What is the influence of managerial fraudulent behavior in stock option backdating on the volatility of stock prices of direct competitors?

“The Impact of Stock Option Backdating on Stock Price

Volatility on Industry Peer Firms”

What is the influence of managerial fraudulent behavior in stock

option backdating on the volatility of stock prices of direct

competitors?

Master of Science: Business Economics – Finance

Professor: Dr. T. Jochem Student: Oscar van der Laan Student nr: 10871519

Field: Corporate Governance December 2015

II

Statement of Originality

This document is written by Student Oscar van der Laan who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

III

Abstract

This research investigates whether managerial fraud has a significant influence on the volatility of the stock returns of peer firms, which have not been exposed to stock option backdating by its executives. This research divides three hypotheses to investigate the influence of stock option backdating on the firm riskiness of the fraudulent firm combined with searching for the impact on control group in the same time period, which have not engaged in stock option backdating. The final hypothesis is to measure the change in firm riskiness within 2 years in the peer group, after backdating has occurred in the same industry by a competitor. I have found significant results that stock option backdating has influenced the volatility of stock return of peer firms in different industries after the Sarbanes-Oxley Act of August 29th, 2002 had been implemented. This research used a total of 5 industries in the United States with a total of 1807 firms.

IV

Contents

2 Literature Review ________________________________________________________ 8

2.1 Corporate Governance And The Principal-Agency Theory __________________________ 8 2.2 Impact Of Compensation Bonus On Risk-Taking Behavior Of Chief Executives __________ 9 2.3 Peer Effects In Product Market Competition ___________________________________ 10 2.4 Sarbanes Oxley Act 2002 ___________________________________________________ 10 2.5 Effects of Sarbanes Oxley Act On Stock Price ___________________________________ 11

3 Methodology __________________________________________________________ 13 3.1 Hypotheses ______________________________________________________________ 13 3.2 Data Collection ___________________________________________________________ 13 3.3 Model __________________________________________________________________ 15 3.4 Preliminary Analysis_______________________________________________________ 16 4 Results _______________________________________________________________ 21 4.1 Backdating Sample ________________________________________________________ 21 4.2 Peer Model ______________________________________________________________ 24 5 Conclusions ____________________________________________________________ 25 5.1 Main Conclusions _________________________________________________________ 25 5.2 Limitations & Further Recommendations ______________________________________ 26

References _______________________________________________________________ 27 Appendix _________________________________________________________________ 29 Summary Statistics _____________________________________________________________ 29 Frequencies __________________________________________________________________ 30 Correlations __________________________________________________________________ 32 OLS Regressions _______________________________________________________________ 34

V

Tables

TABLE 1: SUMMARY STATISTICS BACKDATING GROUP. ____________________________________________ 29 TABLE 2: SUMMARY STATISTICS CONTROL GROUP. _______________________________________________ 29 TABLE 3: FREQUENCIES INDUSTRIES BACKDATING GROUP. _________________________________________ 30 TABLE 4: FREQUENCIES YEARS BACKDATING GROUP. ______________________________________________ 30 TABLE 5: FREQUENCIES INDUSTRIES CONTROL GROUP. ____________________________________________ 30 TABLE 6: FREQUENCIES YEARS CONTROL GROUP. _________________________________________________ 30 TABLE 7: DISTRIBUTION OF THE BACKDATED AND PEER GROUP FIRMS. _______________________________ 31 TABLE 8: CORRELATIONS BACKDATING GROUP. __________________________________________________ 32 TABLE 9: CORRELATIONS CONTROL GROUP. _____________________________________________________ 33 TABLE 10: OLS REGRESSION BACKDATING GROUP SAMPLE, CORRECTED FOR HETEROSCEDASTICITY. _______ 34 TABLE 11: OLS REGRESSION CONTROL GROUP SAMPLE, CORRECTED FOR HETEROSCEDASTICITY. __________ 35 TABLE 12: OLS REGRESSION TESTING THE RELATION BETWEEN FIRM RISK AND OPTION VARIABLES WITHIN 2

YEARS OF THE BACKDATING EVENT FOR THE TOTAL CONTROL GROUP SAMPLE. ___________________ 36 TABLE 13: OLS REGRESSION TESTING THE RELATION BETWEEN FIRM RISK AND OPTION VARIABLES FOR THE

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1 Introduction

In corporate governance, checks and balances must be created between managers and shareholders of the corporation (Fama et al., 1980). If a firm is unsuccessful in bridging the distance between both, agency problems and costs will arise. The target of the field of corporate governance is to overcome the conflicts and align the interests of both sides. However, due to the opportunities and power, which corporate managers have, some

executives and directors have been abusing the freedom by conducting fraudulent behavior to benefit themselves financially. In this research, I will try to determine the influence of the misconducts these executives have committed on the volatility of the stock returns of their own firms, a control group and most notably their direct industry peer firms. The objective of this paper is to investigate the effects of managerial fraudulent behavior on the volatility of stock return of direct rivals in the same industry. Prior research has been conducted on fraudulent behavior among directors in different forms. The most notable white-collar crimes have been accounting scandals, also due to the larger impact they have had on their local economies. The Dodd-Frank Act in the United States was responsible for implementation.

1.1 Executive Compensation

Managerial fraud within executive compensation has taken on many forms. The most

representative form of fraud has been stock option backdating. Especially since 2005, notable examples of fraud have been described in literature. However, other notorious forms have been accounting scandals and say-on-pay. Accounting scandals have mainly arisen between 1997 and 2004 approximately, while say-on-pay is a relatively lesser-known style.

1.2 Stock Option Backdating

However, the theme of stock option backdating has been prevalent in the early years of the new millennium. This theme is interesting, because accounting practices have been largely unable to prevent this type of fraud for some years, resulting in several executives relishing the opportunity without being penalized until years later if at all. Stock option backdating is defined as altering the grant date when the stock price was low in order for the executive to

7 earn a large sum of funds (Collinsa , Gongb, & Lic, 2008, p.1). The difference in price

between the strike price of the option and the stock price at the execution date will constitute the profit. However, in 2002 the Sarbanes-Oxley Act was introduced, which enforced firms to enlighten the Securities and Exchange Commission (SEC) within two business days of the granted stock options (Heron & Lie, p.519). The knowledge derived from the answer to the central research question is important, because the outcome could determine the quantity of the impact direct rival firms have on one another in any particular industry in the form of fraud.

1.3 Literature Review

In order to determine the influence of peer groups in business, it is crucial to outlay a set of defining principles a peer must adhere to. Peer groups could be defined in multiple areas, ranging from size, industry, geography, product focus to even compensation of the chief executive officer1. The reference is made to firms, which rather construct their executive compensation towards higher paid executives from peer firms. This measure would imply self-serving behavior on behalf of the (newly) chief executive.

The goal of this research is to determine the influence of managerial fraud on the corporate governance level of direct competitors. Therefore, I had to establish guidelines to compare firms in industries to find out whether or not they are to be described as peers, or competitors, in the same industry. The firms used were in 5 different industries and all these industries combined created the entire control group.

