchases
 OMR FirmsMatching FirmsAbnormal Trading
Event QuarterPurchasesSalesNPPurchasesSalesNPPurchasesSalesNP
Panel A: All Insiders
−40.7442.331−0.143***0.9171.793−0.060***−0.173***0.538***−0.084***
−30.7842.507−0.149***0.8761.854−0.069***−0.093*0.653***−0.080***
−20.7242.428−0.168***0.8921.764−0.062***−0.168***0.664***−0.106***
−10.8752.081−0.088***0.9581.747−0.038***−0.0820.334***−0.050***
10.8772.347−0.090***0.8661.774−0.050***0.0110.573***−0.040***
20.7062.266−0.121***0.8101.756−0.065***−0.104**0.510***−0.057***
30.7782.720−0.129***0.9501.769−0.055***−0.172**0.950***−0.074***
40.6872.592−0.147***0.8641.782−0.064***−0.177***0.810***−0.083***
−4 to –11.0643.179−0.186***1.2392.435−0.078***−0.176***0.744***−0.109***
1 to 41.0443.399−0.167***1.1952.425−0.080***−0.152***0.974***−0.087***
−4 to 41.0773.361−0.180***1.2442.483−0.080***−0.167***0.877***−0.100***
Panel B: Senior Insiders
Note
  1. The table reports the average number of insider trades per firm per quarter in the four quarters before and after the share repurchase announcements. NP (net purchases) is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades. Abnormal Trading is defined as the difference between the OMR firms and the matching firm averages in the given quarter. ***, **and *denote significance at the levels of 1%, 5%, and 10%, respectively.

−40.2361.133−0.133***0.3340.899−0.072***−0.098***0.234***−0.061***
−30.2471.184−0.139***0.3070.873−0.084***−0.060**0.311***−0.055***
−20.2411.168−0.149***0.3120.861−0.075***−0.071***0.307***−0.074***
−10.3090.896−0.090***0.3540.826−0.051***−0.0450.070−0.040***
10.3031.040−0.085***0.3270.793−0.058***−0.0240.247**−0.027***
20.2461.028−0.111***0.3020.810−0.067***−0.055*0.217**−0.044***
30.2331.337−0.113***0.3490.775−0.060***−0.117***0.562**−0.053***
40.2381.100−0.110***0.3220.740−0.056***−0.084***0.360***−0.054***
−4 to –10.4822.046−0.239***0.6101.615−0.132***−0.128***0.430***−0.107***
1 to 40.4962.192−0.204***0.6321.517−0.117***−0.136***0.675***−0.087***
−4 to 40.5272.282−0.239***0.6691.689−0.134***−0.142***0.593***−0.105***

Given the post-announcement upward drift in prices previously documented in the literature, the preponderance of selling reported in Table 2 is unexpected. This preliminary univariate analysis, however, is limited in its scope. The next section links the observed trading activity to operating and financial market performance. Our analysis partitions the data by transaction type (i.e., whether abnormal buying or selling is observed) and examines the long-term operating and stock performance using various benchmarks. Additionally, we examine whether or not there exists differential timing ability between a sub-sample of “senior” insider traders and “others”. Finally, we control for other potential confounding elements suggested by the literature within our concluding tests.

3. EMPIRICAL TESTS AND FINDINGS

  1. Top of page
  2. Abstract
  3. 1. INTRODUCTION
  4. 2. THE SAMPLE
  5. 3. EMPIRICAL TESTS AND FINDINGS
  6. 4. CONCLUSION
  7. REFERENCES

(i) Changes in Long-run Operating Performance

Any discussion of private information would be incomplete without addressing the potential content of such information. Since the available data preclude the precise identification of such content, we employ a second-best method and address changes in long-run operating performance.

The abnormal operating performance is measured as the change in operating return on assets from event quarter +5 to quarter +16 after each announcement relative to a performance-matched firm. Operating return on assets is measured as operating income before depreciation and amortization divided by book assets. We use operating income so that differences related to capital structure, managerial discretion among depreciation methods for reporting purposes, and accounting for goodwill will not confound our analysis.

We identify a matching firm for each repurchasing sample firm using the procedure proposed by Lie (2005). First, for each repurchasing firm, we select all firms in the same industry (a two-digit SIC code) that meet the following conditions: (1) a pre-repurchase market-to-book ratio of assets within ±20% or within ±0.1 of that of the sample firm; (2) operating performance for the announcement quarter (quarter 0) within ±20% or within ±0.01 of that of the sample firm; and (3) operating performance for the four quarters ending with quarter 0 within ±20% or within ±0.01 of the corresponding performance for the sample firm. Our matching firm is then chosen on the basis of minimization of the sum of absolute differences across conditions (2) and (3). If no firm meets any of these criteria, we repeat our procedures using a one-digit SIC code. If still no firm meets any of the above criteria, we repeat our procedures absent the industry matching constraint.9

Table 3 reports mean and median adjusted changes in abnormal return on assets using performance matching firms and segmented by insider classification.10 Trading patterns are categorized into groupings based on the sign of net purchases in the 1-year post-announcement period, where net purchases, NP, are defined as the average difference between the insider purchase and sales frequency normalized by the number of total insider trades in the four quarters immediately following the repurchase announcement. The data here show timing ability in operating performance across both senior insiders and others. In both cases we observe positive adjusted mean and median ROAs when NP > 0 and negative measures when NP < 0. The right-hand column tests differences between these two statistics and is significant at the 5% level in all cases.11

Table 3. Changes in Operating Performance and Post-OMR-announcement Insider Trading
 NP > 0NP = 0NP < 0NP > 0 vs. NP < 0
Note
  1. This table reports mean and median percentage changes in abnormal operating performance. Abnormal operating performance is measured as the change in return on assets from event quarter +5 to quarter +16 after each announcement relative to a performance-matched firm. We define insiders as officers, directors, general partners, controlling persons and general counsels. Top executives (chief executive officer, president, chairman of the board, chief financial officer, officer and a member of the board of directors, officer or director and beneficial owner, general partner, controlling person, and vice president) are classified as “senior” (Seyhun, 1998; Allen, 2001). NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the one-year period after the OMR announcement. The p-values for the t-statistics are reported in parentheses while those for the Signed-Rank tests are reported in square brackets. For a test of differences in means and medians between the “NP > 0” and “NP < 0” groups, we report significance levels for the t-test and Kruskal-Wallis test in parentheses and square brackets, respectively.

