Why Do Insiders Hedge Their Ownership? An Empirical Examination*

Carr Bettis Arizona State University and Gradient Analytics

John Bizjak Texas Christian University

Swaminathan Kalpathy Southern Methodist University

This Draft: May 2011

* The authors thank participants at the 2010 FMA European Conference in Hamburg, Germany, participants at the 2010 American Law and Economic Association meetings in Princeton, participants at the 2010 FMA meetings in New York, seminar participants at Arizona State University, Southern Methodist University, Texas Christian University, Texas Tech University, and University of Oregon for helpful comments. The authors thank Lucian Bebchuk, Jeff Coles, Huasheng Gao, Mike Lemmon, Ebru Reis, and David Yermack for their helpful comments and suggestions. The authors are thankful to Emmelin Cardella for her excellent research assistance.

Electronic copy available at: http://ssrn.com/abstract=1364810 Why Do Insiders Hedge Their Ownership? An Empirical Examination

Abstract

We analyze four different instruments – collars, forwards, exchange funds and equity swaps – used by corporate insiders to hedge or diversify their ownership in order to better understand why these instruments are used and how they impact managerial incentives and behavior. Insiders hedge over a third of their ownership with collars, forwards and equity swaps which significantly reduces pay-performance-sensitivity, but they hedge much less ownership with exchange funds. The use of collars and forwards, but not exchange funds, precedes poor stock performance and adverse corporate events indicating opportunistic timing by insiders. Our analysis also indicates that insiders use these securities to reduce personal taxes and to maintain voting rights prior to certain corporate events. Finally, most corporate boards do not restrict the use of these derivative instruments. Understanding these strategies and how they are used has important implications for both insider trading and incentive contracting.

Electronic copy available at: http://ssrn.com/abstract=1364810 1. Introduction

We provide the most comprehensive analysis to date of how corporate insiders

use different types of derivative securities to hedge or diversify their equity holdings of

stock and options in their firm. According to SEC filings the most common derivative

instruments used by insiders are: pre-paid variable forwards (forwards), zero-cost collars

(collars), exchange trusts, and equity swaps. Forwards and collars are similar instruments that allow insiders to protect themselves from downside movement in the firm’s stock price while retaining the opportunity to benefit from stock price appreciation, deferring income taxes, and maintaining voting rights. Exchange trusts, also known as exchange funds, are portfolios of securities formed when insiders from different companies contribute their own shares into a portfolio. Equity swaps allow the insider to trade the return on the stock for the return on another security.1

Because these instruments can allow insiders to trade opportunistically ahead of

adverse firm-specific events without the transparency or litigation risk that is typically

associated with open market sales the use of these securities has attracted significant

scrutiny from shareholders and proxy advisors (e.g., Institutional Shareholder Services

and Council of Institutional Investors), regulators (e.g., the Securities and Exchange

Commission) along with legislators (e.g., the Dodd-Frank Act) and academics (Bebchuk

and Fried (2010) and Larcker and Tayan (2010)).2 Another concern with these

instruments is they reduce the sensitivity of an executive’s wealth to firm performance

1 We provide more details about the structure of these instruments in Section 2 and in Appendix A. 2 We discuss below how these contracts are reported and the reasons they are harder to identify than an insider sale.

3 which affects the incentives of executives to increase shareholder value and can

exacerbate agency problems in the firm.

While the potential use of these securities to exploit private information raises

concerns, there are rational economic reasons for why insiders would use these

instruments. Insiders often have significant holdings of stock and options and can use

these securities to reduce personal portfolio risk associated with concentrated holdings of one asset. The other advantages of these securities relative to an open market sale include deferring personal income taxes, maintaining some of the upside gain in share price, and maintaining voting and dividend rights on the underlying shares.

Diversification at the personal level could also prevent costly hedging and investment distortions at the firm level (Amihud and Lev (1981), Stulz (1984)). In addition, derivative securities might allow an otherwise risk-averse executive to bear more firm- specific risk and thereby take on risky, yet value-enhancing projects for shareholders.

Beginning in 1996 Primark/Disclosure (now part of Thomson Reuters) began collecting all of the hedging and diversification transactions that appear in Table II of forms 3, 4, and 5 (most of which are revealed in footnotes to the tables). We gather information on these transactions reported by corporate insiders over a ten-year period starting in January of 1996 through December of 2006 from the Thomson Reuters database and augment this with hand-collected data from our own keyword searches of

SEC filings. We compile a sample of over 2,000 hedging transactions initiated by over

1,000 insiders at almost 600 unique firms. To our knowledge this is the most comprehensive data set gathered on these types of transactions.

4 Given a lack of comprehensive information about the different types of derivative strategies available to insiders, our first objective is to provide some basic facts about the types of hedging and diversification strategies that are used, their fundamental

characteristics, the frequency of their use, their evolution over time, and the amount of ownership covered. Our second objective is to provide an understanding of what

motivates insiders to hedge, if there are reasons to use one instrument versus another

(e.g., forward versus exchange funds) and the implications of the use of these securities

for insiders, shareholders, and the firm.

With regard to our first objective, we document a recurrent use of three particular

types of transactions - collars (481), pre-paid variable forwards (983), and exchange

funds (442). Equity swaps (136) are less frequently used. The data reveal that a diverse

group of corporate insiders engage in these transactions and include CEOs and Chairmen

of the Board (380), other senior officers (363), non-officer directors (239) and 10%

beneficial owners (158). We find that CEOs tend to use exchange funds more frequently

while upper level managers tend to use collars and forwards more often. Equity swaps

appear to be more prevalent among 10% beneficial owners. In our sample the average

level of ownership hedged with collars (31%), forwards (28%), and swaps (33%) are

quite similar and significantly larger than the average open-market insider sale

(Lakonishok and Lee (2001)). In contrast, we find significantly lower levels of

ownership placed in exchange funds (9% on average).

In terms of our second goal of understanding the motivation behind the use of

these different instruments the results of our empirical analysis suggest that insiders time

their use collars and forwards based on inside information. For collars (forwards) we

5 find cumulative abnormal returns of 43% (22%) in the year prior to the transaction

compared to an industry-size matched control firm which is then followed by an

abnormal return of –19% (–7%) the year following the transaction. These abnormal

returns are larger than what has been documented in prior research for insider sales

(Seyhun (1992) and Lakonishok and Lee (2001)). We also find evidence of poor performance following equity swaps but we are cautious about interpreting this finding

due to the small sample size.

Further bolstering the timing story is our evidence that collars and forwards are

followed by shareholder securities-based litigation, earnings restatements, and negative

earnings surprises (for collars) in the year subsequent to the transaction – activities that

are traditional associated with poor firm performance. We also find that forwards are

frequently used by insiders in an acquiring firm prior to the announcement of an M&A

transaction. A potential explanation for this latter finding is that insiders want to keep

voting rights to influence the deal but protect themselves from any downside risk.

In contrast, the use of exchange funds by insiders does not appear to be information based. We do find a run-up in stock price prior to the transaction but find no evidence of poor performance subsequently. In fact, we find a positive 9% abnormal return post transaction. We also do not find evidence that the use of exchange funds is related to shareholder litigation, earnings restatements, or negative earnings surprises the year after the transaction.

Another motivation for the use of these various instruments is as a diversification strategy when insiders are concerned about changes in firm risk. To test this idea we

examine if the frequency of these transactions is associated with corporate events that

6 could change the firm’s risk profile such as a change in CEO, changes in R&D, book leverage, total investments or with increases in stock return volatility. We find no relation between the use of derivative transactions and these events or changes in firm characteristics. An alternative interpretation of these findings is that these instruments do not provide incentives for managers to initiate riskier investment strategies.

Another rational for the use of these securities, with the exception of equity swaps, is to allow insiders to defer income taxes over the contract life which effectively reduces the present value of personal tax liability. Consistent with this idea, we find some evidence that insiders are more likely to use these securities to reduce taxes.

To better understand how these instruments might affect incentives we measure the impact of hedging on pay-for-performance sensitivity of CEOs, and report on related governance characteristics at hedging versus non-hedging firms. To be clear, these experiments lack a theoretical framework to explain why it is optimal to allow insiders to hedge at the personal level to adjust the pay-for-performance sensitivity when boards can structure compensation contracts that would nullify the need for any hedging on the part of the insiders. Similarly, our investigation of firm governance characteristics may be viewed as merely descriptive. What we do find, however, raises some concerns. Collars and forwards reduce the sensitivity of changes in CEO wealth to changes in stock price by about 22% and boards do not appear to reinstate the weakened incentives by making ex-post adjustments to compensation. Indeed boards can mandate and enforce corporate policies that ban or restrict the use of these instruments, but seldom do. In addition, we find that these instruments tend to be used in firms that have characteristics that are traditionally associated with weaker corporate governance. Firms where insiders use

7 these derivatives tend to have fewer independent directors and for forwards lower levels of ownership by 5% institutional investors.

Our analyses suggest that not all derivative instruments are created equal and that

there are important differences in the use of these securities. One reason why the size of

collars, forwards and swaps transactions tend to be larger in magnitude compared to

exchange trusts is because these instruments can be tailored to the individual needs of the

insiders. Moreover, since these three securities provide full protection from any drop in

share price they are more conducive to being used when insiders anticipate poor

performance. In contrast, exchange funds are primarily designed by investment banks as

a diversification strategy for insiders, which suggest that banks have the incentive to limit

the amount that any particular insider can contribute into the fund and to monitor the

quality of stocks selected for inclusion into the fund.

There are three notable papers that precede our work. Bolster, Chance and Rich

(1996) provide a case study on a single equity swap transaction by the CEO of Autotote

in 1994. Bettis, Bizjak and Lemmon (2001) examine 85 zero-cost collars initiated

between 1996 and 1998. Jagolinzer, Matsunaga, and Yeung (2007) study a sample of

200 forward contracts spanning 100 individuals between 1996 and 2004. While this

previous work has addressed some of the issues surrounding the use of some of these

instruments the size and comprehensive nature of our data allow us to provide insight into

a number of issues left unexplored in prior studies. These issues include: the use of these

instruments around material corporate events; whether the use of these instruments affect

managerial behavior; how hedging affects incentive contracting; to what extent personal

8 taxes and voting rights influence the motivation to use these instruments; and to what

extent firms ban insiders from using these instruments.

The paper is organized as follows. Section 2 provides a description of these

securities and the data. Section 3 provides a background for the different motivations

insiders would have to use these securities. Section 4 contains the examination of stock

price performance and corporate events surrounding hedging transactions. Section 5, 6

and 7 provide evidence on the determinants of the use of hedging contracts. Section 8

concludes.

2. Sample Collection and Summary Statistics

2.1 Common Hedging and Diversification Instruments

There are four types of securities reported in SEC filings that insiders can use to

hedge or diversify their equity holdings in the firm. Each type is described briefly here

with more detailed discussion in Appendix A. In a collar transaction the proceeds from

the sale of a call option on the stock are used to buy a put option on the stock. Forwards

represent a forward sale of the firm’s stock. While collars and forwards are different

instruments they share some of the same fundamental characteristics. They both provide

downside protection in stock price (floor), while sacrificing some of the upside return

(ceiling). Also each has a fixed maturity that determines the contract length and both are private over-the-counter transactions between the individual and the investment bank. A major difference between these two instruments is forwards are much easier to monetize than collars (i.e. to receive a cash advance against the shares). In an exchange fund a group of insiders from different firms individually place their shares in a limited partnership or limited liability company. By pooling shares into a single entity the

9 participants receive a return based on the performance of the diversified portfolio. These funds are organized by financial institutions such as investment banks. Equity swaps allow investors to exchange the future returns on their stock for the cash flows of another financial instrument such as a debt instrument (e.g., the cash flows associated with the return of the LIBOR), or any other financial instrument such as the S&P 500.