1.4 Structure

The thesis is structured in the following order. Firstly, I will describe the literature

concerning the managerial fraudulent behavior in corporate governance with a focus on stock option backdating from 2003 until 2014. Secondly, there will be a chapter about hypotheses in stock option backdating. Data methodology and regression results follow and I will end the thesis with a conclusion of the data results and provide an answer to the research question. On the last pages, an appendix will be filled with regression results and graphs, accompanied by references to the literature used.

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2 Literature Review

This section provides information about the literature I consulted to answer the central research question. I have elected to divide the parts into 5 subsections. Firstly, I will describe the central theorem behind corporate governance and the principal-agent theory. Secondly, the definition of a peer is described in the context of product market compensation. Thirdly, the stock option backdating scandals and their impacts on stock volatility will be discussed. Fourth, a part about the entrance of the Sarbanes-Oxley Act will follow. Finally, the influence of the Sarbanes-Oxley Act of 2002 will be revealed.

2.1 Corporate Governance And The Principal-Agency Theory

Corporate governance is, as previously mentioned, described as a system of checks and balances in order to align interests of principals and agents. Within corporate governance, a well-defined problem is the principal-agent problem, which explains the differences in motivation between the principal (shareholders) and the agent (executives) of the firm. (Larcker & Tayan, 2011). Agents would have a higher tendency to act in their self-interest, whereas the principals will have the interests of the entire firm at heart. These actions will lead to negative consequences for the shareholders, while they have to pay the costs these risks might entail. The effectiveness of upholding strong corporate governance within a firm depends mostly on the control mechanism combined with the eventual agency costs and the implementing of the control mechanism (Larcker & Tayan, 2011). Within current knowledge, several researchers have argued that the control mechanism is divided between internal and external monitoring (Fama & Jensen, 1983). Internal monitoring control exists of board of directors, (Fama, 1980), small groups of large shareholders and the relative quantity of stockholdings by the chief executive (Denis & Denis, 1995). Also, a large outside

shareholder will result in closer monitoring (Shleifer & Vishny, 1986). However, external monitoring control consists of legal rules, political systems and market regulation (Jensen, 1993). Additionally, external control has an influence on internal control mechanisms in order to keep the executives in line.

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2.2 Impact Of Compensation Bonus On Risk-Taking Behavior Of Chief Executives

In the past, a few researchers have determined that a relatively large bonus scheme in the compensation of chief executives could induce larger risk-taking by the executive. Large stock holdings induce executives to engage in investing in higher variance projects (Agrawal & Mandelker, 1987). The benefits for managers will be larger while the

shareholders would have to bear the costs of the potential losses. Additionally, stock return variances and volatility increase after stock options have been granted to executives

(DeFusco et al., 1990). Therefore, we can conclude that shareholders consider stock options for executives a threat to the value of their stock. However, between 1984 and 2001 average stock option ownership among managers from United States corporations had risen from less than 1% of the total compensation package to approximately 67% (Hall, 2003). This indicates that corporations have been willing to engage executives more in firm performance. The performance of firms distributing stock options to executives is proven to be of a higher calibre (Hillgeist, 2003). Not only in performance, but also firm value increases with more stock options granted. Even though only in manufacturing companies, according to Mehran (1995), the Tobin’s Q will correlate positively with stock options. Managers with a higher bonus scheme related compensation will more easily invest in research and development, arrange a higher leverage for the firm and focus on fewer lines of business (Coles et al., 2006). So even at the balance sheet decisions of the firm, the higher risk compensation scheme will have an impact. More specifically, the stock options also have a positive relation with investing in projects with higher risks and rewards (Chen et al., 2005). Saunders et al. also concludes that banks with a higher management equity ownership will exhibit greater risk-taking behavior by executives in the banking industry. This is mainly attributed to the use of call and put options in a more volatile time. However, contradicting results exist. In a different time period, managerial ownership has had a negative relationship with risk-taking (Chen et al., 1998). The results of this paper have had a relevance for regulators in the financial industry to tighten rules concerning firm risk. It has been discovered that a positive relationship between excess compensation for executives and firm underperformance exists (Brick, Palmon & Wald (2005). Combining findings of firm underperformance and higher risk-taking, when executives receive respectively higher compensation and stock options as a percentage of their total compensation, there is some evidence that rewarding executives in an aggressive manner has the potential to lower shareholder value.

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2.3 Peer Effects In Product Market Competition

In this research, I will compare the results of firms, where executives have conducted stock option backdating versus their peers, where no fraud has been committed. In order to determine the difference, it is important to establish rules as to when a group of firms can considered being peers. Businesses can be categorized in markets, products, size, geography and other factors. In previous research, products and industry groups have been strong indicators, instead of product processes (Hoberg & Phillips, 2009). Another approach is to match firms based on their own business descriptions on published quarterly results and by geography. This measurement has proven to be more effective, considering it takes into effect the changing nature of many industries over the years. Stock option compensation is partly determined by the magnitude of pay that executives at rival firms are granted. Therefore, the importance of compensation at peer firms is vital, just as picking the correct peer group for the company. To be able to determine if peer groups are actually chosen correctly, firms are exposed to market shocks and their reactions have been measured. If they are in common, peer groups can be identified (Albuquerque, 2006). A firm’s size is the most important factor, since equally sized firms tend to have similar reactions to market shocks. Obviously, other factors, such as geographical location, are relevant as well. Interestingly enough, stock returns have a positive relation on relative chief executive compensation. As previously explained, researchers have demonstrated both the positive and negative relation between incentive based compensation and stock returns.

2.4 Sarbanes Oxley Act 2002

‘After August 29, 2002, the Sarbanes-Oxley Act required that companies notify the SEC within two business days after granting stock options. In 2003, the SEC required increased disclosure of stock option plans. The SEC issued enhanced option grant disclosure rules effective December 15, 2006. Policy options to further reduce backdating and other timing manipulation include changes in SEC regulations and a change in the tax law.’

Due to several managerial fraud scandals, most of which committed in the 1990’s and 2000’s, change in regulation of managers of large corporations was needed. The Act is aimed at providing a stronger corporate governance, management and board responsibility and

11 the Sarbanes Oxley Act (SOX) was an ever-increasing flow of fraud in the form of

accounting scandals and stock option backdating. As the examples of Enron and Tyco became widespread among the American public, regulators had come to the agreement that monitoring control had been insufficient and an external control mechanism should be created. Without describing SOX in elaborate detail, the most important requirements of the Act are as follows:

As of August 29th_{, 2002, firms are obliged to disclose granting stock options to executives}

within two business days instead of sixty business days. Since implementing SOX, most firms have obeyed the rule.