Panel A: All Insiders
N8614661,543 
Mean0.521−0.109−0.7131.234
 (0.005)(0.734)(<.001)(<.001)
Median0.013−0.023−0.0150.028
 [0.312][0.275][0.087][0.073]
Panel B: Senior Insiders
N5701,1181,182 
Mean1.091−0.375−0.8941.985
 (<.001)(<.056)(<.001)(<.001)
Median0.071−0.02−0.0350.106
 [0.004][0.170][0.011][<.001]
Panel C: Other Insiders
N8626691,339 
Mean0.2060.282−0.8391.045
 (0.208)(0.248)(<.001)(<.001)
Median0.0130.030−0.0310.044
 [0.462][0.629][0.016][0.032]

Figure 1 presents the average abnormal operating performance each year following OMR announcements. We observe a decline in abnormal operating performance for the post-NP < 0 group but improvement in abnormal operating performance for the post-NP > 0 group for the subsequent 4 years. Furthermore, for the first year, the abnormal operating performance for the post-NP < 0 group is positive and large relative to the comparison samples. This operating performance provides an attractive environment for insider sales. Overall, Figure 1 suggests that senior insider trades during the first year following OMR announcements reveal valuable information relevant to subsequent abnormal operating performance.

image

Figure 1. Abnormal Operating Performance Following OMR Announcements

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(ii) Multivariate Analysis of Changes in Long-run Operating Performance

Previously, Table 3 presented the relationship between insider trading and subsequent accounting performance. The adjusted mean and median ROAs were positive when NP > 0 but both measures were negative when NP < 0. These results suggest that insiders may have been privy to information regarding the future operating performance of their respective firms. We now extend these tests by examining the abnormal changes in the long-run operating performance of our OMR sample in a multivariate framework.

Table 4 presents a regression analysis where the dependent variable is the change in return on assets from event quarter +5 to quarter +16 relative to a performance-matched firm as explained in sub-section (i). Our main explanatory variable, the net purchases of insiders, NP, is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement in each respective category (i.e., all insiders, senior insiders and others).

Table 4. Post-announcement Change in Operating Performance and Insider Trading
Model(1)(2)
Note
  1. This table reports the regression analysis of the relationship between post-announcement operating performance and insider trading. The dependent variable is the change in return on assets from event quarter +5 to quarter +16 after each announcement relative to a performance-matched firm. NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the one-year period after the OMR announcement; ARPR is the prior 1-year buy-and-hold abnormal return adjusted by matching firms; 1st-year Abnormal Return is the post 1-year buy-and-hold abnormal return adjusted by matching firms; B/M decile (1 being the lowest) is based on the ratio of book equity value at the prior fiscal year-end to total market value at the month-end prior to the announcement; Size decile (1 being the lowest) is based on the firm's market value of total common equity at the end of the prior month and converted into 2006 prices; FCF is free cash flow which is defined as in Lehn and Poulsen (1989) at the end of the prior fiscal year; Leverage is long-term debt to total assets normalized by minus the firm's target leverage ratio as the median leverage ratio of all firms with the same two-digit SIC code at the end of the prior fiscal year; ABACC is the average of the industry-performance-adjusted abnormal total accruals in the quarter of the announcement and the preceding quarter; Psought is the percent sought; Actual Buy is actual shares buyback in the year after the repurchase announcement divided by the number of shares sought, and we use the monthly decrease in adjusted shares outstanding reported by CRSP as the proxy of actual share buyback. OMR Order is the order of OMR programmes announced for a given firm within our sample period. Numbers in parentheses are heteroskedasticity-adjusted t-statistics (White, 1980). ***, **, and *denote significance at the levels of 1%, 5%, and 10%, respectively.

Intercept−1.846−1.847
 (−2.76)***(−2.77)***
Insider NP0.880 
 (5.40)*** 
Senior NP 0.858
  (5.02)***
Other NP 0.349
  (2.12)**
ARPR−0.068−0.060
 (−0.22)(−0.20)
1st-year Abnormal Return−0.741−0.720
 (−2.82)***(−2.75)***
B/M decile0.0200.014
 (0.35)(0.24)
SIZE decile0.0630.076
 (1.44)(1.72)*
FCF6.8047.112
 (2.32)**(2.42)**
Leverage2.3442.240
 (2.58)***(2.47)**
ABACC7.6417.589
 (1.53)(1.52)
Psought0.0150.014
 (0.62)(0.56)
Actual Buy0.6650.679
 (2.24)**(2.29)**
OMR Order0.1100.112
 (1.63)(1.66)*
N2,7152,715
Adjusted-R20.0290.032
F-value8.368.50

Our regression models also control for other variables previously documented to be related to buy-and-hold returns subsequent to announcements of open market repurchases. ARPR is the prior 1-year buy-and-hold abnormal return adjusted by matching firms; 1st-year Abnormal Return is the post 1-year buy-and-hold abnormal return adjusted by matching firms; Book-to-market is given by B/M decile (1 being the lowest) and is defined as the ratio of book equity value at the prior fiscal year-end to the total market value at the month-end prior to the announcement; Size decile (1 being the lowest) is the OMR firm's market value of total common equity at the end of the prior month, using 2006 prices as a base; FCF is free cash flow which is defined as in Lehn and Poulsen (1989) at the end of the prior fiscal year; Leverage is the difference between the long-term debt to total assets ratio of our sample firm and the similar industry measure defined by the two-digit SIC code at the end of the prior fiscal year; ABACC is the average of the industry performance-adjusted abnormal total accruals in the quarter of the announcement and the preceding quarter. Following Kothari et al. (2005); Gong et al. (2008); and Cheng et al. (2012), we define the industry-performance-adjusted abnormal accrual as a firm's abnormal accruals minus the median abnormal accruals of its corresponding industry performance-matched portfolio. Psought is the percent of outstanding shares sought; Actual Buy represents the realized buyback in the year after the repurchase announcement divided by the number of shares sought. We also control for the possibility that multiple OMR programmes by a given firm may confound our analysis. OMR Order is the order of OMR programmes announced for a given firm within our sample period.

Models (1) and (2) of Table 4 show that the abnormal changes in the return on assets of repurchasing firms is positively related to insider trading and that this association holds regardless of insider seniority classification. These findings are consistent with those reported earlier in both Table 3 and Figure 1 and reinforce the idea that insider trades may be motivated by asymmetric information regarding future operating performance.

Regarding our control variables, the coefficients on 1st-year Abnormal Return are significantly negative. The result indicates that investors, based upon incomplete information, may be either overly optimistic or pessimistic. The coefficients on the variable indicating free cash flow as defined in Lehn and Poulsen (1989) are significantly positive in both regressions. This finding suggests that more free cash flows help reduce financial constraints and thus improve future operating performance. Similarly, the variable indicating leverage is also significantly positive as the literature has indicated that the constraints imposed by debt may be a partial solution to management inefficiently deploying free cash flows. Furthermore, both models show that repurchasing firms with more actual buyback activity exhibit better abnormal operating performance than those with lower realized buyback levels when controlling for post-OMR-announcement insider net purchases. The results also provide evidence of timing ability at the firm level.