2.2 Identifying Hedges.

Beginning in 1996 Primark/Disclosure (now part of Thomson Reuters) via its

Lancer Analytics strategic partnership with Gradient Analytics began collecting all of the

hedging transactions that appear in Table II of Forms 4 and 5.3 Our dataset is comprised

of transactions collected by Thomson Reuters, supplemented by additional filings

identified by Verus Research, LLC, and by our own investigation of identified filings.

The quality of reporting for hedging transactions varies widely. Some filings contain the contract details (e.g., contract ceiling and floor values for collars and forwards) but many merely include generic references to the hedging instruments. When details are presented most of them are contained in the footnotes to the filings. When available we collect the type of instrument reported, name of the insider who enters into the transaction, title of the insider, transaction date, number of shares hedged in the transaction, and the length of the contract. For collars and forwards when reported we also gather information on the

3 Prior to 1994 the SEC viewed hedging transaction, at the time mainly swaps and collars, as private deals and not open-market transactions, and therefore did not require insiders to report these transactions (Norris, 1994). In 1996 the SEC formalized their position regarding hedging transactions in release No. 34-347260 (1996) and mandated that these instruments be reported in Forms 4 or 5. Details of these transactions are primarily reported in Table II of those forms.

10 floor and ceiling price and for forwards the cash payment received from monetization of the hedging contract.4

2.3 Sample Statistics.

Table 1 Panels A, B and C provide a description of the frequency of the four

different types of hedging transactions in our sample. Between 1996 and 2006 there were

2,042 unique transactions by 929 unique individuals (for a total of 1,200 individual-

years) that hedged their ownership positions at 582 different firms (for a total of 924 firm-years). For the sample of firms with hedging transactions we gather data on individual position and individual ownership from corporate proxy statements or Forms 3 or 4. Table 1 shows how the use of hedging instruments has generally increased over time, albeit the single largest use occurred in 2000.5 There is also significant time-series

variation in the popularity of each type of instrument. From 1996 through 2000 collars

were the most common. Beginning in 2001 forwards replaced collars as the most popular hedging instrument. One potential reason for the increased popularity of forwards is that

they are easier to monetize than collars and they allow insiders to raise more cash than with a collar. The majority of investments in exchange funds appear to be clustered in

1999 and 2000 with a significant reduction in subsequent years. This may reflect an aggregate sentiment about the market by insiders but also may be a function of the number of transactions that could be structured by the investment banks, who are not

4 For collars, in particular, the amount of cash received if the transaction is monetized is rarely reported in the filing. 5 Seyhun (1988) shows that on average shifts in the aggregate insider purchase to sales ratio is a leading indicator of general market increases or decreases. We do not investigate whether aggregate insider hedge transactions are also in an indicator of general market declines, but we speculate that the surge in hedging activity in 2000 may be because insiders became concerned about the run up in equity values prior to the stock market downturn that began in late 2000.

11 likely to offer these funds every year. Panels B and C show similar patterns when

looking at the use of derivatives at both the individual and firm level.6

Table 2 provides summary statistics on the amount of ownership hedged by each

type of instrument. In reporting the details in Table 2, we aggregate the transactions used

by a certain insider in a given year since it is not uncommon for insiders to engage in

multiple transactions in a calendar year and because we are interested in examining the

economic magnitude of these transactions. Panel A shows the percentage of ownership

hedged and the dollar value hedged on average by insider-year. On average insiders

hedge a significant amount of ownership when they engage in a collar, forward, or swap

transaction. Insiders using collars, forwards or swaps all hedge about 30% of their

ownership in the firm. All three have a significantly larger percentage of ownership

hedged than exchange funds, where on average insiders’ hedge approximately 9% of

their ownership. As discussed previously, among other reasons, the relatively smaller

size of exchange fund transactions may be attributed to investment banks limiting the

amount of equity that can be contributed by each insider in the investment pool.

Panel B of Table 2 provides evidence on the position of the individual who initiates the hedging transaction. All transactions types are used by a diverse group of insiders although there is cross-sectional variation by derivative type and insider position.

Exchange funds are used by a higher proportion of CEOs/Chairmen of the Board (41%) while collars tend to be more concentrated in lower level firm executives (39%).

6 Of course we do not know if these patterns are a result of changes in the use of these instruments or are more a function of attitudes regarding the reporting of these securities. We speculate, however, that even if reporting is incomplete there should be a strong correlation between the use and reporting of these securities.

12 Forwards are more evenly spread across the different insider groups. The use of equity

swaps is most frequent among outside 10% blockholders (58%).

Table 3 contains statistics on the structure of collar and forward agreements that

illustrate some distinct differences. On average, collars provide insiders with more

upside share price gain than forwards. The average (median) stock price appreciation the

investor retains with a collar is 55% (36%), compared to 33% (29%) for forwards. In

contrast, insiders sacrifice more downside share price loss before the collar’s hedge takes

effect. Specifically for collars the stock price would have to fall an average (median) of

14% (10%) before receiving downside protection. For forwards the floor is very close to

(or the same as) the stock price at the transaction date. The stock price would have to fall

an average (median) of 7% (1%) of the stock price on the transaction date before the

forward starts providing downside protection to the insider. In general, collars and

forwards have very similar contractual lengths of about 2.8 years. Table 3 also provides

data on the dollar amount monetized by the forward transactions. On average, insiders

receive $13 million in cash associated with the agreement while the median amount of

cash associated with the transaction is $3.4 million.

Overall the data indicate that insiders hedge or diversify a significant fraction of

their ownership position, in particular with collars, forwards and swaps. When using a

collar or forward agreement they also maintain a significant amount of potential for future share price appreciation. Given the median contracts are approximately three years in length and the median ceiling-to-price ratio is approximately 1.3, insiders maintain the potential to retain an appreciation of 9.14% annually over the life of the

13 contract. At the same time both collars and forwards provide insiders with a hedge

against most of the risk associated with stock price decline.

As already noted one advantage of our study is the comprehensive nature of our

data – both in the cross-section and in the time-series. Bettis et al (2001) examined a

sample of 85 zero-cost collars between 1996 and 1998. While Jagolinzer et al (2007)

examined forward contracts over a longer time period, one potential drawback of their

study is that they are limited to forward contracts that were filed electronically which misses a significant number of forwards and underestimates their use. For example, using just keyword searches of forms 3, 4, and 5, Jagolinzer et al (2007) identify 74 forward transactions between 1996 and 2004. In contrast, we identify six times as many

forward transactions, 444, over that same time period. The primary reason for the

discrepancy is that prior to June 2003 only a minority of insiders filed these transactions

electronically.7 Pursuant to their strategic partnership with Gradient Analytics via Lancer

Analytics, Thomson Reuters manually examined all the Table II filings prior to 2003 in order to identify the various types of hedging transactions.8

Our data set enables us to provide a better picture of how prevalent these instruments are, how they have evolved over time, and what type of executives use these securities. We start by revisiting and extending some of the analysis done in prior work but note that some of our results differ from previous studies. We also, however, go well beyond merely applying different methodology and more complete data to questions

7 The SEC’s final rule which was adopted on May 7, 2003 requires electronic filing of Forms 3, 4, and 5 that are filed after June 20, 2003. 8 We recognize that while we have attempted to identify all hedging transactions our sample may underestimate the total amount of hedging by corporate insiders in particular if insiders to not report these transactions. The SEC has repeatedly and unequivocally stated that insiders are required to report transactions in derivative instruments.

14 addressed in prior work. For example, we compare to what degree these securities

substitute for one another or if they are unique instruments with different implications for executives or shareholders. And, we examine some issues not comprehensively addressed or not addressed at all in prior research. For example we investigate the use of these instruments around material corporate events, whether the use of these instruments affect managerial behavior, how hedging affects incentive contracting, to what extent personal taxes and voting rights influence the motivation to use these instruments, and to what extent firms attempt to preclude insiders from using these securities.

3. Insiders’ Motivation to Hedge

3.1 Why hedge?

In this section we discuss hypotheses for what motivates an insider to use one of these derivative instruments. We focus on two particular reasons. The first is the ability to exploit private information about future performance. The second, involves other economic rational which are primarily driven by the need for diversification of equity- related wealth in the firm.

3.1.1 Informational hedging and changing incentives. Several studies suggest that managers use private information in the timing of their decisions to buy and sell equity in the firm (e.g., Seyhun (1986), Lakonishok and Lee (2001)), or in the grants of stock options (e.g. Yermack (1997), Aboody and Kasznik (2000)). Similar to insider sales, hedging and diversification strategies also provide an opportunity for insiders to trade on

private, value-relevant information about future firm performance. Moreover, these securities have several characteristics that provide an advantage to trading on inside

15 information relative to a typical insider sale. First, these transactions tend to be more

opaque relative to selling equity because they only appear on Table II of Form 4 while an open market sale appears on Table 1 of Form 4. Table II data is not as widely disseminated to shareholders through most commercial sources as the data on insider trades derived from Table I. In addition, these transactions typically appear in the footnotes to these filings making manual inspection of filings necessary to identify the transactions (this is a particular problem before electronic filing became mandatory in

2003). Second, these transactions do not affect managerial ownership reported in the proxy statement which also contributes to the lack of transparency of these securities. In contrast, an open market sale of securities directly affects the insider’s ownership that is disclosed in that year’s annual proxy statement. Third, unlike an open market sale these transactions typically allow the insiders to keep both the voting rights and dividends associated with the shares. Finally, case law surrounding the use of derivative securities is less developed than the case law associated with insider stock sales. Consequently, insiders have incentive to be more aggressive in using these securities based on inside information.9 If these securities are used by insiders to profit from inside knowledge of

future firm performance we expect the following.

H1: Insider’s use of a derivative security is associated with poor firm performance following the transaction. Moreover, the use of derivative securities by insiders is more likely to occur around material corporate events that have a negative impact on firm performance such as shareholder litigation, earnings restatements, or negative earnings surprises.10

9 To date there have been no enforcement actions by either the SEC or other agency that is directly related to an insider using a derivative instrument to trade on inside information that was not tangential to other issues that were the target of the enforcement action. (Source: Business week article, ‘Some CEOs are Selling Their Companies Short,’ February 25, 2010). 10 Bhagat, Bizjak and Coles (1998) find negative abnormal stock returns around the announcement of shareholder initiated lawsuits. Palmrose, Richardson, and Scholz (2004) find a negative stock market reaction associated with earnings restatements while Li and Zhang (2006) find evidence of informed trading by insiders around restatements. Ke, Huddart, and Petroni, (2003) find evidence that insider trading

16

As anecdotal support of the above hypothesis, in 2005 Maurice “Hank”

Greenberg, the former CEO of AIG, used a variable forward contract to hedge and

monetize 4.42 million shares of AIG stock worth at the time almost $300 million. He

closed the hedging transaction in 2008 by delivering the same number of shares which had declined in total value to $8.4 million for a net savings of over $280 million. In

February 2008 AIG agreed to settle securities fraud charges related to improper accounting with the Securities Exchange Commission (SEC). Several executives at

Krispy Kreme engaged in a series of hedges in the two years prior to their bankruptcy, earnings restatements, and SEC settlement for securities fraud.11

We note that since exchange funds are established primarily by investment banks that have discretion over who they allow to invest in these funds, these banks have an

incentive to prevent insiders from opportunistically contributing stock. Consequently,

insiders may be less likely to be able to use exchange funds to trade opportunistically on

inside information.