Previous studies have found that the volatility of a companies’ stock price has been

abnormally negative prior to the announcement of stock option grants. (Heron & Lie, 2007). Additionally, stock returns are abnormally positive after the announcements. This effect has weakened since the implementing of SOX. Obviously, logic dictates fewer fluctuations of the stock price are possible if the backdating period is reduced to two business days. Chief executives have to ascertain the accuracy financial statements provided by the firm. Furthermore, auditors have to be scrutinized with tighter internal controls, for which the board of directors is responsible (soxlaw.com). Secondly, corporate loans to executives and directors have been prohibited (Cohen, Dey, & Lys, 2004). Also, the Act requires return of incentive based compensation including profits from stock sales. This could be part of the explanation why executives have opted to lower their risk-taking activities after SOX was implemented. The structure of internal controls also has to become transparent to the

regulators. Accountants, who knowingly participate in fraudulent behavior, will be risking up to ten years in federal imprisonment with the executive at fault being penalized to a

maximum of 20 years for any fraudulent conduct.

2.5 Effects of Sarbanes Oxley Act On Stock Price

The Sarbanes-Oxley Act has reduced the large volatility in stock price returns pre- and post-stock options granted (Narayanan & Seyhun, 2005). However, the SOX had not completely eliminated the fluctuations altogether. Another explanation of positive abnormal returns of stock prices is thought to be the granting of stock options to executives just before

12 announcing sensitive company information in order to benefit the executives (Solomon, 2004). Still, the SOX Act has not proven to be entirely efficient. Approximately 24% of the researched firms have a lagged response of more than two business days. As suspected, this group of firms experienced a larger than average post-grant date fluctuation of stock price after 2002. Especially smaller firms (market capitalization: $29 million) have a larger tendency to apply later for granted stock options. Risk-taking by firms has also altered by decreasing capital expenditures and investing in research and development by chief executives after the Sarbanes Oxley Act has made its entrance. The performance-based compensation of executives as a percentage of total compensation has decreased, which lowers the incentive for executives to engage in riskier projects.

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3 Methodology

3.1 Hypotheses

H1: CEO stock option backdating resulted in the increase of firm riskiness, when higher stock options were added to their remuneration plan.

Firm riskiness is defined in separate ways. The measurements will be discussed in the literature part in more detail.

H2: CEOs who did not undertake stock option backdating did not increase the firm riskiness, when higher stock options were added to their remuneration plan

Of utmost importance, is the relativity with peer groups of the firms, which have not had the influence of stock option backdating. Firm size is expected to be one of the more dominant factors in comparing peer groups.

H3: There is a positive relation between the stock option backdating by a firm and the stock return volatility of its peer group within two years.

This hypothesis will investigate whether a chief executive, who has backdated his or her stock options, had a statistically significant impact on the volatility of the stock returns of its peer group. This peer group consists of firms in the same industry in the United States in the same year.

3.2 Data Collection

I have collected the majority of the available accounting data from Compustat within the Wharton Research Data Services (WRDS) database. Compustat has a large database with variables, ranging from annual CEO compensation, equity awards, stock option granting to other financial bonuses for directors. Within WRDS, the Centre for Research in Security Prices (CRSP) provides fundamental stock prices, inflation rates and a combined

14 and Exchanges Commission (SEC), which publicly discloses (former) executives and

directors alleged and/or accused of fraudulent behavior whilst occupying their positions. Furthermore, the Federal Reserve Bank of St. Louis has supplied an abundance of macro-economic indicators, such as gross domestic product, unemployment rates and currency exchange rates. Finally, I have used additional non-academically published information from the Wall Street Journal, New York Times and the Financial Times. The regression is meant to demonstrate the effect of stock option backdating on the firms’ long-term stock return. I expect to witness a negative relation due to shareholders’ mistrust in the firm’s corporate governance. This might lead to reputational damage and a smaller desire to hold the stock.

(INSERT TABLE 1 HERE)

This is a summary of relevant statistics used to create the first hypothesis. Beta, sdreturns and sdresiduals are the three variables, which measure firm riskiness. These are drawn from the Chen et al. (2005) study. In their study, they include a fourth firm riskiness measurement, Ri or return on investment. I have excluded this measurement, since their focus was placed on the financial sector and this research focuses on all industries. This table provides basic descriptive variables for the dataset of the backdating sample. Beta is a measurement of systematic risk and the coefficient of the stock return compared to the market (S&P 500).The sdreturns represents the standard deviation of one stock to the market return. Sdresiduals is a single standard deviation as a non-systematical risk, which cannot be explained by the market returns. Options is the average dollar amount in options received by the chief executive in a given year. TotalCompensation was used to calculate percOption as what percentage the options are as a part of total compensation in dollar values. Accumulated_Option represents the amount of options the chief executive has been granted in total. PercOption is the percentage of total compensation, which is granted in the form of options. In order to have smaller samples, Size is measured as a log function of total assets, so the beta would not be too low. Additionally, the log function decreases the quantity of size so the normal

distribution would be more appropriate. CapitalRatio is total shareholders’ equity divided by total assets. Growth equals the revenue growth measured over 3 years. DividendYield represents the annual percentage of profits distributed to shareholders in the form of dividend. StockPrice is the average stockprices of all 33 firms. deltaWealth equals the year-on-year shareholders’ equity growth measured in millions of U.S. dollars. _Iyear are the

15 dummy variables representing the percentages of the amount of backdating per year, ranging from 2004 until 2014. The last four rows present the four quartiles, in which data are

presented. This is created in order to established a clear pattern and have an indication of outliers.

3.3 Model

The OLS Regression Model for the backdated and peer group firms sample is:

𝑅𝑖𝑠𝑘 = 𝛽0+ ∑ 𝛽𝑖𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑡 8

𝑖=1

+ 𝜀 Eq 1

The OLS Regression Model for the event test is:

𝑅𝑖𝑠𝑘𝑡= 𝛽0+ 𝛽1𝑏𝑎𝑐𝑘𝑑𝑎𝑡𝑒𝑑𝑡+ 𝛽2𝑝𝑒𝑒𝑟𝑡+ ∑ 𝛽𝑖𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑡 8 𝑖=3 + ∑ 𝛾𝑗𝑌𝑒𝑎𝑟𝑡 11 𝑗=1 + ∑ 𝛿_𝑗𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑡 4 𝑘=1 + 𝜀 Eq 2

 Where firm risk 𝑅𝑖𝑠𝑘𝑡 is one of the firm risk measures, Betas, standard deviation of the

returns and standard deviation of the residuals.

 Where 𝑏𝑎𝑐𝑘𝑑𝑎𝑡𝑒𝑑_𝑡 is a dummy variable that is 1 only if the firm did have backdating scandal in year "t", else 0,

 Where 𝑝𝑒𝑒𝑟_𝑡 is a dummy variable that is 1 only if the firm did have an industry peer that had a backdating scandal in year "t" and no own scandal in year "t", else 0,

 𝛽1 is then the increase in firm risk that a firm with a backdating scandal had,

16 scandal.

 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠 are log of the accumulated options, percentage options owned, log of total assets, capital ratio, the growth, dividend, price and the delta of wealth, for firm i in year

t,

 𝑌𝑒𝑎𝑟 are the year fixed effects, and  𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 are the industry fixed effects.