(iii) Long-run Stock Performance

We next categorize our sample by post-OMR-announcement NP in the 1-year post-announcement period. In order to avoid an overlap with the measurement period of post-OMR-announcement NP, we first calculate the 3-year buy-and-hold return (BHR) from month 13 to month 48 following the share repurchase announcement. If shares are delisted during this interval, the returns are calculated up to the delisting month. The respective measures for the matching firms are calculated over the same holding periods as the corresponding sample firms. If any of the matching firms are delisted prematurely, we substitute the returns of the CRSP value-weighted index over the interval of missing data.

Table 5 reports mean and median BHRs using the above-mentioned procedures. Raw returns are presented in Panel A, market-adjusted returns in Panel B, and matching firm adjusted returns in Panel C. The returns show a striking pattern which suggest that insiders make effective use of their private information. This pattern of successful trading can be discerned from the marginal column statistics which reflect the difference in long-run mean and median returns between the NP > 0 and NP < 0 groups. This difference is both positive and significant across all three panels. Of the two measures of abnormal performance provided, the matching firm adjustments in Panel C are likely to provide the more widely-accepted measure of abnormal performance. Within this panel, the marginal column difference for the mean returns of 20% is especially notable. The lower level of 9% shown for the median measure reflects the underlying skewness of the data when using matching firms.

Table 5. Long-run Stock Market Performance and Post-OMR-Announcement Insider Trading
 NP > 0NP = 0NP < 0NP > 0 vs. NP < 0
Note
  1. The buy-and-hold return (BHR) is calculated by the compounded 3-year return from event day 253 to day 1,008 following the share repurchase announcement. Factor models present the average monthly abnormal return based on the Fama and French (1993) three-factor and the Carhart (1997) four-factor models using value-weighted portfolios. We define insiders as officers, directors, general partners, controlling persons and general counsels. NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement. The p-value for the t-statistic is reported in parentheses. The p-value for the Signed-Rank test is reported in square brackets. For a test of differences in means and medians between the “NP > 0” and “NP < 0” groups, we report significance levels for the t-test and Kruskal-Wallis test in parentheses and square brackets, respectively.

Panel A: Long-run BHR (%)
N1,5119072,772 
Mean45.34739.1635.1910.157
 (<.001)(<.001)(<.001)(<.001)
Median32.18125.30120.58411.597
 [<.001][<.001][<.001][<.001]
Panel B: Adjusted by CRSP Value-weighted Returns (%)
N1,5119072,772 
Mean24.28915.0237.13717.152
 (<.001)(<.001)(<.001)(<.001)
Median12.2311.724-0.9613.191
 [<.001][0.015][0.192][<.001]
Panel C: Adjusted by SIC-B/M-size Matching Firm Returns (%)
N1,5119072,772 
Mean9.8776.202-9.87419.751
 (<.001)(0.085)(<.001)(<.001)
Median7.0576.245-2.2489.305
 [<.001][0.017][0.049][<.001]
Panel D: Factor Models (%)
N1,5119072,772 
3-factor0.3800.205−0.1520.532
 (0.002)(0.164)(0.115)(<.001)
4-factor0.4900.335−0.0230.513
 (<.001)(0.020)(0.795)(<.001)

We also employ two variants of a factor methodology to measure long-run performance. Following Brav et al. (2000), we use the calendar-time portfolio method to estimate abnormal returns.12 In Panel D of Table 5, we report the intercepts obtained from monthly calendar time regressions using both the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model.13 Tests of significance across the insider trading groups are performed by forming value weighted zero-investment portfolios between the NP > 0 and NP < 0 classifications and regressing these returns on the respective factors across the two models. As with our initial tests, the intercepts from these monthly regressions act as our proxy for abnormal performance. Both Fama and French's (1993) three factor model and Carhart's (1997) four factor model show a significant difference between the respective portfolios in a direction consistent with the results of Panels A through C. Taken together, however, the tests in Table 5 are limited in scope as they implicitly assume that all classifications of insiders have privy to the same information and trade in an identical manner.

(iv) Classification by Senior Officers and Other Insiders

We next examine the extent to which some insiders might have greater timing ability than others. Table 6 segments insiders between senior officers (Panel A) and others (Panel B). Top executives (chief executive officer, president, chairman of the board, chief financial officer, officer and a member of the board of directors, officer or director and beneficial owner, general partner, controlling person, and vice president) are classified as “senior,” while the remainder is classified as “others” (Seyhun, 1998; Allen, 2001). To the extent senior insiders have access to better information than other insiders, and trading is based upon these private information sets, we would expect differential performance between the two groups.

Table 6. Long-run Stock Market Performance and Post-OMR-announcement Insider Trading Classified by Senior versus Other Insiders
 NP > 0NP = 0NP < 0NP > 0 vs. NP < 0
Note
  1. We define insiders as officers, directors, general partners, controlling persons, and general counsels. Further, insiders are grouped into “senior” and “others” categories. Top executives (chief executive officer, president, chairman of the board, chief financial officer, officer and a member of the board of directors, officer or director and beneficial owner, general partner, controlling person and vice president) are classified as “senior” (Seyhun, 1998 and Allen, 2001), and “others” are insiders who are not “senior”. NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement;. The buy-and-hold return (BHR) is calculated by compounding 3-year returns from the second to the fourth year following the share repurchase announcement. Factor models present the average monthly abnormal return based on the Fama and French (1993) three-factor and the Carhart (1997) four-factor models using value-weighted portfolios. The p-value for the t-statistic is reported in parentheses. The p-value for the Signed-Rank test is reported in square brackets. For a test of differences in means and medians between the “NP > 0” and “NP < 0” groups, we report significance levels for the t-test and Kruskal-Wallis test in parentheses and square brackets, respectively.