Another aspect of derivative instruments is that they reduce the sensitivity of the

value of equity holdings to changes in stock price thereby altering managerial incentives.

Moreover, these instruments separate cash flows rights from voting rights which may further exacerbate the agency problem between insiders and stockholders (Lease,

McConnell, and Mikkelson (1983)). If derivative use weakens equity incentives, in particular for the managers of the firm, it is more likely that these instruments will be

is associated with changes in earnings over time with insiders sales becoming more frequent prior to an earnings decline. 11 See ‘Some CEOs are Selling Their Companies Short,’ Business Week, February 25, 2010.

17 used by insiders in firms with weaker corporate governance which leads to the following

hypothesis.

H2: Firms whose insiders’ hedge will have fewer independent directors on the board, lower levels of 5% institutional blockholders, and more frequent CEO/Chair duality.

All of these derivative transactions (including exchange funds, which we

postulate are less likely to be used opportunistically) reduce the sensitivity of wealth to

firm performance and alter the incentives established by the board of directors.

Consequently, if these instruments are used opportunistically it is more likely they will

occur when there is less oversight of their behavior by the board and shareholders. If

these instruments are used purely for diversification or monetization of a concentrated

equity position and not motivated by inside information or to alter incentives we would

not expect their use to be associated with the governance characteristics of the firm. This

is the null for hypothesis H2.

3.1.2 Hedging, diversification, and incentive contracting.

Insiders often have significant holdings of equity along with an investment in firm

specific human capital.12 Consequently, they have an incentive to diversify away some

of the firm-specific risk associated with high levels of ownership and human capital.13 In addition, insiders, for either personal consumption or for diversification purposes, will eventually want to “cash out” or monetize their holdings in firm stock.14 Collars,

forwards, exchange funds and swaps can be used as a substitute for an open market sale

12 Besides a growth in the use of equity based pay many companies also require executives to maintain a certain amount of ownership in the firm’s stock. See (Core and Larcker (2002) and Cao, Gu, and Yang (2010)). 13 Hall and Murphy (2002) and Carpenter (2000) show that executives value their equity positions in the firm below their market value because they cannot hedge the risk associated with these positions. Meulbroek (2000) demonstrates that undiversified executives are willing to sell shares at a substantial discount in order to reduce their exposure to firm specific risk. 14 Ofek and Yermack (2000) find that executives appear to manage the amount of wealth they have at risk in the firm by selling some previously owned shares following new option grants.

18 to achieve either diversification or monetization of ownership in the firm’s stock. In fact, literature produced by investment banks and wealth management advisors such as JP

Morgan, William Blair and Company, and Bernstein Wealth Management all tout the diversification aspect of collars, forwards, exchange trusts and swaps.

If hedging is done primarily for diversification we would expect these transactions to be associated with high ownership levels. Additionally, there are corporate events that affect the incentives of insiders to seek diversification or

monetization of their ownership. For example, insiders in firms that have recently gone

public tend to hold a considerable number of shares and often are subject to lockup

provisions that prohibit them from immediately selling their holdings (e.g., Field and

Hanka (2001), and Brav and Gompers (2003)). High ownership coupled with lockup

provisions expose insiders to considerable firm specific risk. There are other corporate

events where insiders want to maintain voting rights while protecting themselves from

downside risk. For example, insiders may want to diversify or hedge their equity and

maintain voting rights prior to a merger transaction or an acquisition of another firm since

there is some evidence that the acquiring firms experience a negative market reaction on

the announcement date (Travlos (1987)). This leads to the following hypothesis.

H3: Insiders are more likely to hedge when ownership levels are high, prior to an IPO or corporate event where voting rights are important (such as a takeover attempt, merger, or acquisition of another firm).

Since concentrated equity positions expose insiders to significant idiosyncratic

risk any change in the riskiness of the firm could increase the demand for these securities.

Consequently, we expect the use of these transactions to be associated with changes in

business strategy or investment activity that change the risk profile of the firm. Similarly,

19 if hedging is undertaken by officers or directors to reduce uncertainty it may also take place following a change in upper level management, for example following the departure of the CEO. This leads to the following hypothesis.

H4: Hedging is associated with events that change the firm’s risk profile (such as a change in the CEO, increase in R&D investment and/or capital expenditures) or occur generally prior to an increase in stock return volatility.

While insiders have the incentive to hedge following a change in business strategy that increases firm specific risk, another aspect of these transactions is they may encourage risk taking once the hedge is put into place since they reduce insiders’ exposure to firm specific risk. Of course, if managers are willing to undertake riskier investments because they have hedged this would lead to predictions similar to hypothesis H4. In our empirical analysis we do not try to distinguish if insiders hedge prior to events that change firm risk or if the hedging transaction itself encourages risk taking. We will simply try and identify if there is an association between the use of these instruments and changes in firm strategy that can increase firm specific risk.

4. Stock Price Performance and Corporate Events Surrounding Hedging by Insiders

In this section we examine the degree to which the use of derivative instruments is driven by insiders’ knowledge about future firm performance. If the use of these derivative instruments is based on insider information we anticipate that we will see changes in firm performance following these transactions and an increased frequency of corporate events that indicate poor future performance (H1). Stock price and financial data for the test conducted below come from CRSP and COMPUSTAT.

4.1 Stock price changes surrounding hedging transactions

20 The prior evidence on whether derivative transactions precede poor performance

is mixed. Bettis et al (2001) find no evidence that the use of collars is associated with

poor performance while Jagolinzer et al. (2007) find some evidence of poor stock price

performance following the initiation of forwards. In this section we examine stock price

performance surrounding the use of collars, forwards, exchange funds and equity swaps.

To analyze the stock price performance surrounding a derivative transaction we

use several benchmarks to evaluate cumulative abnormal returns. We compare returns

for derivative firms with a size (total book value assets) and industry (two-digit SIC code)

matched sample. Because these transactions are similar to an insider sale we also use

firms similar in size and industry that have an insider open market sale similar in size to

the derivative transaction. This benchmark can provide evidence as to whether a

derivative transaction may serve as a substitute for an insider sale prior to poor

performance. In addition, this benchmark provides a more conservative measure of

abnormal returns assuming that open market sales are used by insiders to exploit private

information. Finally, because prior evidence in Bettis, et al (2001) and Jagolinzer (2007)

show that these transactions are preceded by a run-up in stock price we also form a

matched sample based on size, prior book-to-market, and prior year stock return.15 We include this benchmark because we expect it to produce a more conservative estimate of negative abnormal performance. We report the return patterns surrounding these contracts separately for each type of hedging contract since the motivation to use each of these securities may vary. We consider multiple transactions at the same firm in the same

15 We also used several other benchmarks for robustness that included the CRSP equally and value- weighted indexes along with a control group using the methodology of Barber and Lyon (1997), matching on size and book-to-market value of equity in the year prior to the hedging transaction. All the results are very similar as reported below with the exception of the CRSP value-weighted index-adjusted abnormal returns where we found weaker post performance results.

21 month for the same insider as an individual observation and select the earliest transaction

for that insider in that month.

Table 4 presents the results of the performance analysis for each separate

instrument. We show returns only for the 250 trading days before and after the hedge but

we run our performance analyses on shorter windows (120 trading days before and after

the hedge) with similar results. As Table 4 indicates all of these transactions are preceded by significant abnormal stock price performance. Using the size and industry controls as a benchmark for purposes of discussion we see that average abnormal returns prior to the transactions are 42.7% for collars, 22.4% for forwards, 40.3% for exchange funds, and 30.6% for swaps. The fact that these transactions follow a significant increase

in stock price is consistent with insiders wanting to diversify away firm risk since they

now have a greater amount of their wealth tied to the firm. Transactions that follow a

significant increase in stock price, however, could also indicate that insiders engage in

these instruments when the firm is overvalued and they expect poor future firm

performance. We now explore this issue.

Table 4 indicates for collars and forwards there is a significant reversal in stock

price performance subsequent to the transaction. Compared to both the size and industry

(size, book-to-market, and prior performance) control, collar transactions are followed by

abnormal returns of –18.8% (–11.5%). These results are similar for forwards, –6.8% (–

13.5%). The results using the size, industry and insiders sales matched sample show

negative performance following a forward transaction, –9.48%, but the negative returns

for collar transactions using this benchmark are not statistically significant. Equity-swaps

on average have subsequent poor performance but the returns are not statistically

22 significant. To some degree our results are related to Yermack (2009) who finds almost

identically patterns of stock price performance for charitable gifts by CEOs. For

example, he finds that charitable stock gifts are preceded by positive abnormal returns

which are then followed by negative abnormal returns. He argues that CEOs take

advantage of inside information about current and future performance to time their

charitable giving.

In contrast to the post-hedging performance results for collars, forwards and to

some degree equity swaps, we find positive stock price performance following exchange

fund transactions. Relative to all benchmarks, firms where insiders enter into an

exchange trust experience positive abnormal returns following the transactions. For the

size and industry control the abnormal return following the transaction is 9%.16 The difference in performance for exchange funds compared to the other hedging instruments could be explained by structural differences discussed in Section 2 above. Since exchange funds are monitored by the institutions managing them they have incentives to include better performing firms in the fund. In fact, these institutions, primarily investment banks, may use information they have about these firms to solicit them into the fund. The difference in ex-post performance results between exchange funds and other hedge instruments also suggest that not all derivative transactions are viewed the same by insiders.

4.2 The frequency that collar and forwards are in the money

16 We examine median abnormal returns, before and after hedging, for all four types of instruments. Our inferences using median abnormal returns are virtually identical to what we obtain using means.

23 In order to better understand an insider’s motivation to use these instruments we next attempt to quantify the economic benefits that insiders achieve by holding a derivative security. We examine the frequency with which collars and forwards hit their

contractual floor to measure the losses avoided by the insider.17 From details available

within a subset of our sample we are able to determine the put-price floor for 259 collar

transactions and the floor price for 362 forward transactions. We cannot use all the

transactions because not all filings reveal the contractual floors and ceilings. We

aggregate transactions for each insider during a particular month. If hedging transactions

precede poor performance we expect the share price of hedging firms to fall below the

contractual floor price more frequently than the control sample of firms. For comparison purposes we use the same benchmarks used in Table 4. In constructing the control sample we place a hypothetical floor for the control group that is similar to the floor of the actual contract of the hedge sample firm. Because the average contract length for both collars and forwards is three years we extend the analysis to three years. Since this requires us to analyze long-term performance we also form a third control group using the methodology of Barber and Lyon (1997), matching on size and book-to-market value of equity in the year prior to the hedging transaction.