3.4 Preliminary Analysis

Table below describes summary statistics for the first hypothesis to determine if stock option backdating has a positive relation with firm riskiness in the form of three risk measures. In total, this sample contains 151 stock option backdating occasions spread over 33 firms in the timeframe between 2003 and 2014. The numbers differ in some of the variables, because of a lack of data provided over the time period. The beta has a mean of 1.381 with a standard deviation of 0.244. The beta varies between 1.143 and 2.010 and has a median of 1.284. The standard deviation of stock returns has an average of 2.8% with a median of 2.7%, which is between a tight frame of 2.1% and 4.3%. Standard deviation residuals, the non-systematic risk is on average 2.5% with a median of 2.4%, ranging from 1.9% and 3.4%. Option has a mean of 1050.834, a standard deviation of 1728.098 and a median of 0.0. TotalCompensation has an average of 6838.235, a standard deviation of 5590.694 and a median of 6380.906. Accumulated_Option has an average of 57023.474, with a standard deviation of 205753.191 and a mean of 3402.340. This is due to a small amount of firms granting a large amount of stock options, which can be seen by p90 entailing 77813.475. PercOption is 0.167 with a standard deviation of 0.238 and a median of 0.000. Again, the p90 indicates that a small amount of firms has a large impact on the total average, because p90 value is 0.479. Size of the firms has an average of 8.289, a standard deviation of 1571 and a median of 8181. CapitalRatio has a mean of 59.8% with a median of 62.7% and a standard deviation of 17.8%. Growth also has an average of 63.0% with a median of 31.0% and a standard deviation of 93.5%, due to a spread out distribution of firms, some of which have experienced negative growth. Dividend Yield has an average of 42.2% with a standard deviation of 101.6% and a median of 10.0%. The average StockPrice was 54.420 with a standard deviation of 82.064, due to a large maximum value of 667.105 and a median of

17 36.260. deltaWealth has a mean of 1518.452 and a standard deviation of 5999.936 and a median of 187.194. _Iyear are binary variables, which can either be 0 or 1, which explains the median and quartile values of 0.0.

(INSERT TABLE 1 HERE)

The table below provides basic descriptive variables for the dataset of the control group. Beta is a measurement of systematic risk and the coefficient of the stock return compared to the market (S&P 500). The sdreturns represents the standard deviation of one stock to the market return. Sdresiduals is a single standard deviation as a non-systematical risk, which cannot be explained by the market returns. Accumulated_Option represents the amount of options the chief executive has been granted in total. PercOption is the percentage of total compensation, which is granted in the form of options. In order to have smaller samples, Size is measured as a log function of total assets, so the beta would not be too low. Additionally, the log function decreases the quantity of size so the normal distribution would be more appropriate.

CapitalRatio is total shareholders’ equity divided by total assets. Growth equals the revenue growth measured over 3 years. DividendYield represents the annual percentage of profits distributed to shareholders in the form of dividend. StockPrice is the average stockprices of all firms. deltaWealth equals the year-on-year shareholders’ equity growth measured in millions of U.S. dollars. _Iyear are the dummy variables representing the percentages of the amount of backdating per year, ranging from 2004 until 2014. The last four rows present the four quartiles, in which data are presented. This is created in order to established a clear pattern and has an indication of outliers. In total, this sample contains 15897 stock option backdating occasions spread over 1807 firms in the timeframe between 2003 and 2014. The beta has an average of 1.000, with the median at 0.998. sdreturns has a mean of 0.161 and a median of 0.141, with a standard deviation of 0.043. sdresiduals has an average of 0.151 and a median of 0.130. Options has a mean of 1451.658, a standard deviation of 4312.097 and 579.010. TotalCompensation has a mean of 5898.812, a standard deviation of 6670.622 and a median of 4042.465. Accumulated_Option was on average 8935.552 with a standard

deviation of 28856.243, ranging from a minimum of 0 to a maximum of 96160.696 due to a high amount of control group firms. PercOption has an average of 19.4% with a median of 16.7% and a standard deviation of 18.5%. Size has an average of 7.679 and a standard deviation of 1.533. CapitalRatio has a mean of 52.2% with a standard deviation of 21.3%.

18 Growth shows a mean of 27.7% with a median of 21.7% and a p90 of 87.6%. DividendYield is on average 34.1% with a standard deviation of 50.3%. StockPrice has a mean of 31.601 and a standard deviation of 20.214 with a maximum of 91.710. deltaWealth has a mean of 213.636, a standard deviation of 522.613 and a median of 62.121. _Iyear are binary variables, which can either be 0 or 1, which explains the median and quartile values of 0.0.

(INSERT TABLE 2 HERE)

The table below presents the different amount (N) of industries of the total backdating group. The peer group consists of the industries, which have been prone to stock option backdating. The banking industry is purposefully ignored, because this industry has already been

discussed by Chen et al. (2006). ‘Pct’ is the percentage of firms, where stock option backdating occurred in the given year out of the total amount of years. ‘Cumpct’ is the cumulative percentage, which adds each year to the total sum of previous years.

(INSERT TABLE 3 HERE)

The table below describes the amount (N) of stock option backdating frequencies per year of firms, whose chief executives have engaged in stock option backdating when higher stock options were added to their remuneration plan. These are the firms prosecuted by the Securities and Exchange Commission.

(INSERT TABLE 4 HERE)

The table below presents the different industries of the total control group. The peer group consists of the industries, which have been potentially prone to stock option backdating. The banking industry is purposefully ignored, because this industry has already been discussed by Chen et al. (2006). The public industry resembles public services provided by

semi-governmental organizations.

19 The table below presents the amount of firms, which have operated in the same industries, but whose chief executives have opted not to engage in stock option backdating when higher stock options were added to their remuneration plan. The table starts at 2006, since the stock option backdating scandals took place as of June 2006.

(INSERT TABLE 6 HERE)

The table below describes the distribution of the backdated and peer group.

(INSERT TABLE 7 HERE)

The table below reports the correlations of the regression of the first hypothesis to demonstrate the influences each factor has on other factors for the backdated firms.

AccumulatedOptions is displayed with a ln function to be able to display smaller outcomes of numbers. ***, **, and * represent statistical significance at, respectively, the 1%, 5%, 10% level. These will be discussed. Beta shares a correlation of 0.206 with Options, a 0.239 relation with Accumulated_Option, 0.219 with percOption and a correlation of 0.299 with Growth. Sdreturns has a positive correlation of 0.949 with sdresiduals. Options has a positive relation of 0.542 with Accumulated_Option and a 0.812 relation with Options.

TotalCompensation has a positive relation of 0.286 with Size and a negative relation of -0.299 with Growth. Accumulated_Options has a 0.323 correlation with percOption and a 0.252 correlation with Size. percOption shares a negative correlation of -0.281 with Size. Size has a negative correlation of -0.266 with CapitalRatio, a 0.373 correlation with

DividendYield, a 0.524 correlation with StockPrice and a 0.436 correlation with deltaWealth. CapitalRatio is for 0.313 correlated with Growth. Growth has a correlation of 0.427 with StockPrice and 0.441 with deltaWealth. DividenYield correlates for 0.554 with StockPrice. StockPrice correlates with deltaWealth for 0.844.