Panel A: Senior Insiders
A1: Long-run BHR (%)
N1,0511,9962,143 
Mean51.57133.16837.75213.819
 (<.001)(<.001)(<.001)(<.001)
Median35.35121.00423.46511.886
 [<.001][<.001][<.001][<.001]
A2: Adjusted by CRSP value-weighted returns (%)
N1,0511,9962,143 
Mean28.77313.5995.79322.98
 (<.001)(<.001)(0.001)(<.001)
Median15.3012.033−1.53116.832
 [<.001][<.001][0.743][<.001]
A3: Adjusted by SIC-B/M-size matching firm returns (%)
N1,0511,9962,143 
Mean13.6811.045−10.50124.182
 (<.001)(0.624)(<.001)(<.001)
Median8.2912.787−3.58311.874
 [<.001][0.052][0.017][<.001]
A4: Factor models (%)
N1,0511,9962,143 
3-factor0.4270.066-0.1350.562
 (0.002)(0.540)(0.170)(<.001)
4-factor0.5600.1960.0010.559
 (<.001)(0.051)(0.994)(<.001)
Panel B: Other Insiders
B1: Long-run BHR (%)
N1,4861,2932,411 
Mean42.52540.8435.5636.962
 (<.001)(<.001)(<.001)0.0078
Median30.67825.94119.51411.164
 [<.001][<.001][<.001][<.001]
B2: Adjusted by CRSP value-weighted returns (%)
N1,4861,2932,411 
Mean19.53312.5589.9959.538
 (<.001)(<.001)(<.001)(<.001)
Median8.5871.6230.0018.586
 [<.001][0.022][0.999][<.001]
B3: Adjusted by SIC-B/M-size matching firm returns (%)
N1,4861,2932,411 
Mean4.673.968-7.50312.173
 (0.058)(0.223)(0.002)(<.001)
Median5.297.2370.5264.764
 [0.004][0.005][0.899][0.029]
B4: Factor model (%)
N1,4861,2932,411 
3-factor0.3520.182−0.1400.492
 (0.002)(0.162)(0.154)(<.001)
4-factor0.4580.301-0.0050.463
 (<.001)(0.018)(0.956)(<.001)

The marginal statistics based upon matching firm data within Table 6 reveal performance differences based upon insider classification. Using matching firms, the mean and median differences between the positive and negative net trading groupings are 24% and 12%, respectively, as shown in panel A3 for senior insiders versus 12% and 5%, respectively, in panel B3 for others. Next, we investigate the timing ability of senior insiders versus others in panels A4 and B4 which examine abnormal performance defined by the factor models. Our test results show that net senior insider purchases significantly outperform their corresponding sales for both the 3-factor and 4-factor models. While a similar pattern holds for other insiders, the magnitude of the difference is diminished compared to the trades of senior insiders.

(v) Long-run Stock Returns and Senior Insider Trading

The prior analysis documents differences in long-run stock performance which are significantly related to the post-announcement trading activity of senior insiders. We next segment our senior insider sub-sample into three categories based upon the sign of the post-announcement net purchases.

Figure 2 presents the cumulative abnormal returns (CARs) from 252 trading days (1 year) prior to the announcement to 1,008 trading days (4 years) afterwards. Consistent with the prior literature, we observe a price decline which is similar across categories and which occurs in the 6 months prior to the announcement. The CARs, however, begin to show divergence from one another within the 1-year post-announcement period. There is a decline in prices occurring for the post-NP > 0 group as evidenced by an average CAR of –12.29%. This contrasts with the post-NP < 0 group where a slight gain of 2.48% occurs and for the post-NP = 0 group which experiences a loss of 5.37% in the same measure. The most prominent feature of the figure, however, is the long-run returns from year +1 through year +4. Here we observe price movements for both the net purchases and net sellers which are directionally opposite to those observed in the 1-year period immediately following the announcements. This process of purchasing as prices fall (and subsequently reverse with an average CAR of 17.79%) and selling as prices rise (and subsequently reverse with an average CAR of –9.81%) provides evidence consistent with insider timing ability.

image

Figure 2. Cumulative Abnormal Returns by 1-year Post-OMR-announcement Senior Insider Trading

Download figure to PowerPoint

(vi) Multivariate Analysis of Long-term Financial Market Performance

We now extend our univariate tests by examining the long-run equity market performance of our OMR sample using a regression framework. The dependent variable is LBHAR which is defined as the log (1 + OMR firm's 3-year BHR) – log (1 + matching firm's 3-year BHR). As with our prior tests, the 3-year BHR is calculated from the end of the first year following the OMR announcement to the fourth anniversary or to the delisting date of the OMR firm if the full sample period is not available.14

Two explanatory variables, the net purchases of insiders and abnormal operating performance, which is a proxy for information content relevant to subsequent stock performance, are of particular interest. The net purchases of insiders, NP, is calculated as the difference between the number of insider purchases and sales divided by the number of total insider trades within the 1-year period after the OMR announcement. Abnormal Operating Performance, is measured as the change in the return on assets from event quarter +5 to quarter +16 after each announcement relative to a performance-matched firm. In a like manner to our previous tests, we use these measures to separately examine long-term financial market performance segmented by all insiders, senior insiders, and others.

These two explanatory variables are crucial elements in our tests of the dichotomous expectations hypothesis. When insider trading shows net abnormal selling activity subsequent to the OMR announcement, the hypothesis predicts weak subsequent stock performance. This relationship is consistent with the presence of a buyback bonanza. Symmetrically, when post-OMR-announcement insider trading shows net abnormal buying activity, our hypothesis predicts strong subsequent stock returns consistent with informed buying. Together, our hypothesis predicts a significantly positive relationship between the net purchases of (senior) insiders and long-run buy-and-hold abnormal returns of OMR firms. Other explanatory variables are defined as in the prior sub-section.

Models (1) and (2) of Table 7 show that the long-run abnormal stock performance of repurchasing firms is significantly and positively related to both post-OMR-announcement insider trades and senior insider trades. In model (3) we delete the insider trading variables and substitute abnormal operating performance. The result is that, as expected, firm performance and stock market performance are strongly related. Models (4) and (5) check robustness for Models (1) and (2), respectively, by adding abnormal operating performance as an additional control variable.15 Our results suggest that Models (1) and (2) are robust to this addition. In particular, Model (4) shows the net purchase of all insiders is still significantly related to the long-run abnormal stock performance of repurchasing firms. Similarly, Model (5) shows the net purchase of senior insiders remains a significant factor in explaining the variation of the long-run abnormal stock performance of OMR firms. We also perform an F-test for the null hypothesis that the coefficients on Senior NP and on Other NP are equal. In Model (2), the p-value is 0.037 (the value of F(1, 4948) = 4.353) for the F-test of equal coefficients. In Model (5), the p-value is 0.048 (the value of F(1, 2701) = 3.914) for the F-test of equal coefficients. Thus, based on both tests, we reject the null hypothesis of equal coefficients and conclude that the net purchases of senior insiders appear to have a much stronger association with the long-run buy-and-hold abnormal return than the net purchases of other insiders. Our results suggest that senior insiders exhibit a greater measure of market timing ability than other insiders.16