Panel A of Table 5 which presents the result for both collars and forwards combined demonstrates that for all the benchmarks and for almost all time periods collars and forwards are more likely to fall below the contractual floor compared to the

comparison matched sample. For example, at contract expiration almost 46% of the

collar or forward firms have stock prices below the contract floor while only 33% of the

17 Our analysis is limited to collars and forwards since these are the only two hedging instruments with this type of a provision whereby we can measure the ceiling-to-floor ratio.

24 Barber and Lyon (1997) matched firms have stock price below the floor. As Panel B

indicates the results for collar firms are consistent with Panel A but slightly weaker using the size, book-to-market and prior return match.

Panel C of Table 5 presents similar analysis for forwards. Using the size and industry control both in the first two years and at contract expiration we find that forward contracts are more likely to be below the floor. The results, however, are not always significant at traditional levels – p-values are 0.15, 0.11 and 0.05 respectively. The results for the first two years following the transaction are similar using the size, industry, and insider sales controls but the results at contract expiration are mostly insignificant – p-values are 0.13 and 0.065 and 0.34, respectively. While not overwhelming, the evidence provides some support for the hypothesis that forwards precede poor performance.

4.3 Hedging prior to corporate events

In this section we examine whether derivative transactions precede three different adverse, material corporate events - shareholder litigation, earnings restatements, and negative earnings surprises. We gather data on litigation from the Securities Class Action

Clearinghouse (SCAC) data maintained by Stanford University. The database contains information on federal class action securities fraud lawsuits.18 We obtain data on

earnings restatements compiled by the General Accounting Office (GAO) of the U.S.

government. Finally, we obtain data on negative earnings surprises from I/B/E/S.

For all our tests we employ a size and industry matched control sample of firms

whose insiders do not file a hedging transaction. These control firms are the same firms

18 More detailed information on this database can be found at http://securities.stanford.edu/.

25 we used for the performance analysis discussed before. We use a difference-in-

difference analysis and run a linear probability model on the following variables.19 The variable Sample takes the value one if the firm’s insiders use hedging instruments, and zero otherwise. The variable Post takes the value one if the period follows the hedging transaction and zero if the period precedes the hedging transaction. A positive coefficient on Sample*Post indicates the difference between the derivative firm and sample firm for the observed event (e.g., shareholder litigation) is greater in the post period than in the pre period. In the table the p-value is displayed to denote statistical significance of

Sample*Post. Standard errors are corrected for heteroskedasticity and clustering at the firm level.

Table 6 Panels A, B, and C present the results on the frequency of shareholder litigation, earnings restatements, and negative earnings surprises for the different instruments. For collars we find an increase in the frequency of shareholder litigation

(Panel A) and earnings restatements (Panel B) both one and two years subsequent to the transaction and negative earnings surprises (Panel C) one year subsequent. For variable forwards we also find an increase in the frequency of shareholder litigation one and two years out and evidence of more frequent earnings restatement two years subsequent but no evidence of earnings surprises following the transactions. We do not find that equity swaps are followed by an increase in these corporate events. This could be due to the small sample size. For the most part, the analysis for collars and forwards is consistent with hypothesis H1 which postulates that if derivative transactions are information based we should see an increase in these corporate event subsequent to the transaction.

19 We report the LPM results because of issues in interpreting interaction variables in non-linear probability models. See Ai and Norton (2003) for related discussions on this issue.

26 For exchange funds we find some evidence of increased shareholder litigation

(Panel A) two years subsequent to the transactions but no evidence of increased

shareholder litigation one year following the transactions. There is no evidence of

increased earnings restatements or negative earnings surprises subsequent to the transactions. These results are consistent with our conjecture that exchange funds are less likely to be information based.

4.4 Additional tests

We also performed cross sectional regressions with the abnormal returns relative to the size-industry control sample for the 250 trading days following each transaction as the dependent variable. Independent variables included firm characteristics such as firm size, characteristics of the insiders (e.g., CEOs, board members, beneficial owners etc), the value of the transaction, the fraction of ownership hedged, whether the firm had an

IPO in the prior two years, the stock price run up prior to the transaction, stock return volatility after the transaction, along with industry and year fixed effects. We include the type of transaction in one specification and then use different specifications for each of the four different hedge types. Other than differences in performance by contract type

(exchange funds had better post performance than collars or forwards), the only other variable related to post stock price performance was the firm’s market-to-book ratio.

Higher market-to-book firms experienced greater stock price declines following the

transaction. Overall, there does not appear to be a relation between the characteristics of the individual or the amount of ownership hedged and poor subsequent performance.

5. Hedging transactions, pay for performance, and corporate governance

27 5.1 Hedging transactions and pay for performance

In the absence of ex-post adjustments to compensation via new stock or option

issuances derivative transactions may significantly diminish the incentives of executive officers to exert effort. It is however unclear to what extent hedging alters incentives and whether boards design compensation contracts for executive officers that take into account executives use of derivative instruments. For example, Gao (2010) finds evidence that boards respond to CEO propensity to hedge by increasing the pay-for-

performance (PPS) sensitivity in compensation contracts. In the analysis below, we

restrict experiments to CEOs with derivative instruments since CEO’s are the primary

decision makers at the firm.

We present results of our analysis in Table 7. The dependent variable is the

change in CEO wealth (in $ thousands), defined as the sum of salary, bonus, equity

compensation comprising the Black-Scholes value of new option awards and the value of

restricted stock awards and long-term incentive payments, and change in the value of

existing stock options and shares. Chgshwealth (in $ million) is the beginning-of-the-

year market capitalization multiplied by the annual stock return during the year. Sample

is an indicator variable that takes the value 1 if the CEO uses a derivative instrument and

0 for the control firm. Control firms are selected from the intersection of CRSP,

Compustat and EXECUCOMP by matching the derivative firm on size (measured by book value of assets) and industry (defined by the 2-digit SIC code). Post is an indicator variable that takes the value 1 if the year is the year of or year after hedging, and 0 if the year precedes the hedging transaction. We follow the specification used by Garvey and

Milbourn (2003) and include the cumulative distribution function (CDF) of systematic

28 risk, unsystematic risk, and market-to-book ratio. We adjust Chgshwealth in the year of and the year after the derivative transaction to account for contractual features of the contract. Since the economic implications of using an exchange fund are somewhat different from the other instruments we restrict attention to collars, forwards and swaps.

Results in Model (1) indicate that a typical CEO faces a $53 increase in firm- related personal wealth for a $1,000 increase in shareholder wealth. Coefficients on all control variables are similar in magnitude and direction to those reported in Garvey and

Milbourn (2003). We find evidence that hedging firm CEOs experience a 16% reduction in the sensitivity of their wealth to firm performance after the transaction. To be precise, the sensitivity of wealth to firm performance declines from $67 (i.e. $52.606+$14.568) to

$56 (i.e. $52.606+$14.568–$18.056+$6.729). Inferences are very similar when we only examine collars and forwards (Model (2)). CEOs that use collars and forwards witness a

22% reduction in the sensitivity of their wealth to firm performance after the transaction

The decline in the sensitivity of CEO wealth to firm performance is both statistically and economically significant.

Our results indicate that certain derivative securities allow insiders to dramatically reduce the sensitivity of their wealth to firm performance thereby significantly decreasing the incentive effects of their equity ownership. To put it another way, the ownership disclosed in annual filings such as proxy statements overstates the pay-for-performance sensitivity in compensation contracts and paints a somewhat misleading story of the true incentive effects of insider ownership to the firm’s shareholders.

5.2 Hedging transactions and corporate governance

29 In this section we examine to what degree the transactions are associated with firm governance structure. For this analysis we form a control sample constructed from the intersection of CRSP-COMPUSTAT-IRRC database of firms for the period covering

1996 through 2006. We include IRRC database because it provides detailed information on board structure. We then form a size (book value of assets) and industry (2-digit SIC code) control group of firms. We note that the firms in the IRRC database consist of firms of similar size across a broad range of industries over the same time period as firms in our hedging sample.20 For firms with multiple hedging transactions in a year we select the earliest contract for a given sample firm in any given year.

The governance variables we analyze include the fraction of outsiders on the board, board size, a dummy for CEO/Chair duality, insider ownership, and ownership by institutions and 5% blockholders. We also include a dummy if there was CEO turnover prior to the year of the hedging transaction. Since data on insider and beneficial ownership is not included in the IRRC database we gather data on insider ownership from proxy statements and data on ownership of 5% institutional blockholders from Thomson

Reuters’ 13F Institutional Holding database.21

Table 8 presents univariate analysis of differences in governance characteristics.

We separate the analysis for the different types of derivative securities but exclude equity swaps because of the small sample size. We also ran a logistic model that included the

20 For robustness we also formed a control sample of firms based on size and industry not restricted to the IRRC universe. These are the same sized industry matched firms used in the analysis above. For the most part all the results on financial characteristics described that are found with the IRRC firms and reported below held up with the unrestricted sample. 21 The Thomson data consists of all institutions with at least 5% ownership. This may not be exactly the same as 5% ownership disclosed in proxies if those entities that do not have to file 13F with the SEC.

30 same variables presented in the univariate analysis plus a number of other control

variables and obtained similar results (see Appendix B for details).

The results in Table 8 indicate that firms where insiders use a derivative

instrument are more likely to have fewer independent directors and higher insider ownership. 22 Firms where insiders use a forward or an exchange fund are more likely to

have lower ownership by 5% institutional blockholders. These results suggest that the

use of these instruments tend to be associated with weaker corporate governance (H2).

While not directly related to corporate governance we also look at the frequency with which these transactions are associated with an IPO and with CEO turnover.

Insiders may use these transactions surrounding CEO turnover because the change in leadership may increase uncertainty about future firm performance (H4). We find that for all transactions firms are more likely to have had an IPO prior to the transactions.23

This is consistent with H3 and suggests firms use these instruments when they have concentrated ownership that might be subject to restrictions on trading. We do not find the use of these instruments is associated with CEO turnover.

6. Further analysis on the motivation of insiders to use derivative securities.

6.1 Derivative transactions and mergers and acquisitions

In this section we discuss the degree to which the use of these securities is associated with M&A transactions. Corporate insiders of an acquiring firm in an M&A transaction have incentive to use these instruments in order to keep voting rights in an

22 For their sample of collars Bettis et al (2001) also find fewer independent directors but in contrast to our findings lower ownership by insiders. 23 Bettis et al (2001) find that firms that use collars are more likely to have done an IPO.

31 attempt to affect the outcome. At the same time they reduce the risk from a failed

transaction.24 There is evidence of negative abnormal returns to bidding firms involved

in an acquisition (Travlos (1987)) which provides a motivation to hedge the uncertainty associated with deal completion.

To examine this issue we obtain information on acquisition activity for our sample of derivative firms and the size and industry-matched control firms using data on

M&A deals from Securities Data Corporation (SDC). Similar to the analysis in Table 6 we perform a difference-in–difference regression examining changes in the frequency in

acquisitions between the two samples the year prior and one and two years subsequent to

the derivative transaction. In results not reported, we find that firms where insiders

engage in a forward transaction or exchange funds are more likely to be involved as an

acquiring firm in an M&A deal the year following the hedge (when compared to control

firms) – p-values on probability of an acquisition one year after the hedge were all

significant at 5% or better. We do not find any evidence that collar transactions are

associated with an increase in acquisition activity. Overall the results suggest that one

reason for the use of forwards and exchange funds is to hedge or diversify prior to an

acquisition which is consistent with H3. The results are also not inconsistent with

opportunistic use of these instruments based on inside information about future corporate

decisions.