(INSERT TABLE 8 HERE)

The table below reports the correlations of the regression of the first hypothesis to demonstrate the influences each factor has on other factors for the control group.

20 numbers. ***, **, and * represent statistical significance at, respectively, the 1%, 5%, 10% level. These will be discussed. Beta has a negative relation of -0.572 with sdreturns, a negative relation of -0.544 with sdresiduals, a positive relation with Accumulated_Option of 0.0728, a positive relation with CapitalRatio of 0.0707, a positive relation of 0.0925 with Growth and a positive relation of 0.115 with StockPrice. Sdreturns has a relation of 0.997 with sdresiduals, a negative relation of 0.0675 with TotalCompensation, a relation of -0.0910 with Accumulated_Option, a relation of -0.164 with Growth and a -0.148 with StockPrice. Sdresiduals has a negative relation of -0.0720 with TotalCompensation, a

negative relation of -0.0854 with Accumulated_Option, a relation of -0.153 with Growth and a negative relation of -0.141 with StockPrice. Options has positive relations of 0.766 with TotalCompensation, 0.528 with Accumulated_Option, 0.356 with percOptions, 0.281 with Size, a negative relation of -0.0696 with CapitalRatio and positive relations with 0.0889 with Growth, 0.0879 with StockPrice and 0.218 with deltaWealth. TotalCompensation has

positive relations with Accumulated_Option of 0.477, with percOptions of 0.127, with Size of 0.605, a negative relation of -0.297 with CapitalRatio and positive relations of 0.272 with DividendYield, of 0.251 with StockPrice and deltaWealth of 0.370. Accumulated_Option has only positive relations with percOptions of 0.136, 0.232 with Size, 0.148 with Growth, 0.203 with StockPrice and 0.215 with deltaWealth. percOptions has a positive relation of 0.122 with Growth and a negative relation of -0.101 with DividendYield. Size has a negative relation with CapitalRatio of -0.567 and positive relations with 0.405 with DividendYield, 0.350 with StockPrice and 0.510 with deltaWealth. CapitalRatio has a positive relation with Growth of 0.219 and a negative relation of -0.291 with DividendYield, of -0.124 with StockPrice. Growth has a negative relation with DividendYield of -0.173 and positive relations of 0.214 with StockPrice and 0.213 with deltaWealth. DividendYield has positive relations with StockPrice of 0.422 and with deltaWealth of 0.114. StockPrice has a positive relation with deltaWealth of 0.244.

21

4 Results

4.1 Backdating Sample

The table below represents the ordinary least square regression to answer the first hypothesis. Beta, sdreturns and sdresiduals are the three risk measures and dependent variables in the regression. Within brackets, the standard deviation of the above number is mentioned. During the timeframe, the research has conducted 38 observations. The table displays a R-squared and an adjusted R-squared value to measure the proportion of the variation in the dependent variable. The p-value of the F-statistic is shown as p(F) to demonstrate the statistical

significance. Heteroscedasticity has been found in this in this test, since p<0.01 in all three risk measurements. The Shapiro-Wilk test is used to check whether the dataset came from a normally distributed database.

(INSERT TABLE 10 HERE)

The independent variables affect the dependent variables, which are the three risk measures. percOption has a positive correlation of 0.0107 with beta, which indicates that beta rises by 10.7% each time percOption would rise by 1. However, unfortunately this is not statistically significant. Size has a positive relation of 3.61% to the beta, which tells us that firm riskiness would improve with the size of the firm. This would entail that larger firms are more prone to a large shareholder reaction when a chief executive has backdated stock options. CapitalRatio has a relation with beta of -17.53%, which is a strong sign that the firm riskiness decreases when the shareholders’ equity increases compared to the firm’s total assets. Therefore, a loss of equity will increase firm riskiness, which would be logical because the capital structure would be more leveraged when that occurs. DividendYield has a positive relation of 10.38% with the beta, implying that when dividend yield increase the firm riskiness will go up. An explanation for this would be that the lower amount of retained earnings on the balance sheet causes more insecurity for the continuity of the firm. The constant is influencing the beta with 1.5308, which indicates that the firm risk on the long term is overestimated and that the returns of the stock are higher than those of the market. Accumulated_Option has a negative relation of 0.07% with sdreturns, stating that the standard deviation of stock returns will lower when Accumulated_Option package will increase. Thus, even though

22 Accumulated_Option will increase volatility, the range between which the stock will move will be smaller. Size has a positive relation of 0.24% with sdreturns, which indicates that a growth in Size will increase the standard deviation of the volatility of the stock returns and thus increase risk. The reason for this could be that more shareholders have been buying into the stock, since firms with higher Size generally have more shares traded compared to firms with moderate Size. DividendYield has a negative rlation of -0.05% with sdreturns,

indicating that stock volatility will decrease when dividend yields increase. This is in line with previous experience, since stocks that pay out more of their earnings are perceived as safer by investors. Constant has a relation of 0.0173 with sdresiduals. Unfortunately, these results have been compromised due to heteroscedasticity.

In the first column of the table, lnAccumulatedOption is positive and significant (0.009, p<5%). An increase of the accumulated options resulted on average in higher market beta for the backdating firms’ sample. For the remainder of the relations no conclusions could be drawn. LnAccumulatedOptions has a 0.9% positive relation with beta, concerning a 5% significance level. This entails that the risk of a firm will slightly increase when the total stock options granted of the chief executive will rise. Size has a negative relation of -3.6% with beta, implying the firm riskiness decreases as the size of a firm grows. This implies that volatility of stock return will be lower for larger firms, which is logical considering firms of a considerable size with lower growth rates have a higher chance of continuity than smaller firms or even high-growth firms. CapitalRatio has a negative impact on beta of -17.5% at a 5% significance level, therefore stating the volatility will be reduced when shareholders’ equity rises. Concluding, a strong capital structure with low leverage is valued higher by shareholders, which is noticeable in the lower volatility. DividendYield has a 10.4% positive influence on beta, which states that when dividend yield rises, the firm riskiness rises as well. Considering these firms have engaged in stock option backdating, a higher dividend yield would imply a stronger relation with share prices and therefore the impact on share will be higher when stock option backdating is reported. This is coherent with previous literature, which proved the incentive based compensation would increase firm risk by chief executives enhancing the risk profile of the firm. LnAccumulatedOptions has a negative relation with sdreturns of -0.1% at the 10% significance level, therefore implying a very weak influence of a higher amount of dollar value in options to firm riskiness. CapitalRatio has a positive influence of 1.0% on sdreturns, also at the 10% level. The influence CapitalRatio has on

23 sdreturns stands in contrast with the relation the variable has on beta, which is much stronger and positive. DividendYield has a negative relation on sdreturns of -0.5% at the 10%

significance level, which is too weak of an influence to lower the impact DividendYield has on beta. Only the constant has a significant influence on the sdresiduals, which entails 1.7% at the 10% level. The standard errors of the parameters are corrected for heteroscedasticity and are thusly more accurate for predicting firm riskiness.