Table 7. Testing the Dichotomous Expectations Hypothesis
Model(1)(2)(3)(4)(5)
Note
  1. This table reports the regression analysis of the relationship between OMR long-run buy-and-hold abnormal return and insider trading. The dependent variable is BHAR (1+ OMR firm's 3-year buy-and-hold return (BHR) – (1+ matching firm's 3-year BHR). The 3-year BHR is calculated from the end of 1 year following OMR announcement to the end of the 4-year anniversary following the announcement or to the delisting date of the OMR firm. NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement; Abnormal Operating Performance is measured as the change in return on assets from event quarter +5 to quarter +16 after each announcement relative to a performance-matched firm; ARPR is the prior 1-year buy-and-hold abnormal return adjusted by matching firms; 1st-year Abnormal Return is the post 1-year buy-and-hold abnormal return adjusted by matching firms; B/M decile (1 being the lowest) is based on the ratio of book equity value at the prior fiscal year-end to total market value at the month-end prior to the announcement; Size decile (1 being the lowest) is based on the firm's market value of total common equity at the end of the prior month and converted into 2006 prices; FCF is free cash flow which is defined as in Lehn and Poulsen (1989) at the end of the prior fiscal year; Leverage is long-term debt to total assets normalized by minus the firm's target leverage ratio as the median leverage ratio of all firms with the same two-digit SIC code at the end of the prior fiscal year; ABACC is the average of the industry-performance-adjusted abnormal total accruals in the quarter of the announcement and the preceding quarter; Psought is the percent sought; Actual Buy is actual shares buyback in the year after the repurchase announcement divided by the number of shares sought, and we use the monthly decrease in adjusted shares outstanding reported by CRSP as the proxy of actual share buyback. OMR Order is the order of OMR programmes announced for a given firm within our sample period. Numbers in parentheses are heteroskedasticity-adjusted t-statistics (White, 1980). ***, **, and *denote significance at the levels of 1%, 5%, and 10%, respectively.

Intercept−0.182−0.185−0.150−0.124−0.129
 (−2.17)**(−2.21)**(−1.29)(−1.06)(−1.11)
Insider NP0.120  0.112 
 (4.56)***  (3.31)*** 
Senior NP 0.118  0.125
  (3.70)***  (2.98)***
Other NP 0.028  0.016
  (1.00)  (0.45)
Abnormal Operating Performance  0.0220.0200.020
   (3.40)***(3.23)***(3.18)***
ARPR−0.068−0.066−0.090−0.089−0.088
 (−1.26)(−1.21)(−1.33)(−1.32)(−1.30)
1st-year Abnormal Return−0.102−0.101−0.125−0.108−0.108
 (−2.78)***(−2.76)***(−2.46)**(−2.08)**(−2.08)**
B/M decile0.0090.0090.004−0.001−0.001
 (1.03)(1.02)(0.35)(−0.03)(−0.05)
SIZE decile0.0010.002−0.0020.0020.004
 (0.06)(0.24)(−0.16)(0.23)(0.41)
FCF−0.239−0.217−0.392−0.351−0.303
 (−1.06)(−0.96)(−1.12)(−1.01)(−0.87)
Leverage0.1120.097−0.085−0.083−0.099
 (0.86)(0.74)(−0.46)(−0.46)(−0.55)
ABACC−0.722−0.7290.5020.4020.418
 (−0.91)(−0.92)(0.57)(0.46)(0.48)
Psought0.0030.003−0.003−0.003−0.003
 (0.76)(0.75)(−0.60)(−0.68)(−0.70)
Actual Buy0.1580.1620.1620.1560.159
 (3.30)***(3.37)***(2.48)**(2.39)**(2.44)**
OMR Order0.0160.0160.0130.0150.015
 (1.66)*(1.62)(0.98)(1.14)(1.14)
N4,9614,9612,7152,7152,715
Adjusted-R20.0100.0100.0150.0180.018
F-value5.525.294.735.094.92

Furthermore, all models show that repurchasing firms with more actual buyback activity outperform those with lower levels when controlling for post-OMR-announcement insider net purchases and abnormal operating performance. The results provide evidence of timing ability at the firm level in that they show a positive relationship between shares actually repurchased and long-term financial market performance.

(vii) The Determinants of Net Purchases of Insiders Following OMRs

In this sub-section, we use cross-sectional regression analyses in order to determine what factors may have been responsible for the net purchases of insiders at OMR firms within 1 year following the repurchase announcement. The dependent variable is NP, the net purchases of insiders, calculated as the ratio of the difference between the number of insider purchases and insider sales to the number of total insider trades within 1 year following the OMR announcement in each respective category of insiders.

The explanatory variables are defined earlier with two exceptions. Announcement Abnormal Returns is the 5-day (–2, +2) cumulative return of an OMR firm adjusted by its matching firm. If the announcement abnormal return is able to fully account for undervaluation of an OMR firm, the net purchases of insiders tend to decrease. On the other hand, if the announcement abnormal return of an OMR firm cannot completely account for its undervaluation, the net purchases of insiders would be likely to increase. Thus, we expect a negative relationship between NP and Announcement Abnormal Returns.

The second new variable introduced, Prior NP, is calculated as the ratio of the difference between the number of insider purchases and insider sales to the number of total insider trades within one year prior to the OMR announcement in each respective category of insiders. This variable is used to control for the possibility that insiders began their informed trading prior to the OMR announcement. Assuming an underlying informational asymmetry, there is no reason that the announcement return would fully reflect the firm's true prospects and thus would provide a motivation for continued insider trading subsequent to the repurchase announcement.

Table 8 reports that Abnormal Operating Performance, which is a proxy for the private information held by insiders concerning the firms’ future prospects, is significantly and positively related to net purchases across all regression models. Interestingly, Announcement Abnormal Returns is not significantly related to the net purchases of insiders apart from a limited association at the 10% level for the group of senior insiders. The variable 1st-year Abnormal Return, however, is significantly and negatively related to the net purchases of insiders in all regressions. The result for senior insiders is consistent with Figure 2 which shows that there is a decline in prices for the post-NP > 0 group but there is a slight gain for the post-NP < 0 group within the 1-year post-announcement period. Also, the regression results support the notion that post-announcement stock mispricing, as perceived by insiders, determines the sign of insider net purchases. If the stock is relatively undervalued after the announcement, insiders tend to buy shares, and the subsequent long-term returns are relatively high; if the stock is relatively less (or not at all) undervalued, insiders tend to sell shares, and the subsequent long-term returns are relatively low.17

Table 8. The Determinants of Net Purchases of Insiders Following OMRs
 All InsidersSenior InsidersOther Insiders
  Standardized Standardized Standardized
 EstimateEstimateEstimateEstimateEstimateEstimate
Note
  1. The dependent variable is NP which is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement. Abnormal Operating Performance is measured as the change in return on assets from event quarter +5 to quarter +16 after each announcement relative to a performance-matched firm; Announcement Abnormal Return is the 5-day (-2, +2) cumulative return adjusted by matching firms; 1st-year Abnormal Return is the post 1-year buy-and-hold abnormal return adjusted by the matching-firm return; Prior NP is calculated as the number of insider purchases minus the number of insider sales and then divided by the number of total insider trades in the 1-year period before the OMR announcement; B/M decile (1 being the lowest) is based on the ratio of book equity value at the prior fiscal year-end to total market value at the month-end prior to the announcement; Size decile (1 being the lowest) is based on the firm's market value of total common equity at the end of the prior month and converted into 2006 prices; Actual Buy is actual shares buyback in the year after the repurchase announcement divided by the number of shares sought, and we use the monthly decrease in adjusted shares outstanding reported by CRSP as the proxy of actual share buyback. Numbers in parentheses are heteroskedasticity-adjusted t-statistics (White, 1980). ***, **, and * denote significance at the levels of 1%, 5%, and 10%, respectively.