6.2 Derivative transactions and changes in investment activity and firm risk

24 Hu and Black (2007) provide some anecdotal evidence of the use of derivative securities by hedge funds around mergers and acquisitions. Their analysis is a case study of a handful of these transactions and the transactions are mainly equity swaps. The sample size is small because hedge funds are not typically Section 16 insiders. In fact, one reason hedge funds engage in a swap around an acquisition is because the swap separates voting rights from cash flows and allows the hedge fund to keep cash flow rights but not have to report beneficial ownership (even if they acquire more than 5% of the equity) because they do not have voting rights.

32 One reason that insiders might want to engage in a derivative transaction is when

there is increased uncertainty about future firm performance or risk (H4). An increase in

investment activity or R&D expenditures could raise uncertainty about the value of the

firm in the future and serve as a motivation to use these instruments. In addition, other

events such as an increase in leverage or general market changes might lead to more

uncertainty and higher stock return volatility in the future. To test hypothesis H4 we look

at changes in R&D expenditures, investment expenditures, leverage, and stock return volatility around the hedging transaction.25

For statistical tests, again we run a difference-in-difference regression to capture

any differences in financial or investment policy between firms whose insiders use derivative instruments and the control sample of firms whose insiders do not use any derivative instruments. We perform our tests one year prior, and one and two years

subsequent to the contract.

As Table 9 indicates we find no evidence to support the hypothesis that changes

in investment and financial policy arise from hedging. Relative to our control firms,

expenditures on R&D and total investments (both scaled by total assets) were no different

after the transaction (years +1 and +2) than before (year 1). Further, we find no

significant differences in leverage or in the standard deviation of the firm’s stock price following the hedge. Overall the results do not support the notion that hedging is motivated by uncertainty surrounding future firm investment or financial policy, nor do they support the alternative explanation that hedging affects firm policy through increased risk-bearing ability of insiders.

25 As discussed in the hypothesis section changes in any of these variables could be driven by executives being more willing to take on risky projects because they have reduced their exposure to firm specific risk.

33 6.3 Derivative transactions and personal income taxes

In this section we examine the degree to which the use of these securities is motivated by the need to shield personal income from taxes. Examination of the impact of taxes on the use of derivative transactions is complicated by the fact that we cannot observe the marginal tax rates of insiders. To simplify the analysis, we only examine

CEOs and restrict analysis to firm-related personal income following the methodology used by Goolsbee (2000). We define personal income as the sum of salary, bonus, value of stock options exercised, and long-term incentive payouts. We collect CEO compensation data from Execucomp database. Following prior literature we control for firm size (measured by book value of assets), market-to-book ratio of assets, annual stock return and annualized stock return volatility. We also include year and industry (two- digit SIC code) fixed effects.

Results are presented in Table 10. We present analysis for the year before, year of, and year following the transaction. Our evidence suggests that sample firm CEOs have higher taxable income in all the years (approximately $3 million more of taxable income compared to control firm CEOs that do not use derivative instruments). Overall our findings suggest that the use of derivatives is, at least in part, driven by the higher level of personal income to shield from taxes. We do not want to overstate the importance of our findings, however, considering the fact that we are likely measuring

CEO taxable income with some noise.

7.1 Other issues associated with these transactions

7.1 Banning these transactions

34 Shareholders, regulators, and some boards have raised concerns over the use of derivative securities by insiders. To examine the concern that shareholders and boards have over the use of these instruments we conducted a keyword search of all proxies and

10Ks filed between 1996 and 2006 to identify firms that have formal policies that ban these transactions.26 Prior to 2006 we found that on average only one firm a year reported that they banned the use of these instruments. We saw a significant increase in reported bans in 2006 where we identified 151 firms having formal policies banning these transactions.27 In all, between 1998 and 2006 we identified 160 firms reporting formal policies regarding the use of derivatives. Of these firms about 72% had complete bans, about 4% allowed these with approval by the board, and about 24% had partial bans.28 Interestingly not all insiders were treated the same. Only 24% of the firms banned all employees from using these and only 15% banned all executives and directors.

Thirty percent banned only executives. Despite the increase in hedging bans disclosed by companies in 2006 the number of firms that restrict the use of these, at least formally, still appears to be small.

7.2 Recent IRS litigation and variable forwards

The tax laws involving these securities have been steadily involving. As discussed above equity swaps are now considered a constructive sale and any capital gains associated with the swap are incurred on the transaction date. During the time period of our study for tax purposes insiders were allowed to defer any tax on the value

26 We use the following keyword search in Lexis-Nexis: ((trad!) w/30 (hedg! or coll! or call! or put! or swap! or forw! or derivative)) or ((inside!) w/30 (hedg! or coll! or call! or put! or swap! or forw! or derivative)). Of course, our numbers will underestimate the total number of firms that banned the use of these instruments. 27 The new Proxy reporting rules effective in 2006 almost certainly spurred the increase in reporting. That is, it is likely that prior to 2006 some of the companies already had bands but did not report them. The new Proxy rules required related disclosure about the existence of such bands. 28 We have rounded here. In 0.6% of the sample the discussion of the ban was too vague to classify.

35 of collars, forwards and exchange funds. Recently, in June of 2010 a U.S. Tax Court judge ruled that the variable forward contract set up by Philip Anschutz was a taxable event on the transaction day which means taxes cannot be deferred. The decision is being appealed and so the final outcome on the tax treatment of variable forwards may not be known for some time (perhaps years). As far as we are aware, the decision by the tax court, however, only involved forwards and not collars or exchange funds or at this point any future instruments developed to provide a hedging or diversification feature. If the ruling stands in the future we anticipate this may have an impact on the use of forwards.

We would not be surprised, however, if investment banks developed additional derivative instruments that would keep the favorable tax status. In fact, while we do not have direct evidence there is reason to believe the development of collars was a response to the change in tax status of equity swaps. In addition, forwards were probably developed because collars are difficult to monetize. It appears these securities, no matter what the final decision by the tax court, will continually evolve.

8. Conclusion

Tying executive wealth to firm performance has been a major goal of shareholders over the last several decades with the economic rationale to motivate managers to exert effort to increase firm value. Shareholders have been largely successful in achieving this goal of aligning managerial incentives through the increased use of stock and stock option based compensation along with minimum ownership requirements for top management. Because of high levels of ownership and human capital that many executives now have in the firm these individuals have incentive to

36 diversify or hedge their equity positions and the development of various hedging securities has given executives and other insiders the flexibility to do this. While insiders have the motivation and means to hedge there is limited empirical research in this area.

In this paper we use a novel data set to provide an empirical examination of the hedging instruments used by corporate insiders that are reported in SEC filings. We find that the use of these instruments has become more popular over time and that there are predominately four types of securities that insiders use to hedge – collars, forwards, exchange funds, and equity swaps. Our data indicate that a diverse group of insiders use these securities and that for certain instruments the average effective ownership hedge is substantial. Our analysis indicates that for collars and forwards, the pay-for-performance sensitivity for CEOs drops by almost 22% after the transactions are put in place.

Our analysis also indicates that there is heterogeneity in the use of these securities and in the motivation for why insiders hedge with these instruments. For collars and forwards we find substantial decline in stock price following the transactions whereas for exchange funds we find no decline in performance following the transactions. The poor stock price performance that follows collars and forwards combined with the fact that the fraction of ownership hedged with these securities is substantial, suggests that insiders may time the use of these instruments opportunistically to exploit private information.

The same does not appear to be true with exchange funds. These result coupled with our findings of an economically significant reduction in the pay-for-performance sensitivity for insiders, and the overall weakness in internal corporate governance mechanisms in derivative firms paint a troubling aspect of insider hedging with certain types of securities such as zero cost collars and variable forwards that has not been well understood.

37 While the recent Dodd-Frank Wall Street and Consumer Protection Act (2010) now requires companies to disclose details of insider hedging policies in the annual proxy statements it is not clear that the regulation will necessary reduce their use. Furthermore, if history is any guide, future development of financial instruments that insiders can use to hedge their firm specific wealth is likely to evolve in sophistication and use.

Understanding the use of these securities is important to not only to research on corporate governance and managerial incentives but also to the research on insider trading.

38 APPENDIX A Hedging Instruments

Over the last couple of decades there has been an increased emphasis on tying

executive wealth to firm performance both through the use of incentive based pay, which

comes primarily through stock options, and increased stock ownership by executives and

other insiders.29 Moreover a strong stock market, increased M&A activity, and stock-for-

stock mergers during our sample period all contributed to an increase in equity ownership

for both individual executives and institutions. Since insiders, in particular corporate

executives, tend to have substantial concentration of wealth and human capital in their

own firm, they have an incentive to reduce their exposure to firm specific risk. There are

a number of ways individuals and institutions can hedge risk associated with concentrated

ownership. Executives could, for example, use their personal wealth to trade securities that have a low correlation with the firm’s stock. Executives could also use stock index futures, single stock futures and options to hedge their exposures to their firms. Hedging

instruments however allow corporate executives to very specifically target their exposure

to firm specific risk. Also, by using customized, off-the-exchange contracts an executive

can avoid issues related to liquidity and trade anonymity that may accompany the use exchange traded single stock futures or options. We now discuss the key features of the

four most common hedging instruments reported and used by corporate insiders.

Equity Swaps

One of the first types of derivative hedging instruments used by insiders were equity swaps which are also referred to as a total return equity swap. In equity swap

29 Murphy (1999) along with Hall and Liebman (1998) document an increase in the use of stock options as part of compensation packages over the last two decades. Holderness, Kroszner, and Sheehan (1999) document an increase in equity ownership by both executives and board members over the last 50 years.

39 agreements investors exchange the future returns on their stock for the cash flows of

another financial instrument, such as the Autotote example used in the introduction where

the CEO swapped the returns on the firm’s stock over a 5 year period for LIBOR minus

2%.While this swap traded the return on the firm’s stock for a debt instrument equity

swaps can also involve the exchange of the firm’s returns for the returns on any other

financial instrument such as the S&P 500.

In the 1997 Tax Payer Relief Act the IRS ruled that an equity swap is equivalent

to the sale of the underlying stock that is part of the swap agreement. Because swap

transactions are deemed a “constructive sale” and trigger an immediate tax liability most

corporate insiders have turned to other hedging securities discussed below that have more

favorable tax treatments. Recently, however, swap transactions have seen a recurrence

with hedge funds and other large blockholders. An interesting aspect of swap agreements

is they allow the separation of economic ownership from voting rights. By separating economic ownership from voting ownership investors can avoid public disclosure of their equity position in the firm and this appears to have been a strategy by a number of hedge funds involved in proxy fights or M&A activity. A recent court case reveals how this type of transaction works. Children’s Investment Fund, 3G Capital and a number of other hedge funds used equity swaps which gave them an effective ownership stake

greater than 5%, which typically triggers disclosure in the U.S., in CSX railroad prior to

launching a proxy contest at the firm. Because the long position in the swap did not have

voting rights the hedge funds claimed they did not have to reveal their equity position in

the company prior to engaging in a proxy battle. It is noteworthy that investment banks

usually hedge the M&A deal - in this case by buying shares in CSX - thus these hedge

40 funds can easily obtain the shares from the investment banks when they are needed to vote in the proxy fight, but at the same time can delay disclosing their ownership to the market.