4.2 Control Group Sample

The table below represents the ordinary least square regression to answer the second hypothesis. Beta, sdreturns and sdresiduals are the three risk measures and dependent variables in the regression. Within brackets, the standard deviation of the above number is mentioned. During the timeframe, the research has conducted 801 observations. The table displays a R-squared and an adjusted R-squared value to measure the proportion of the variation in the dependent variable. Heteroscedasticity has been found in this test, since p<0.01 in (2)sdreturns and (3)sdresiduals. The p-value of the F-statistic is shown as p(F) to demonstrate the statistical significance. According to the regression results for the control group firms sample, the percOptions of total compensation did not have effect on any of the risk measures, considering a 5% significance level. The increase of Accumulated_Options lead to significant decrease in the risk of the backdating firms through its influence on beta of -0.21% at the 5% significance level, if risk is proxied by standard deviation of the firm stock returns and also on the standard deviation of the market model residuals, where beta is -0.19% at the 5% significance level. The first risk measure, the market beta, leads to insignificant results. The number of observation for all specifications is 801, whereby all three models are significant, concluded from the significant F-statistic (p<5%). The explanatory power of the first (second) model is the lowest (highest) amongst the three models, viz. 0.018 (0.034) before the correction for heteroscedasticity. The normality of the residuals for all models is rejected (Shapiro-Wilk p statistic<5%). The heteroscedasticity for second and third specifications is significant (p<5%). These specifications have standard errors that are corrected for heteroscedasticity by robust standard errors.

24 What immediately strikes is that the explanatory power of the models has increased due to correction of the standard errors and by estimating the model with firm and year fixed effects. The R-squared are 0.043 for beta, 0.196 for standard deviation and 0.182 for sdresiduals. Obviously, all models have a significant F-statistic at the 5% significance level. If specification one and three is inspected, none of the option remuneration variables are significant. In the second specification, lnAccumulatedOptions is significant with a -0.47% influence on sdreturns and a -0.41% influence on sdresiduals with a 5% significance level. This is depicting the negative relation between accumulated option and the firm risk proxied by standard deviation of stock returns. High option value in the CEO package leads to lower firm risk over the long term for the control group.

4.2 Peer Model

In the third hypothesis, a comparison is created to create the impact of stock option

backdating on the peer group. The peer group is constructed by creating a match between the industry group and event year from the firms from the control group. In total, there is a three year impact for the control group firms, since an extra data was added to the number of event years. Backdated is a dummy variable, with the value 1 for the event date itself, which is the backdating year and 0 for the 2 years after the event. The dummy variable describes that, if proven statistically significant, there has been a backdated event in the past two years, which has influenced the volatility of the stock returns of the peer group in which the backdating has taken place. For example, if in 2007 the chief executive of Shell has backdated his stock options, we would see a change in their peer group in (one of the) three risk measures, which indicates that in the years 2008 and 2009 the stock volatility has changed due to stock option backdating in the industry group.

(INSERT TABLE 12 HERE)

In the table above is the dummy ‘backdated’ significant for the models with all three risk measures. The model, which explains market betas, has a negative backdated parameter of - 0.17% on a 5% significance level. On average, within two years after the backdating event, firms in the control group experienced lower average market beta. This picture changes; for the parameters of the returns and sdresiduals. According to the results above, the backdating firms are subject to a significant increase in firm risk measured by betas (0.168, p<1%), and a

25 significant decrease in firm risk measured by sdreturns 0.131, p<1%) and sdresiduals (-0.127, p<1%). A firm’s industry peer – namely the backdated firms - did not show any significant increase or decrease in firm risk (resp. beta of 0.005, -0.001, and -0.001, p>5%). This means that the firms saw their risk decreasing after the event due to the positive betas. However, there is no statistical significance that percOption or Accumulated_Option has had an influence. Therefore, we can see that, after stock option backdating has occurred at a competitor’s firm, the peer group has not responded by increasing its options as a percentage of the total compensation package.

5 Conclusions

5.1 Main Conclusions

According to the regression results, the backdating firms sample show a decreased riskiness of the firm if the remuneration of the CEOs – proxied by the percentage of options in the package - had decreased. The relation remains the same for the control group sample. An increase in the accumulated options remuneration, decreased the riskiness of the control groups’ firms significantly. First sample results suggest it is not evident that CEOs

undertaking stock option backdating frauds, did not cause the increase of firm riskiness. After all, an increase of their remuneration package, measured by the option value, did not reveal a positive relation. The same results rule for the control group sample.

The hypotheses of this thesis could be answered as follows:

H1: CEO stock option backdating resulted in the increase of firm riskiness, when higher stock options were added to their remuneration plan.

This hypothesis is accepted, however with caution, since the number of observations is too low for the backdating sample to generalize.

26 H2: CEOs who did not undertake stock option backdating did not increase the firm riskiness, when higher stock options were added to their remuneration plan.

This hypothesis is accepted. Higher option values and distributions lead to lower firm risk.

H3: There is a positive relation between the stock option backdating by a firm and the stock return volatility of its peer group in the same year.

This hypothesis is accepted. We saw for the total control group sample as well as for the specific industries, which the risk after the backdating event had increased significantly within two years.

5.2 Limitations & Further Recommendations

The results in this research are not completely tested for robustness to other statistical shortcomings of the current models. For instance one could incorporate the correlation of external factors with the exogenous variables, which are not correlated with the current risk measures. This would correct for endogeneity of the models and circumvent the biasedness and causal relations that would alter the accuracy of the parameter estimates. The

econometric models should be chosen, carefully after an elaborate investigation to potential omitted factors that would cause the riskiness of the firms. Omitted variables, may in same manner have a detrimental impact on the unbiasedness of the model estimates. The industry peer groups are constructed by means of the 2-digit SIC codes, which may be a too stringent method, that may deteriorate the peer group model estimations. Or, the effects of the peer group from the backdated group, could in this manner hardly differentiated from each other. One should divide the firms over a much detailed industry sub categories.

27

References

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28 executive stock option grants?’ Journal of Financial Economics 83 (2007) 271–295

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29

Appendix

Summary Statistics

Table 1: Summary Statistics Backdating group.

Table 2: Summary Statistics Control group.