Intercept−0.121 −0.099 −0.126 
 (−2.81)*** (−2.36)** (−2.83)*** 
Abnormal Operating Performance0.8720.1350.9970.1430.6930.121
 (4.55)*** (5.15)*** (3.50)*** 
Announcement Abnormal Return−0.063−0.008−0.213−0.0280.0390.004
 (−0.49) (−1.65)* (0.30) 
1st-year Abnormal Return−0.168−0.070−0.136−0.112−0.153−0.055
 (−8.20)*** (−6.53)*** (−7.39)*** 
Prior NP0.3820.3830.3150.3280.3660.363
 (20.74)*** (17.49)*** (19.93)*** 
B/M decile0.0190.0760.0220.0900.0180.072
 (3.79)*** (4.48)*** (3.51)*** 
SIZE decile−0.024−0.107−0.032−0.082−0.016−0.068
 (−5.66)*** (−7.42)*** (−3.43)*** 
Actual Buy0.0270.0150.0060.0030.0190.010
 (0.92) (0.23) (0.64) 
N2,854 2,854 2,854 
Adjusted-R20.243 0.219 0.193 
F-value131.89 115.41 98.4 

The prior results indicate that both post-announcement undervaluation and future operating performance are the drivers of insider trading. When the regression coefficients are standardized, the absolute coefficient on Abnormal Operating Performance is larger than the absolute coefficient on 1st-year Abnormal Return. This finding suggests that the future change in abnormal operating performance appears to be the dominating factor. On the other hand, when investigating the drivers of long-run stock abnormal returns in Table 7, we find that Abnormal Operating Performance is positive and significant at the 1% level in regression models (3)–(5) but that 1st-year Abnormal Return is insignificant across all models. The results suggest that the change in operating performance leads to long-run stock abnormal return, rather than that the market takes a long time to correct undervaluation existing at the time of the repurchase announcement. Overall, our evidence supports the notion that post-announcement insider purchases (sales) predict an improvement (decline) in abnormal operating performance that leads to higher (lower) long-term abnormal stock returns.

(viii) Consistent Trading Behavior

Corporate insiders who own private information about the firm may execute multiple trades in a given sample period as discussed in Betzer and Theissen (2010). As such, we categorize insider trading according to whether insider trading is mixed (i.e., cases involving both buy and sell transactions) or unidirectional (i.e., cases where all trades are in the same direction) in the 1-year post announcement period. We expect our reported associations to be stronger for the latter category where trading behavior is consistent. To examine the relationship between consistent trading behavior and operating/financial market performance of OMR firms, we define PP (pure purchases) as OMR firms with NP equal to one, Mixed (mixed trades) as those with NP between −1 and 1, and PS (pure sales) as those with NP equal to negative one. These definitions are consistent with those used in Lee (1997) and Chen et al. (2012).

Table 9 examines the long-run operating and stock market performance of OMR firms based on insider trading patterns and seniority of insiders. Panel A reports the changes in long-run operating performance measured by the change in operating return on assets from event quarter +5 to quarter +16 relative to a performance-matched firm. We find that pure insider purchasing OMR firms significantly outperform those with pure insider selling and that these results are consistent across seniority classification. Table 9 presents long-run abnormal stock market performance over the 3-year period from event day +253 to day +1,008 using two approaches. Our first approach uses traditional event-time portfolios and is shown in Panels B through D. Panel B reports buy-and-hold returns, Panel C presents abnormal buy-and-hold returns adjusted by the CRSP value-weighted index returns, while Panel D provides abnormal buy-and-hold returns adjusted by the SIC, book-to-market and size-matched firm returns. Similar to the abnormal operating performance presented in Panel A, pure insider purchasing OMR firms significantly outperform those with pure insider selling. These results are consistent across abnormal return measures and insider classification.

Table 9. Consistent Trading Behavior
 All InsidersSenior InsidersOther Insiders
 PPMixedPSPP-PSPPMixedPSPP-PSPPMixedPSPP-PS
Panel A: Changes in Long-run Operating Performance
Note
  1. The table reports the percentage change in abnormal operating performance and buy-and-hold return (BHR). In Panel A, abnormal operating performance is measured as the change in return on assets from event quarter +5 to quarter +16 after each OMR announcement relative to a performance-matched firm. In Panels B through D, BHR is the compounded 3-year return from event day 253 to day 1,008 following the share repurchase announcement. In Panel E, factor models present the average monthly abnormal return based on the Fama and French (1993) three-factor and the Carhart (1997) four-factor models using value-weighted portfolios. We define insiders as officers, directors, general partners, controlling persons and general counsels. Top executives (chief executive officer, president, chairman of the board, chief financial officer, officer and a member of the board of directors, officer or director and beneficial owner, general partner, controlling person, and vice president) are classified as “senior” (Seyhun, 1998; Allen, 2001), and “others” are insiders who are not “senior”. PP (pure purchases) is defined as OMR firms with NP equal to one. Mixed (mixed trades) is defined as OMR firms with NP within (–1, 1). PS (pure sales) is defined as OMR firms with NP equal to negative one. NP (net purchases) is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement. The p-values for the t-statistics are reported in parentheses while those for the Signed-Rank tests are reported in square brackets. For a test of differences in means and medians between the “PP” and “PS” groups, we report significance levels for the t-test and Kruskal-Wallis test in parentheses and square brackets, respectively.