Another advantage of equity swaps is that they can also be used to keep voting

rights but not an economic interest. This occurs by taking a short position in the swap and also holding shares. The ability to decouple ownership from voting power with a

swap transaction has raised concerns by both companies and regulators. In addition,

several hedge funds are being investigated for using swaps to hide ownership positions

prior to takeovers and proxy fights. See Hu and Black (2007) for more detailed

discussion of how insiders and hedge funds (or any institutional investor) can use swap transactions to decouple economic and voting ownership and the recent controversy that surrounds their use. To the best of our understanding, the equity swaps included in our sample involve transactions where the company insiders hold shares in the company and take a short position using an equity swap contract effectively unwinding the economic ownership in the firm, and yet retaining voting power.

Zero-Cost Collars (Collars) and Prepaid Variable Forward Contracts (Forwards).

While collars and forwards are technically different instruments they share some of the same characteristics. Both collars and forwards have; 1) a floor price which determines the level of downside protection in stock price the investor can hedge against,

2) a ceiling price which determines the level of upside growth in stock price the investor can participate in, 3) a set maturity that determines the contract length, and 4) a cash advance feature (a feature more common with forwards).

41 More specifically, a collar transaction involves the simultaneous purchase of a put

option and sale of a call option covering the firm’s shares. Most collar transactions are

“zero cost” because the proceeds from the sale of the written call are used to purchase the

put. The put option component of the collar transaction provides insurance for the holder against downward movement in the stock price below the strike price of the put. Any stock price appreciation above the strike price on the call option is forgone profit. One

reason for the popularity of collars versus equity swaps for insiders following the change

in the tax code in 1997 is that collars, written with sufficient spread, are not considered a

constructive sale and subsequently do not trigger a taxable event. This means that

insiders can defer capital gains taxes on any appreciation for the life of the collar in

addition to hedging against stock price risk.30

A forward is a strategy that combines features of a forward sale of stock and an

equity collar. In a forward agreement the investor enters into a forward sale agreement,

typically with an investment bank, and promises to deliver shares of the firm’s stock at

some future date in exchange for an up-front cash advance. The amount of stock that

must be forfeited upon termination of the contract depends on the value of the stock at

that future date. At maturity if the share price has fallen below a pre-specified price (the

floor price of the contract) the investor is required to deliver all the shares covered by the

contract. Typically the floor price on the forward is the current stock price.

Consequently a typical forward provides full downside protection against depreciation of

the underlying stock price. The investor participates fully in any price appreciation in the

underlying stock up to a preset level (the upper ceiling on the contract). If the stock price

exceeds the upper ceiling the investor receives a predefined percentage of any price

30 For some additional information on the specific structure of collars see Bettis et al (2001).

42 appreciation above the upper ceiling of the contract which means they give up some upside gain. If the share price appreciates the investor is required to deliver only that percentage of the shares necessary to repay the contract amount. It is also possible to structure the agreement so that the investor has the right to cash settle the contract and retain the underlying shares when the contract terminates. By cash settling the contract the investor avoids any capital gains tax that would occur upon disposition of the shares and also retains voting and cash flow rights associated with the shares.31

With both forwards and collars the insider is protected against a decline in the

underlying stock price while retaining a predefined amount of upside in the underlying stock. The insider is also able to defer taxes on the sale of the underlying security while receiving some of the benefits of a sale. One difference between a forward and a collar is how the contracts can be monetized. Forward contracts allow the investor to receive a much larger upfront cash payment in the range of 80% to 90% of the value of the underlying stock. Typically the shorter the contract and the more upside gain sacrificed the more upfront cash payment the insider receives. Monetization of zero-cost collars is more complex. To monetize insiders would receive a loan when the collar is initiated.

The loan amount and interest rate charged depend on the stated purpose of the loan. If

the proceeds of the loan are being used to purchase marketable securities, what is referred

to as a “purpose loan”, the insider can typically borrow up to 50% of the market value of

the hedged position. If the insider wants to use the loan proceeds for reasons such as to

purchase insurance or invest in private equity, then the bank may choose to lend up to

90% of the put strike price. This would be referred to as a “non-purpose” loan.

31 For some additional detailed information about prepaid variable forwards see Jagolinzer et al (2007).

43 Both collars and Forwards are private bilateral agreements between the corporate

insider and a counter party, the latter usually an investment bank. Investment banks

receive commissions and spreads in addition to potentially strengthening their

relationship with the corporation via the senior executives. With a forward the

investment banks usually factor in the costs of the contract as an additional discount in

the cash advance received by the investor. With a zero-cost collar the investment banks

often receive commission fees and/or make money on the spread between the call and put contract.

Exchange Funds

Exchange funds, sometimes referred to as exchange trusts or swap funds, are perhaps the oldest type of hedging instrument used by insiders. Exchange funds have existed since the 1960s and while they have evolved in their sophistication and use their basic structure is fundamentally the same. In an exchange fund a group of insiders individually place their shares in a limited partnership or limited liability company. By pooling shares into a single entity the participants in the fund are able to create a diversified portfolio of securities. In addition, the contribution of shares into the fund does not trigger a tax event that would occur if the shares were sold.

In order for the contributions into the fund to not trigger an immediate capital gains tax liability for the participants, the partnership (fund) cannot invest more than 80% of its assets in marketable equities. Twenty percent of its assets must be invested in non- publicly traded securities which are often relatively illiquid real estate investments.

Typically the assets must remain in the fund for up to seven years but the length can vary.

There are often significant penalties for early withdrawal but redemptions policies also

44 vary. Upon the dissolution some funds distribute the particular stock contributed back to

the insider while others distribute a pro rata portion of the fund’s total marketable securities. As long as investors stay in the fund the full seven years they do not pay any taxes until they sell their underlying stock. Finally, the executive contributing the shares can exercise control over the voting of the shares via the manager of the fund.

Most exchange funds are organized and administered by large investment banks and require a minimum investment of $1 million with an additional requirement that the investor must have a net worth of $5 million. The size of the funds can vary, but they often have at least 50 investors, even though some can be as large as 500 investors. Fees for investing in exchange funds can be substantial including a front-end load and on- going advisory and servicing fees. The investment purpose of the fund can vary widely.

Some funds are structured to benchmark standard indexes such as the S&P 500 while others are more targeted. Because exchange funds are illiquid they are often used for estate planning. In fact, some of these funds are established specifically to attract insiders who want a gift to remain illiquid or inaccessible for a period of time.

45 APPENDIX B Logistic Analysis

The table provides maximum likelihood estimates from a logistic regression of the determinants of hedging during the period 1996 to 2006. The dependent variable is one if for a given firm an insider purchased a derivative instrument and zero otherwise. Derivative instruments include exchange funds, zero-cost collars, equity swaps, and prepaid variable forwards. Control group is size (measured by book value of assets) and industry (2-digit SIC code) matched firms drawn from the intersection of CRSP, Compustat and IRRC. Market- to-book ratio is the sum of market value of equity and book value of total liabilities divided by the book value of assets. Abnormal return is defined as the cumulative raw returns for a firm net of the cumulative returns for the CRSP Value-Weighted index. We measure both stock price performance and volatility over the 250 trading days both prior and subsequent to the hedging transaction. Stock return volatility is the (annualized) standard deviation of daily stock returns. Dividend is dividend per share. Insider ownership is ownership by all officers and directors of the firm. Standard errors are corrected for heteroskedasticity and clustering at the firm level. Absolute values of Z-statistics are reported in parentheses. ***, **, and * denote significance at less than 1%, 5%, and 10% levels, two-tailed tests, respectively.

Zero Cost Variable Exchange Collars Forwards Funds Intercept 0.077 2.255*** −0.608 (0.08) (3.57) (0.72) Book value of assets 0.000 0.000 0.000 (1.50) (1.03) (1.01) Market-to-book 0.048 −0.012 0.090 (0.68) (0.29) (1.09) R&D/assets −7.354*** −0.182 0.810 (3.36) (0.11) (0.44) Abnormal over the 250 trading days prior to 1.144*** 0.741*** 0.522** the transaction (3.44) (3.89) (2.46) Abnormal returns over the 250 trading days −0.488* −0.614*** 0.015 subsequent to the transaction (1.86) (2.85) (0.07) Stock return volatility 250 trading days prior 0.231 −0.362 −1.579** to the transaction (0.31) (0.74) (2.00) Stock return volatility 250 trading days −0.352 −0.535 0.163 subsequent to the transaction (0.67) (1.33) (0.34) Dummy equal to one for firms that went 2.706*** 1.463*** 1.019* public in the prior two years (2.60) (3.46) (1.84) Dividend −0.983 −0.964** −0.554* (1.41) (2.42) (1.82) Governance characteristics Fraction of outside directors on the board −1.667** −3.800*** −1.637*** (2.26) (5.92) (2.17) Number of directors on the board 0.048 0.047 0.141*** (0.86) (1.02) (2.98) Dummy equal to one for firms where CEO is −0.195 0.342 0.100 also chairman of the board (0.67) (1.42) (0.38) New CEO in office 0.102 −0.006 0.978* (0.20) (0.02) (1.91) Insider ownership 2.276* 0.400 2.743*** (1.93) (0.49) (2.97) Ownership of all institutions with beneficial 0.454 −1.758** −0.267 ownership greater than 5% (0.38) (2.20) (0.24) Pseudo R-square 0.203 0.162 0.146 Number of observations 302 609 426

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49 Table 1: Distribution of hedging contracts by year The table provides the distribution of hedging contracts for the period between 1996 and 2006. The sample consists of 2,042 unique hedging transactions, spread across 929 unique individual filers and 582 unique firms during the period from 1996 to 2006. We sub-divide the sample into four different types of hedging contracts; zero cost collars, variable forwards, exchange funds and equity swaps.

Panel A: Year-wise distribution of unique transactions Year Zero Cost Collars Exchange Funds Variable Forwards Equity Swaps Total by Year 1996 21 0 0 1 22 1997 46 2 0 0 48 1998 55 67 1 1 124 1999 70 121 3 7 201 2000 131 138 48 5 322 2001 78 36 165 2 281 2002 35 20 227 3 285 2003 15 10 193 25 243 2004 14 19 165 3 201 2005 6 18 117 56 197 2006 10 11 64 33 118 Total by 481 442 983 136 Contract

Panel B: Year-wise distribution of unique individuals Year Zero Cost Collars Exchange Funds Variable Forwards Equity Swaps Total by Year 1996 14 0 0 1 15 1997 35 2 0 0 37 1998 37 64 1 1 103 1999 41 112 3 5 161 2000 57 132 25 3 217 2001 49 35 91 1 176 2002 16 20 94 1 131 2003 8 10 96 4 118 2004 8 17 81 3 109 2005 4 15 50 9 78 2006 7 10 33 5 55 Total by 276 417 474 33 Contract

Panel C: Year-wise distribution of unique firms Year Zero Cost Collars Exchange Funds Variable Forwards Equity Swaps Total by Year 1996 13 0 0 1 14 1997 29 2 0 0 31 1998 26 52 1 1 80 1999 26 81 3 5 115 2000 38 99 23 3 163 2001 39 31 76 1 147 2002 13 17 75 1 106 2003 6 5 71 4 86 2004 5 16 52 3 76 2005 3 14 35 8 60 2006 5 9 27 5 46 Total by 203 326 363 32 Contract

50 Table 2: Ownership characteristics of hedged instruments This table provides the percentage of ownership hedged with each instrument, the value (in millions of dollars) that is hedged with each hedging observation (panel A), and the distribution of hedged instruments across our classification of “insiders” (panel B) as defined by Section 16 of the Securities Exchange Act of 1934. We begin with 2,042 unique individual hedging transactions from 1996 through 2006. In order to get hedging sample observations, we aggregate hedging transactions for each individual insider in each calendar year. We sub-divide the sample into four different types of hedging contracts; zero cost collars, variable forwards, exchange funds and equity swaps. We classify insiders into two executive categories and two others. Executives are classified as either the CEO/Chairman or “other officer”. The other two classifications are non-officer directors, and beneficial owners (10% or more ownership interest).