Count Mean SD Median Min Max p10 p25 p75 p90

Betas 1807 1.000 0.003 0.998 0.997 1.004 0.997 0.997 1.002 1.004 Sdreturns 1807 0.161 0.043 0.141 0.121 0.235 0.123 0.126 0.185 0.235 Sdresiduals 1807 0.151 0.040 0.130 0.117 0.222 0.119 0.121 0.169 0.222 Options 1782 1451.685 4312.097 579.010 0.000 90693.400 0.000 0.000 1712.051 3372.701 TotalCompensation 1781 5898.812 6670.622 4042.465 0.000 96160.696 1010.393 1976.283 7769.976 12436.161 Accumulated_Option 1806 8935.552 28856.243 1548.758 0.000 617991.400 0.000 8.597 6913.830 21931.244 PercOptions 1779 0.194 0.185 0.167 0.000 0.534 0.000 0.000 0.328 0.523 Size 1806 7.679 1.533 7.499 5.524 10.985 5.640 6.462 8.658 9.982 CapitalRatio 1436 0.522 0.213 0.533 0.097 0.829 0.207 0.368 0.709 0.818 Growth 1476 0.277 0.384 0.217 -0.262 1.161 -0.201 0.001 0.480 0.876 DividendYield 1804 0.341 0.503 0.000 0.000 2.080 0.000 0.000 0.550 1.135 StockPrice 1804 31.601 20.214 26.920 7.930 91.710 8.990 16.215 42.775 60.030 DeltaWealth 1164 213.636 522.613 62.121 -556.100 1768.000 -153.200 -5.726 270.494 849.000

Count Mean SD Median Min Max p10 p25 p75 p90

Betas 124 1.381 0.244 1.284 1.143 2.010 1.177 1.210 1.561 1.814 Sdreturns 124 0.028 0.006 0.027 0.021 0.043 0.023 0.026 0.030 0.035 Sdresiduals 124 0.025 0.004 0.024 0.019 0.034 0.021 0.022 0.027 0.029 Options 95 1050.834 1728.098 0.000 0.000 9409.277 0.000 0.000 1535.561 3042.000 TotalCompensation 95 6838.235 5590.694 6380.906 0.001 30165.992 19.093 2577.022 9606.187 14856.321 Accumulated_Option 124 57023.474 205753.191 3402.340 0.000 1601658.510 0.000 0.000 24067.685 77813.475 PercOptions 95 0.167 0.238 0.000 0.000 0.871 0.000 0.000 0.291 0.479 Size 124 8.289 1.571 8.181 4.407 12.354 6.561 7.041 9.071 10.838 CapitalRatio 106 0.598 0.178 0.627 0.147 0.875 0.345 0.502 0.739 0.819 Growth 78 0.630 0.935 0.310 -0.834 4.489 -0.240 0.088 0.900 1.900 DividendYield 124 0.422 1.106 0.100 0.000 11.400 0.000 0.000 0.535 1.000 StockPrice 124 54.420 82.064 36.260 6.710 667.105 15.365 22.125 53.480 87.890 DeltaWealth 85 1518.452 5999.936 187.194 -12002.000 41595.000 -155.518 18.321 670.568 2518.000

30

Frequencies

Table 3: Frequencies industries backdating group.

Sector Count Percentage (%) Cumulative Percentage (%)

Construction 12 9.68 9.68

Finance 16 12.90 22.58

Manufacturing 72 58.06 80.65

Services 24 19.35 100.00

Total 124 100.00

Table 4: Frequencies years backdating group.

Year Count Percentage (%) Cumulative Percentage (%)

2003 8 6.45 6.45 2004 9 7.26 13.71 2005 9 7.26 20.97 2006 7 5.65 26.61 2007 9 7.26 33.87 2008 10 8.06 41.94 2009 12 9.68 51.61 2010 13 10.48 62.10 2011 12 9.68 71.77 2012 12 9.68 81.45 2013 12 9.68 91.13 2014 11 8.87 100.00 Total 124 100.00

Table 5: Frequencies industries control group.

Sector Count Percentage (%) Cumulative Percentage (%)

Construction 37 2.05 2.05 Finance 174 9.63 11.68 Manufacturing 1129 62.48 74.16 Public 3 0.17 74.32 Services 464 25.68 100.00 Total 1807 100.00

Table 6: Frequencies years control group.

Sector Count Percentage (%) Cumulative Percentage (%)

2006 103 5.70 5.70 2007 306 16.93 22.63 2008 333 18.43 41.06 2009 355 19.65 60.71 2010 309 17.10 77.81 2011 245 13.56 91.37 2012 156 8.63 100.00 Total 1807 100.00

31 Table 7: distribution of the backdated and peer group firms.

Dummy variable Observations Percentage

Backdated 0 1915 99.17 1 16 0.83 Total 1931 100.00 Peer 0 937 48.52 1 994 51.48 Total 1931 100.00

32

Correlations

Table 8: Correlations Backdating group.

betas sdreturns sdresiduals Options Total Compensation

Accumulated Option

percOptions Size CapitalRatio GROWTH Dividend Yield

StockPrice

betas 1

sdreturns -0.0803 1

sdresiduals 0.101 0.949*** _{1 Significance levels} * _{p < 0.05,} ** _{p < 0.01,} *** _{p < 0.001}

Options 0.206* _{0.0157 0.0212 1} TotalCompensation 0.110 -0.166 -0.164 0.180 1 Accumulated_Option 0.239** _{-0.0767 -0.0289 0.542}*** _{0.0964 1} percOptions 0.219* _{0.0684 0.0785 0.812}*** _{-0.0713 0.323}** ₁ Size -0.119 -0.0762 -0.0936 -0.0251 0.286** _0.252** _-0.281** ₁ CapitalRatio 0.183 -0.0266 0.00171 -0.00464 -0.0981 0.0524 0.0438 -0.266** ₁ GROWTH 0.299** _{-0.0531 -0.0197 -0.0540 -0.299}** _{0.164 0.138 0.0768 0.313}** ₁ DividendYield -0.0867 -0.134 -0.103 -0.139 0.0335 -0.0825 -0.180 0.373*** _{-0.0570 0.0505 1} StockPrice -0.00901 -0.108 -0.0863 -0.111 -0.124 0.0294 -0.154 0.524*** _{0.0505 0.427}*** _0.554*** ₁ deltaWealth -0.0385 0.0549 0.0462 -0.135 -0.223 -0.0757 -0.147 0.436*** _{0.0896 0.441}*** _{0.133 0.844}***

33 Table 9: Correlations Control group.

betas sdreturns sdresiduals Options Total Compensation

Accumulated Option

percOptions Size Capital Ratio GROWTH Dividend Yield StockPrice betas 1 sdreturns -0.572*** ₁

sdresiduals -0.544*** _0.997*** _{1 Significance levels} * _{p < 0.05,} ** _{p < 0.01,} *** _{p < 0.001}

Options 0.00933 -0.0143 -0.0156 1 TotalCompensation 0.0170 -0.0675** _-0.0720** _0.766*** ₁ Accumulated_Option 0.0728** _-0.0910*** _-0.0854*** _0.528*** _0.477*** ₁ percOptions 0.00359 0.00613 0.00925 0.356*** _0.127*** _0.136*** ₁ Size -0.0306 0.000608 -0.00160 0.281*** _0.605*** _0.232*** _{0.0407 1} CapitalRatio 0.0707** _{-0.0443 -0.0412 -0.0696}** _-0.297*** _{-0.00576 0.0498 -0.567}*** ₁ GROWTH 0.0925*** _-0.164*** _-0.153*** _0.0889*** _{0.0361 0.148}*** _0.122*** _{-0.0351 0.219}*** ₁ DividendYield -0.00731 -0.0334 -0.0346 0.0384 0.272*** _{0.0254 -0.101}*** _0.405*** _-0.291*** _-0.173*** ₁ StockPrice 0.115*** _-0.148*** _-0.141*** _0.0879*** _0.251*** _0.203*** _{0.0227 0.350}*** _-0.124*** _0.214*** _0.422*** ₁ deltaWealth -0.0230 0.0338 0.0410 0.218*** _0.370*** _0.215*** _{0.0435 0.510}*** _{-0.0492 0.213}*** _0.114*** _0.244***

34

OLS Regressions

Table 10: OLS regression backdating group sample, corrected for heteroscedasticity.