N4271,687756 4741,412984 5171,565788 
Mean1.250−0.357−1.0162.2661.112−0.504−0.8982.0100.451−0.213−1.0201.471
 (<.001)(0.012)(<.001)(<.001)(<.001)(0.005)(<.001)(<.001)(0.039)(0.163)(<.001)(<.001)
Median0.067−0.005−0.0690.1360.074−0.007−0.0530.1270.037−0.001−0.0710.108
 [0.026][0.504][0.006][<.001][0.012][0.314][0.018][<.001][0.217][0.987][0.003][0.004]
Panel B: Long-run BHR
N7583,0241,408 8552,5561,779 9152,8121,463 
Mean45.56140.52231.41714.14450.30137.40635.34914.95244.35339.05234.7619.592
 (<.001)(<.001)(<.001)(<.001)(<.001)(<.001)(<.001)(<.001)(<.001)(<.001)(<.001)(0.007)
Median31.09826.36716.40414.69434.83724.17620.78514.05232.27825.47716.88315.395
 [<.001][<.001][<.001][<.001][<.001][<.001][<.001][<.001][<.001][<.001][<.001][<.001]
Panel C: Adjusted by CRSP Value-weighted Returns
N7583,0241,408 8552,5561,779 9152,8121,463 
Mean23.77014.7925.00318.76729.83714.6184.18225.65519.36113.6998.98110.380
 (<.001)(<.001)(0.015)(<.001)(<.001)(<.001)(0.024)(<.001)(<.001)(<.001)(<.001)(<.001)
Median9.4693.917−3.62013.08916.1102.465−3.81519.9259.0093.121−1.35010.359
 [<.001][<.001][0.753][<.001][<.001][<.001][0.547][<.001][<.001][<.001][0.22][<.001]
Panel D: Adjusted by SIC-B/M-size Matching Firm Returns
N7583,0241,408 8552,5561,779 9152,8121,463 
Mean11.5051.027−11.37122.87611.9562.130−12.06624.0228.105−0.244−7.86215.967
 (0.003)(0.608)(<.001)(<.001)(0.003)(0.289)(<.001)(<.001)(0.013)(0.908)(0.01)(<.001)
Median10.1983.810−0.73010.9288.2913.962−3.90912.2008.3753.953−0.6979.072
 [<.001][0.003][0.121][<.001][<.001][0.002][0.013][<.001][0.001][0.004][0.315][0.029]
Panel E: Factor Models
N7583,0241,408 8552,5561,779 9152,8121,463 
3-factor0.3940.133−0.1440.5380.4380.121−0.1410.5790.4150.134−0.1130.528
 (0.006)(0.141)(0.25)(<.001)(0.001)(0.221)(0.177)(<.001)(0.001)(0.177)(0.314)(<.001)
4-factor0.4940.255−0.0320.5260.5620.243−0.0010.5630.4900.2650.0240.466
 (0.001)(0.002)(0.589)(<.001)(<.001)(0.009)(0.989)(<.001)(<.001)(0.004)(0.815)(<.001)

Our second approach to measuring abnormal long-run stock performance uses the calendar-time portfolio method to calculate abnormal returns. Panel E reports the monthly average abnormal return, which is the intercept calculated using the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model, respectively. It is worth noting that the intercepts for all PP portfolios are significantly positive but those for PS portfolios are insignificant. Furthermore, both factor models show significant differences between PP and PS portfolios for all insider categories. Overall, Table 9 confirms our prior expectation that this paper's main findings are stronger in the presence of consistent insider trading behavior in the 1-year post-announcement period.

4. CONCLUSION

  1. Top of page
  2. Abstract
  3. 1. INTRODUCTION
  4. 2. THE SAMPLE
  5. 3. EMPIRICAL TESTS AND FINDINGS
  6. 4. CONCLUSION
  7. REFERENCES

The anomalous long-run performance of equities subsequent to open market repurchases remains a contentious topic in the literature. One aspect which has yet to be addressed is whether this performance is primarily the result of public or private information. The purpose of the current study is to focus on this question by using the insider trading data as a proxy for private information. The different trading behavior of insiders following the repurchase announcements motivates us to empirically investigate the potential heterogeneity of OMR programmes by examining the dichotomous expectations hypothesis. This hypothesis reflects two types of expectations of corporate insiders about firms’ prospects following the announcements of share buyback. One is related to the creation of buyback bonanzas, suggesting that some insiders may use private information to sell their shares at attractive prices following the announcements of share repurchases. The other is related to informed buying, suggesting that some insiders of OMR firms may expect an improvement in future operating performance and use this information to initiate purchases for their own accounts.

Our first set of tests explores the trading pattern of insiders in the four quarters prior to and the four quarters subsequent to open market repurchase announcements. Here we utilize the consensus of insider trading methodology to measure abnormal net purchases or sales relative to a control firm selected on the basis of industry, size and book-to-market. Despite the positive average long-term drift in prices that has been documented in the prior literature, our results reveal net abnormal sales in each of the eight quarters surrounding the repurchase announcement.

Next, the paper explores the operating and financial market performance of our sample firms during the 3-year period from year +1 to year +4 relative to the OMR announcements. This analysis segments each performance measure by the insider trading activity observed in the initial post-event year. Results are partitioned by abnormal purchases and sales relative to the announcement. The data show that purchases are accomplished during a period of decreasing prices which subsequently reverse in the long term. In a similar fashion, sales are made during a period of increasing prices which also reverse. This trading activity is further segmented by insider seniority classification and we generally find that trading by senior insiders is more likely to be predictive of future firm performance than other reported insider trades. These univariate tests provide evidence of informed trading by insiders and support the dichotomous expectations hypothesis.

Our multivariate methodology examining long-run stock returns utilizes regression analysis to test the dichotomous expectations hypothesis and employs appropriate controls established within the related literature. These tests once again provide consistency with the dichotomous expectations hypothesis and support our earlier univariate results. Our findings also suggest the presence of profitable trading at the firm level in terms of the actual percentage of shares sought which are ultimately repurchased.

With the employment of abnormal changes in long-run operating performance as the potential content of private information conveyed by insider trades, our regressions show that the abnormal changes in return on assets of repurchasing firms is positively related to post-OMR-announcement insider trades. The results suggest that insider trades may contain private information about subsequent abnormal changes in operating performance. In conclusion, our combined results indicate that private information relevant to the future change in operating performance is associated with the long-term financial market performance of firms subsequent to open market repurchase announcements.

  • Note:This figure presents the average abnormal operating performance following OMR announcements. Abnormal operating performance for an OMR firm is measured as the change in return on assets for the given year following OMR announcement relative to a performance-matched firm. NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement.

  • Note: This figure depicts the cumulative abnormal returns (CARs) categorized by post-OMR-announcement senior insider trading during the 1-year period after the announcement. NP is calculated as the difference between the number of insider purchases and sales and divided by the number of total insider trades within the 1-year period after the OMR announcement. The benchmark return is the return of matching firms based on industry, size and book-to-market ratio. One year is measured by 252 trading days relative to the announcement day.

  1. 1

    Ikenberry et al. (1995) employ publicly available book-to-market ratios and demonstrate that the positive long-run drift in returns is most pronounced for value firms. There is debate, however, over whether the primary finding of long-run abnormal performance may result from a statistical artifact. Fama (1998) and Mitchell and Stafford (2000) assert that the original buy-and-hold return methodology is biased. Chan et al. (2007) and Peyer and Vermaelen (2009), however, provide evidence inconsistent with this claim.