Panel A: Percentage of ownership and dollar amount covered by each derivative security.

Percentage of Ownership Invested Dollar Value Invested (millions)

Number of Number of Mean Median Mean Median Observations Observations Zero Cost Collars 227 31.47 21.62 255 $37.48 $5.25 Variable Forwards 441 28.37 18.07 452 $44.91 $7.65 Exchange Funds 363 9.00 4.44 364 $5.19 $2.17 Equity Swaps 31 32.58 14.89 26 $16.40 $3.78

Panel B: Classification of insiders (percentage) for unique hedging observation with available information about the insider’s position.

Number of CEO/ Other Outside 10% Non-Officer Observations Chairman Officer Owner Director Other

Zero Cost Collars 261 27.97 39.46 11.11 18.01 3.45 Variable Forwards 469 28.14 29.64 17.91 23.24 1.07 Exchange Funds 411 41.12 28.95 6.33 18.73 4.87 Equity Swaps 33 18.18 6.06 57.58 18.18 0.00

51 Table 3: Contract life, cash value, and spreads for collar and prepaid variable forward contracts The table provides summary statistics on contractual terms for collar and prepaid variable forward contracts. We begin with 481 individual zero cost collar transactions and 983 prepaid forward sale contracts for the period 1996 – 2006. Both types of contracts have specific term lengths, and contract ceiling and floors. The details necessary to determine the length/term of the contracts, the ceiling-to-floor and ceiling-to-price ratios are provided in Form 4 filings for a subset of these transactions. A feature of prepaid variable forward contract is that cash is available at the time in which the contract is signed. We use Form 4 footnote disclosures for prepaid variable forward transactions to determine the cash received by the insider (as defined in Section 16 of the Securities Exchange Act of 1934).

Panel A: Zero Cost Collars

Days-to- Ceiling-to- Ceiling-to- Price-to- Expiration Floor Ratio Price Ratio Floor Ratio Mean 1028 1.79 1.55 1.16 Median 1019 1.59 1.36 1.11 N 410 416 416 416

Panel B: Variable Forwards

Cash Days-to- Ceiling-to- Ceiling-to- Price-to- Cash received Expiration Floor Ratio Price Ratio Floor Ratio discount ($000) Mean 1025 1.43 1.33 1.07 13,292 21.79 % Median 1095 1.34 1.29 1.01 3,433 17.27% N 807 612 612 612 558 558

52 Table 4: Stock returns around initiation of hedging contracts The table provides stock returns for firms whose insiders engage in hedging transactions during the period 1996 to 2006. We begin with 2,042 unique individual hedging transactions from 1996 through 2006 and aggregate hedging transactions for each individual insider in each calendar month of a year and end up with a total of 1,374 hedging transactions. Cumulative abnormal return (CARs) is defined as the cumulative return for a sample firm minus the cumulative return for a control firm. There are three sets of control firms appearing in the table. The first control group is size (measured by book value of assets) and industry (2-digit SIC code) matched firms drawn from the intersection of CRSP and Compustat. The second control group is size (measured by book value of assets), industry (2-digit SIC code), and open market sales (measured by the numbers of shares sold by an insider in the open market deflated by the total shares outstanding for the firm) matched firms drawn from the intersection of CRSP, Compustat and Thomson Reuters insider trading database. The third control group is size (measured by book value of assets), Btm, defined as the ratio of book-to-market value of common equity, and return-matched firms drawn from the intersection of CRSP and Compustat. Specifically, for each sample firm, we find a control firm with size that lies within 70% to 130% of the sample firm’s size. Within this subset of possible matches, we select a control firm that has the closest book-to-market value of equity and returns in the 250 trading days prior to the event. P-values are reported in parentheses.

Mean Cumulative Abnormal Return (%)

Panel A: Zero Cost Collars Matched Firm: Matched Firm: Matched Firm: Size & Industry Size, Industry, & Size, Btm, & Insider Sales Prior Return [−250,0] 42.72 7.60 0.57 (0.000) (0.174) (0.165) [0,+250] −18.83 −5.45 −11.51 (0.000) (0.210) (0.011)

Panel B: Variable Forwards Matched Firm: Matched Firm: Matched Firm: Size & Industry Size, Industry, & Size, Btm, & Insider Sales Prior Return [−250,0] 21.42 2.44 0.03 (0.000) (0.488) (0.705) [0,+250] −6.77 −9.48 −13.50 (0.024) (0.003) (0.000)

Panel C: Exchange Funds Matched Firm: Matched Firm: Matched Firm: Size & Industry Size, Industry, & Size, Btm, & Insider Sales Prior Return [−250,0] 40.28 20.65 0.03 (0.000) (0.000) (0.622) [0,+250] 8.87 6.69 13.58 (0.062) (0.215) (0.007)

Panel D: Equity Swaps Matched Firm: Matched Firm: Matched Firm: Size & Industry Size, Industry, & Size, Btm, & Insider Sales Prior Return [−250,0] 30.62 6.52 1.10 (0.031) (0.698) (0.434) [0,+250] −21.57 10.34 −4.52 (0.163) (0.520) (0.664)

53 Table 5: Frequency that collar and forward contracts end up below stock price floor The table provides the frequency with which zero cost collars and prepaid forward contracts end up below the stock price floor specified in the contract. Sample firms are as described in Table 4. There are three sets of control firms appearing in the Table. The first control group is size (measured by book value of assets) and industry (2-digit SIC code) matched firms drawn from the intersection of CRSP and Compustat. The second control group is size (measured by book value of assets), Btm, defined as the ratio of book-to-market value of common equity, and return-matched firms drawn from the intersection of CRSP and Compustat. The third control group is formed following the approach in Barber and Lyon (1997). Specifically, for each sample firm, we find a control firm with a market value of equity that lies within 70% to 130% of the sample firm’s market value of equity. Within this subset of possible matches, we select a control firm that has the closest book-to-market value of equity. We measure market value of equity at the end of June of the year t, i.e. the year of adoption of performance-vesting provision. We measure book-to-market value of equity at the end of year t-1.

Panel A: Zero Cost Collars and Variable Forwards Year 1 Year 2 Year 3 At Contract Expiration Collars, Forwards 43.71 45.37 42.83 45.55 Size & Industry 37.12 38.04 35.84 32.38 Match p-value 0.027 0.018 0.028 0.000 Size, Btm and 35.85 38.41 35.68 39.17 Return Match p-value 0.009 0.027 0.026 0.055 Barber & Lyon 36.19 36.13 30.17 32.95 Match p-value 0.004 0.002 0.000 0.000

Panel B: Zero Cost Collars Year 1 Year 2 Year 3 At Contract Expiration Zero Cost Collar 49.79 56.16 53.43 55.07 Size & Industry 42.04 48.04 44.74 36.26 Match p-value 0.092 0.094 0.084 0.000 Size, Btm and 44.02 49.24 47.83 49.72 Return Match p-value 0.221 0.157 0.270 0.293 Barber & Lyon 38.99 37.50 25.77 29.89 Match p-value 0.020 0.000 0.000 0.000

Panel C: Variable Forwards Year 1 Year 2 Year 3 At Contract Expiration Variable Forwards 39.24 37.33 35.09 37.97 Size & Industry 33.66 31.12 29.66 29.71 Match p-value 0.149 0.113 0.175 0.050 Size, Btm and 29.93 30.63 27.13 31.20 Return Match p-value 0.016 0.091 0.045 0.112 Barber & Lyon 32.67 35.03 33.10 35.06 Match p-value 0.088 0.559 0.617 0.492

54 Table 6: Corporate events surrounding hedging transactions The Table provides the frequency of various corporate events for firms whose insiders engage in hedging transaction during the period 1996 to 2006. The control group is size (measured by book value of assets), Btm, defined as the ratio of boo- to-market value of common equity, and return-matched firms drawn from the intersection of CRSP and Compustat. Shareholder litigation data is obtained from Securities Class Action Clearinghouse website (SCAC) (http://securities.stanford.edu/). Earnings restatements data is obtained from the website of General Accounting Office (GAO) office of the U.S. Government. A negative earnings surprise occurs when the actual annual earnings per share (EPS) is below the last analyst EPS forecast prior to the actual release of earnings. Data for actual and forecasted earnings is obtained from I/B/E/S. For each firm, we define pre- and post- event windows that are the calendar days before and after the day of the event.. We run a linear probability model of the occurrence of a corporate event on: Sample, Post and Sample*Post. Sample takes the value one if the firm’s insiders use hedging instruments, and zero otherwise. Post takes the value one if the period follows the hedging transaction, and zero if the period precedes the hedging transaction. Sample*Post is the coefficient estimate from the above linear probability model and p- value is displayed to denote statistical significance of Sample*Post. Standard errors are corrected for heteroskedasticity and clustering at the firm level.