(1) (2) (3)

Dependent variable Risk measures: betas sdreturns sdresiduals

lnAccumulatedOptions 0.0086 -0.0007* -0.0003 (0.004) (0.000) (0.000) percOptions 0.0107 -0.0001 -0.0005 (0.070) (0.003) (0.002) Size -0.0361* 0.0024* 0.0010 (0.018) (0.002) (0.001) CapitalRatio -0.1753** 0.0098** 0.0041 (0.027) (0.001) (0.001) GROWTH 0.0292* 0.0004 0.0002 (0.0157) (0.0010) (0.0008) DividendYield 0.1038*** -0.0050** -0.0022 (0.028) (0.003) (0.002) StockPrice 0.0000 -0.0001 -0.0000 (0.001) (0.000) (0.000) deltaWealth 0.0000 -0.0000 -0.0000 (0.000) (0.000) (0.000) Constant 1.5308*** 0.0117 0.0173** (0.138) (0.012) (0.009) Observations 38 38 38 R-squared 0.441 0.301 0.146 adj. R-squared 0.2867 0.1083 -0.0902 F-statistic 2.8593 1.5616 0.6174 p(F) 0.0179 0.1799 0.7561

Heteroscedasticity accepted? Yes Yes No

Heterosc Test: chi2(1) 5.9311 10.6613 2.9691

Heterosc Test: P(chi2(1)) 0.0149 0.0011 0.0849

Corrected for heteroscedastic errors Yes Yes Yes

Shapiro-Wilk Normality Statistic 0.6828 2.2178 0.6396

Shapiro-Wilk p-statistic 0.2474 0.0133 0.2612

35 Table 11: OLS regression control group sample, corrected for heteroscedasticity.

(1) (2) (3)

Dependent variable Risk measures: betas sdreturns sdresiduals

lnAccumulatedOptions 0.0001 -0.0047** -0.0041* (0.0002) (0.0023) (0.0022) percOptions 0.0003 0.0068 0.0048 (0.0013) (0.0168) (0.0159) Size 0.0015** -0.0216** -0.0231*** (0.0006) (0.0096) (0.0088) CapitalRatio -0.0012 0.0406 0.0369 (0.0020) (0.0311) (0.0291) GROWTH 0.0006 -0.0314*** -0.0264*** (0.0004) (0.0071) (0.0066) DividendYield -0.0008* -0.0042 -0.0032 (0.0005) (0.0082) (0.0076) StockPrice 0.0000** -0.0010*** -0.0009*** (0.0000) (0.0003) (0.0002) deltaWealth -0.0000** 0.0000*** 0.0000*** (0.0000) (0.0000) (0.0000) Constant 0.9869*** 0.3803*** 0.3748*** (0.0049) (0.0805) (0.0742) Observations 801 801 801

Within group R-squared 0.043 0.196 0.182

Number of firms 276 276 276

F-statistic 7.9620 15.5079 14.3802

p(F) 0.0000 0.0000 0.0000

Heteroscedasticity accepted? Yes Yes Yes

Heterosc Test: chi2(1) 0.4189 13.2307 18.3094

Heterosc Test: P(chi2(1)) 0.5175 0.0003 0.0000

Corrected for heteroscedastic errors Yes Yes Yes

Shapiro-Wilk Normality Statistic 10.2166 11.8889 12.1673

Shapiro-Wilk p-statistic 0.0000 0.0000 0.0000

36 Table 12: OLS regression testing the relation between firm risk and option variables within 2

years of the backdating event for the total control group sample.

(1) (2) (3)

Dependent variable Risk measures: Betas Sdreturns Sdresiduals

Backdated group -0.0017*** 0.0204*** 0.0201*** (0.0002) (0.0028) (0.0026) lnAccumulatedOptions 0.0001* -0.0021*** -0.0020** (0.0001) (0.0008) (0.0008) percOptions -0.0000 0.0099 0.0087 (0.0006) (0.0078) (0.0074) Size 0.0000 0.0016 0.0015 (0.0001) (0.0014) (0.0013) CapitalRatio 0.0006 0.0003 -0.0000 (0.0006) (0.0087) (0.0082) GROWTH 0.0003 -0.0090** -0.0069* (0.0003) (0.0041) (0.0038) DividendYield -0.0001 -0.0030 -0.0026 (0.0002) (0.0028) (0.0026) StockPrice 0.0000 -0.0001 -0.0000 (0.0000) (0.0001) (0.0001) deltaWealth -0.0000* 0.0000 0.0000 (0.0000) (0.0000) (0.0000) Constant 0.9994*** 0.1496*** 0.1394*** (0.0010) (0.0139) (0.0130) Observations 801 801 801 R-squared 0.100 0.104 0.106 adj. R-squared 0.0901 0.0933 0.0963 F-statistic 11.2633 9.7036 10.0599 p(F) 0.0000 0.0000 0.0000

37 Table 13: OLS regression testing the relation between firm risk and option variables for the

backdated, peer and control group sample.

(1) (2) (3)

Dependent variable Risk measures: Betas Sdreturns Sdresiduals

Backdated group 0.168*** -0.131*** -0.127*** (0.026) (0.031) (0.030) Peer group 0.005 -0.001 -0.001 (0.007) (0.002) (0.002) lnAccumulatedOptions -0.001 0.001 0.001 (0.002) (0.001) (0.001) percOptions -0.006 0.002 0.002 (0.019) (0.007) (0.006) Size 0.002 -0.002 -0.002 (0.002) (0.001) (0.001) CapitalRatio 0.021 -0.012* -0.012* (0.016) (0.007) (0.006) GROWTH 0.025 -0.003 -0.003 (0.018) (0.003) (0.003) DividendYield 0.006 -0.000 -0.001 (0.006) (0.002) (0.002) StockPrice -0.000 0.000 0.000 (0.000) (0.000) (0.000) deltaWealth 0.000 -0.000 -0.000 (0.000) (0.000) (0.000) (0.024) (0.008) (0.008) Constant 1.313*** 0.037*** 0.035*** (0.025) (0.012) (0.012)

Industry Fixed Effects Yes Yes Yes

Year Fixed Effects Yes Yes Yes

Observations 839 839 839

R-squared 0.396 0.831 0.827

adj. R-squared 0.380 0.827 0.822

F-statistic 2171.940 12178.023 11426.299

p(F) 0.000 0.000 0.000