  2. 2

    As reported by Megan Burnett, “According to Standard & Poor's, which is officially calling the surge of open market repurchases a ‘buyback bonanza,’ share repurchases hit record levels during the third quarter of 2006, up 35% over the prior year and a whopping 140% over 2004” (Wall Street Journal, February 18, 2007). Interestingly, the article further cites Albert Meyer, President of the financial advisory firm, Bastiat Capital, who suggests that some repurchases may exist “purely for the benefit of insiders” and that “a giant red flag” exists whenever insider selling coexists with these repurchase programmes.

  3. 3

    We make no explicit prediction about insider trading prior to the OMR announcement as the motivation may be diminished relative to post-event trading for several reasons. First, it makes little economic sense to purchase before the event with the hope of capturing the modest announcement period returns which have been previously documented. As reported by Comment and Jarrell (1991), open market repurchase programmes are more likely to be weaker signals of undervaluation than fixed price tender offers. Peyer and Vermaelen (2009) report mean 3-day cumulative abnormal returns (CARs) over the 1991 to 2001 period of just 2.4%. This result is essentially identical to the mean announcement for OMRs reported by Comment and Jarrell for the 1984 through 1989 period but substantially less than the 11% they report for fixed price tender offers. Although it is possible that insiders might assume that particular announcements would have substantially greater short-term price reactions, these mean revaluations are still substantially less than the 4-year long-run CARs of 24% reported by Peyer and Vermaelen (2009). Second, the same study reports average prior 6-month abnormal returns of –9% which are used to partially support their conclusion that these programmes are motivated by an overreaction to bad news. This latter finding suggests that prior purchase positions are subject to a potential loss in value if they are initiated prematurely. Lastly, insider trading before any public disclosure is more likely to be subject to SEC scrutiny than similar trading after the disclosure (Korczak et al., 2010).

  4. 4

    The subsequent empirical results do not change qualitatively when we exclude financial firms. Following Ikenberry et al. (1995), Chan et al. (2004), and Peyer and Vermaelen (2009), we report the results of both financial firms and non-financial firms together.

  5. 5

    The breakpoints that we use for book-to-market ratios are downloaded from Kenneth French's online data library. All NYSE stocks on CRSP-COMPUSTAT are sorted to determine the NYSE decile breakpoints for book-to-market ratios. NYSE, AMEX and NASDAQ stocks that have the required CRSP-COMPUSTAT data are then allocated to 10 book-to-market portfolios based on the NYSE breakpoints.

  6. 6

    We define the variable, PSought, as the percentage of outstanding shares announced to be repurchased. If PSought is not available on SDC, we calculate a proxy for PSought following Stephens and Weisbach (1998). We first define the dollar amount of the repurchase programme divided by the share price on the announcement date as the number of shares intended to be repurchased. We then divide this number of shares by the number of outstanding shares and use this quotient as our proxy for PSought.

  7. 7

    The conclusions in this study remain unchanged if NP is defined in terms of the dollar value of trades or the number of shares traded.

  8. 8

    Jenter (2005) offers additional motivations for insider sales including tax management and avoidance of trading law violations. Cooke reports that “the conventional wisdom on Wall Street that insiders have many reasons to sell company stock — including a desire to diversify, buy a boat, or fund a child's education — but only one reason to buy: a desire to make money” (Wall Street Journal, November 12, 2003, Page C14).

  9. 9

    If a repurchasing sample firm lacks sufficient operating performance data for the yearly calculation, our procedure considers only the announcement quarter operating performance for potential matching firms. We refer interested readers to page 421 of Lie (2005) for further details of these procedures.

  10. 10

    There are fewer observations in Table 3 than in our stock return tests shown in Tables 5 and 7 due to the relative unavailability of accounting performance data.

  11. 11

    In unreported results, we examine the stock and operating performance following OMR announcements in each quintile classified on the basis of NP. The results indicate that both stock and operating performance increase in insiders’ net purchases. The mean and median difference between the 1st and 5th quintile of all insider trades and senior insider trades are significant at the 5% level or better. Thus, our results, classified by NP-based dummies, are robust when considering the full distribution of the continuous NP variable. The conclusions remain unchanged even if we classify the sample by the dollar value of insider trades or the number of shares traded by insiders.

  12. 12

    The following steps describe our procedure for constructing calendar-time portfolios and estimating the intercepts for each portfolio. Step 1: We collect all monthly returns of OMR firms over the 36-month period, starting from the 13th month after the announcement date in terms of calendar month. Step 2: For each calendar-month over the sample period, we form value-weighted portfolios based upon insider transaction type. Step 3: Within each portfolio, we regress the monthly portfolio returns on the factors from both the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model. The estimated intercepts from these monthly regressions are then used as our proxy for abnormal performance.

  13. 13

    Artmann et al. (2012) recently provided an out-of-sample test of the explanatory power of both factor models using a large sample from the German market. Also, Gregory et al. (2013) construct and test alternative versions of the Fama–French and Carhart models for the UK market.

  14. 14

    The design of our dependent variable is such that a significant portion of the explained variation in the OMR firm buy-and-hold return is already accounted for by the corresponding matching firm return. Hence, the regression models can be expected to yield a rather low coefficient of determination. See, for example, Chou et al. (2006). Our focus here is on the potential significance of the independent variables rather than on the explanatory power of the regression.

  15. 15

    We have checked the values of the variance inflation factors (VIFs) in Table 7. All such factors on NP (across insider classifications) and Abnormal Operating Performance are less than 1.4. The general rule for the VIF test is that a value greater than 10 may lead to misleading inferences (Belsley et al., 2004). Therefore, our model does not severely suffer from multicollinearity considerations.

  16. 16

    In unreported results, we find that the standardized regression coefficients on Senior NP are 0.061 in model (2) and 0.066 in model (5). The interpretation of 0.061 (or 0.066) is “each one standard deviation increase in the net purchases of senior insiders is associated with a 0.061 (or 0.066) standard deviation increase in the long-run buy-and-hold abnormal return.” However, the standardized regression coefficients on Other NP are only 0.015 in model (2) and only 0.009 in model (5), which are much smaller than those on Senior NP. Therefore, the net purchases of senior insiders also appear to have a much stronger association with the long-run buy-and-hold abnormal return than the net purchases of other insiders.

  17. 17

    We thank the referee for pointing this out.

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  1. Top of page
  2. Abstract
  3. 1. INTRODUCTION
  4. 2. THE SAMPLE
  5. 3. EMPIRICAL TESTS AND FINDINGS
  6. 4. CONCLUSION
  7. REFERENCES
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