Panel A: Shareholder Litigation Zero Cost Collars Variable Forwards Exchange Funds Equity Swaps

[-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2]

Sample 3.99 16.61 27.91 6.28 10.95 19.93 3.47 7.73 20.00 8.82 2.94 5.88 Size/Industry Match 5.65 3.65 8.64 3.23 5.57 11.49 2.93 4.00 10.13 0.00 5.88 8.82 Sample*Post 0.146 0.209 0.023 0.053 0.032 0.093 −0.117 −0.117 p-value 0.000 0.000 0.395 0.224 0.261 0.016 0.217 0.217 Size/Btm/Retun Match 4.65 6.98 10.63 3.59 2.51 6.28 2.93 5.87 10.67 0.00 2.94 2.94 Sample*Post 0.102 0.179 0.057 0.109 0.013 0.088 −0.088 −0.058 p-value 0.009 0.000 0.041 0.003 0.658 0.018 0.271 0.494

Panel B: Earnings Restatements Zero Cost Collars Variable Forwards Exchange Funds Equity Swaps

[-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2]

Sample 1.33 5.32 9.97 2.69 4.49 12.03 3.47 2.40 6.93 5.88 2.94 8.82 Size/Industry Match 2.99 2.99 6.64 8.08 5.39 8.80 1.87 2.67 7.73 5.88 0.00 0.00 Sample*Post 0.039 0.049 0.044 0.086 −0.018 −0.024 0.029 0.088 p-value 0.071 0.231 0.076 0.003 0.237 0.341 0.347 0.114 Size/Btm/Retun Match 2.66 2.33 4.65 3.05 2.24 4.49 1.87 3.20 6.67 5.88 8.82 11.76 Sample*Post 0.043 0.066 0.021 0.078 −0.024 −0.013 −0.058 −0.029 p-value 0.057 0.077 0.148 0.001 0.128 0.560 0.432 0.715

Panel C: Negative Earnings Surprises Zero Cost Collars Variable Forwards Exchange Funds Equity Swaps

[-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2] [-1,0] [0,+1] [0,+2]

Sample 19.16 27.68 43.49 26.37 31.21 48.24 25.77 26.12 45.56 43.75 12.50 43.75 Size/Industry Match 39.84 33.73 53.75 31.74 28.37 47.92 36.81 29.25 49.19 40.91 27.27 54.55 Sample*Post 0.146 0.104 0.082 0.056 0.079 0.074 −0.176 −0.136 p-value 0.052 0.147 0.123 0.306 0.175 0.230 0.404 0.630 Size/Btm/Retun Match 26.75 23.81 50.84 27.33 34.10 57.02 29.47 27.34 42.86 25.00 38.10 47.62 Sample*Post 0.114 0.002 −0.019 −0.078 0.024 0.064 −0.443 −0.226 p-value 0.090 0.973 0.689 0.144 0.647 0.307 0.114 0.374

55 Table 7: Effect of hedging on CEO pay-performance sensitivity The table provides estimates from an OLS regression of change in CEO pay. The dependent variable is the change in CEO total pay (in $ thousands) where total pay is defined as cash compensation plus the Black-Scholes value of new options awarded plus the value of restricted stock awards and long-term incentive payments, plus the change in the value of existing stock options and shares. Sample takes the value 1 if the CEO is employed by the hedging firm, and 0 if employed by control firm. Control group CEOs are chosen from firms matched with hedging firms on size (measured by book value of assets) and industry (2-digit SIC code) drawn from the intersection of CRSP, Compustat and Execucomp. Post takes the value one if the year is the year of or year after the hedging transaction (Years 0 or +1), and zero if the year precedes the hedging transaction (Year –1). Chgshwealth (in $ million) is the change in shareholder wealth during a year and is defined as the beginning-of-the-year market capitalization multiplied by the annual stock return during the year. Chgshwealth for CEOs that hedge is adjusted in Years 0 and +1 to account for contractual features of the hedges that are put in place. Total risk (measured by the variance of stock returns) is decomposed into a systematic and an unsystematic component using the monthly market model regression using data from the 60 months prior to the current year. Unsystematic risk is the mean-squared error from the market model regression and systematic risk is the beta-squared multiplied by the variance of market returns. The risk measures are then converted to dollar risk measures by multiplying the percentage risk measures by the square of the beginning-of-the-year market capitalization. Unsysrisk and Sysrisk are dollar risk measures. Market-to-book ratio is defined as the sum of market value of equity and book value of total liabilities divided by the book value of assets. Cumulative distribution function (cdf) measures are obtained by ranking the observations and transforming the ranks such that they lie uniformly between 0 and 1. Standard errors are corrected for heteroskedasticity and clustering at the firm level. Absolute values of t-statistics are reported in parentheses. ***, **, and * denote significance at less than 1%, 5%, and 10% levels, two-tailed tests, respectively.

Model: (1) (2) Collars, Forwards Collars and and Swaps Forwards Intercept 48,816.540** 44,096.220* (2.11) (1.74) Chgshwealth 52.606*** 45.441*** (3.21) (3.10) Chgshwealth × sample 14.568** 15.319** (2.09) (2.13) Chgshwealth × sample × post −18.056** −17.784** (2.28) (2.15) Chgshwealth × post 6.729 4.555 (1.17) (0.75) Chgshwealth × cdf of unsysrisk −86.931*** −76.134*** (3.17) (3.05) Chgshwealth × cdf of sysrisk 27.559 30.563 (1.31) (1.51) Chgshwealth × cdf of market-to-book 17.138* 12.429 (1.77) (1.40) Cdf of unsysrisk 17,276.280 13,782.480 (0.81) (0.65) Cdf of sysrisk −16,925.390 −12,678.270 (0.73) (0.54) Cdf of market-to-book −20,003.850* −24,729.950** (1.83) (2.16) Sample −1,682.503 517.073 (0.35) (0.11) Post 10,129.220* 9,745.948* (1.84) (1.81) Industry Fixed Effects Yes Yes Year Fixed Effects Yes Yes Adj. R-square 0.455 0.457 N 397 389

56 Table 8: Univariate comparison of hedging firms and control firms The table provides differences in mean and median firm characteristics between hedging firms and control firms during the period 1996 to 2006. Hedging firms are firms whose insiders use exchange funds, zero-cost collars, and prepaid variable forwards. Control group is size (measured by book value of assets) and industry (2-digit SIC code) matched firms drawn from the intersection of CRSP, Compustat and IRRC. Insider ownership is ownership by all officers and directors of the firm. The Student’s t-test (Wilcoxon rank-sum test) is used to test whether there is a statistically significant difference between the means (medians). Absolute values of these statistics are reported in the table. ***, **, and * denote significance at less than 1%, 5%, and 10% levels, two-tailed tests, respectively.

Panel A: Zero Cost Collars Sample Control t-stat Wilcoxon Z Firms firms Mean Mean (Means) (Medians) Dummy equal to one if the firm went public in prior two years 0.149 0.013 4.51*** 4.37*** Fraction of outside directors on the board 0.504 0.623 4.84*** 4.56*** Number of directors on the board 9.071 8.798 0.76 0.97 Dummy equal to one for firms where CEO is chairman of board 0.551 0.597 0.80 0.80 Dummy equal to one if there is a new CEO in office 0.071 0.084 0.42 0.42 Insider Ownership 0.188 0.110 4.39*** 5.60*** Ownership of all institutions with ownership greater than 5% 0.154 0.155 0.04 0.28

Panel B: Exchange Funds Sample Control t-stat Wilcoxon Z Firms firms Mean Mean (Means) (Medians) Dummy equal to one if the firm went public in prior two years 0.217 0.060 4.97*** 4.84*** Fraction of outside directors on the board 0.530 0.638 5.87*** 5.40*** Number of directors on the board 9.465 9.191 0.83 1.20 Dummy equal to one for firms where CEO is chairman of board 0.617 0.634 0.38 0.38 Dummy equal to one if there is a new CEO in office 0.060 0.030 0.118 1.56 Insider Ownership 0.226 0.120 5.93*** 5.48*** Ownership of all institutions with ownership greater than 5% 0.127 0.156 2.45** 2.42***

Panel C: Forwards Sample Control t-stat Wilcoxon Z Firms firms Mean Mean (Means) (Medians) Dummy equal to one if the firm went public in prior two years 0.137 0.032 4.82*** 4.73*** Fraction of outside directors on the board 0.525 0.661 8.94*** 8.19*** Number of directors on the board 8.865 8.958 0.42 0.16 Dummy equal to one for firms where CEO is chairman of board 0.602 0.592 0.24 0.24 Dummy equal to one if there is a new CEO in office 0.038 0.057 1.12 1.12 Insider Ownership 0.183 0.130 4.01*** 5.85*** Ownership of all institutions with ownership greater than 5% 0.137 0.170 3.19*** 3.25***

57 Table 9: Investment and financial policy surrounding hedging transactions This table provides details of investment and financial policy surrounding the use of hedging instruments during the period 1996 to 2006. Control firms are selected by matching with hedging firms by book value of assets and 2-digit SIC code. We run a regression of each of the investment and policy measures on: Sample, Post and Sample*Post. Sample takes the value one if the firm’s insiders use hedging instruments, and zero otherwise. Post takes the value one if the year follows the hedging transaction (Years +1 or +2), and zero if the year precedes the hedging transaction (Year –1). Year 0 is the fiscal year of the hedging transaction. Leverage is total long-term debt divided by book value of total assets. Investments is the sum of R&D, advertising and capital expenditures. Volatility is defined as the standard deviation of daily stock return. Standard errors are corrected for heteroskedasticity and clustering at the firm level.

Year –1 Year +1 Year +2

R&D/Total Assets Mean Sample 0.039 0.041 0.047 (Median) (0) (0) (0) Mean Control 0.034 0.036 0.038 (Median) (0) (0) (0) Coefficient on Sample*Post −0.000 0.003 p-value 0.847 0.516

Leverage Mean Sample 0.195 0.181 0.179 (Median) (0.133) (0.122) (0.124) Mean Control 0.198 0.210 0.208 (Median) (0.151) (0.169) (0.166) Coefficient on Sample*Post −0.025 −0.025 p-value 0.037 0.040

Investments/Total Assets Mean Sample 0.114 0.113 0.116 (Median) (0.086) (0.084) (0.082) Mean Control 0.104 0.097 0.096 (Median) (0.075) (0.071) (0.071) Coefficient on Sample*Post 0.006 0.009 p-value 0.336 0.157

Standard deviation of daily stock returns Mean Sample 0.036 0.036 0.032 (Median) (0.032) (0.028) (0.026) Mean Control 0.035 0.034 0.031 (Median) (0.030) (0.028) (0.026) Coefficient on Sample*Post 0.001 0.000 p-value 0.395 0.795

58 Table 10: Hedging and CEO taxable income The table provides estimates from an OLS regression of CEO taxable income. The dependent variable is taxable income (in $ 000’s) which is defined as the sum of salary, bonus, value of stock options exercised, and long-term incentive payout (LTIP). Sample takes the value 1 if the CEO is employed by the hedging firm, and 0 if employed by control firm. Control group CEOs are chosen from firms matched with hedging firms on size (measured by book value of assets) and industry (2-digit SIC code) drawn from the intersection of CRSP, Compustat and Execucomp. Market-to-book ratio is the sum of market value of equity and book value of total liabilities divided by the book value of assets. Stock return is annual compounded raw returns. Volatility is the (annualized) standard deviation of monthly stock returns using five years of data. All independent variable are lagged by a year. Standard errors are corrected for heteroskedasticity and clustering at the firm level. Absolute values of t-statistics are reported in parentheses. ***, **, and * denote significance at less than 1%, 5%, and 10% levels, two-tailed tests, respectively.

Model: (1) (2) (3) Taxable Income: Taxable Income: Taxable Income: Year Before Hedging Year of Hedging Year After Hedging (in $ 000’s) (in $ 000’s) (in $ 000’s) Intercept 3,136.080 −1,577.761 −2,619.751 (0.71) (0.51) (0.77) Sample 3,200.286*** 2,283.068* 3,251.365*** (2.85) (1.95) (2.61) Book value of assets (in $ mill) 0.108 0.290*** 0.246** (1.09) (3.32) (2.25) Market-to-book ratio 637.696 543.186 528.536 (1.19) (1.13) (1.06) Stock Return 4,419.067** 2,731.570 1,593.071 (2.22) (1.55) (1.06) Volatility −11,175.39** 4,957.122 548.296 (2.44) (1.09) (0.16) Industry Fixed Effects Yes Yes Yes Year Fixed Effects Yes Yes Yes

Adj. R-square 0.210 0.118 0.096 N 294 334 339

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