CEO hedging opportunities and the weighting of performance measures …conference/conference2012/... · 2012-12-20 · Taychang Wang* Department of Accounting National Taiwan University

CEO hedging opportunities and the weighting of performance measures in compensation

Shengmin Hung

Department of Accounting

Soochow University

[email protected]

Hunghua Pan


National Taiwan University

[email protected]

Taychang Wang*


National Taiwan University

[email protected]

November 9, 2012

* Corresponding author.

mailto:[email protected]

CEO hedging opportunities and the weighting of performance measures in compensation

Abstract

Ideally, managerial ownership and short-sale constraints make managers bear firm-specific risk,

leading them to prioritize shareholder interests. However, corporate managers can easily hedge their

ownership positions, thereby avoiding firm-specific risk. In the context of managerial hedging, we

examine whether corporate boards take advantage of accounting-based performance measures, which

can be observed ex post, to develop efficient incentive schemes ex ante that will induce managers to

take desired actions. We first investigate the effect of CEO hedging opportunities or hedging cost and

performance measures on compensation, considering the relative weighting of accounting- and

stock-based performance measures. We find that when managerial hedging cost is low, compensation

is more sensitive to accounting-based than stock-based performance measures. Additionally, the

effect of the interaction between managerial hedging opportunities and accounting-based

performance measures on compensation increases with managerial hedging needs (represented by

managerial ownership and firm-specific risk). Overall, our study relies on the contract theory to

provide evidence that given managerial hedging, accounting information plays an important role in

compensation design.

Keywords: Executive compensation; Managerial hedging; performance measurement

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1. Introduction

Managers are incentivized by compensation schemes to maximize shareholder profit only when

they cannot use third parties to unwind their incentives (Tirole, 2006). In fact, compensation schemes

prohibit managers from undoing their positions in firms through secret or open trading.1 In addition,

managers may be required to forfeit any profit from the short selling of their firm’s stocks. Unlike

shareholders, managers cannot hold perfectly diversified portfolios (Lambert et al., 1991). Although

managers can buy stocks from other firms without legal constraints, holding perfectly diversified

portfolios remains a challenge for them because these portfolios are relatively expensive. Campbell

et al. (2001) demonstrate that risk-neutral investors need to achieve relatively complete portfolio

diversification by about fifty randomly selected stocks. Moreover, a large amount of managerial

wealth depends on firm performance. It is more difficult for managers to diversify the risk of a firm.

Ideally, managerial ownership and short-sale constraints make managers bear firm-specific risk,

leading them to prioritize shareholder interests.

Nonetheless, third parties, including investment banks and options markets, provide channels for

managers to insulate against the adverse effects of stock price movements. Given a premium, third

parties are willing to hold the position opposite that of managers at the expense of stakeholders, who

cannot depend much on compensation schemes to induce managerial efforts. The types and trading

strategies of derivative instruments are becoming increasingly innovative, and corporate managers

can now easily hedge their stock ownership positions. Bettis et al. (2001) estimate that about 30% of

shares held by top executives are hedged by derivative instruments. Jagolinzer et al. (2007) find that

corporate insiders utilize prepaid variable forwards (PVFs) to diversify their positions in anticipation

of poor performance. Furthermore, Bettis et al. (2012) find that most corporate boards do not ban

1 Section 16 (c) of the Securities and Exchange Act of 1934 makes it illegal for managers to short sell their shares in

firms. Specifically, it states that “it shall be unlawful for any such beneficial owner, director, or officer, directly or

indirectly, to sell any equity security of such issuer (other than an exempted security) (1) does not own the security sold,

or (2) if owning the security, does not deliver it against such sale within twenty days thereafter, or does not within five

days after such sale deposit it in the mails or other usual channels of transportation.”

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insiders from using derivative instruments.2 In fact, stock price becomes more and more important

in compensation setting (Armstrong et al., 2010). Whenever managers can easily hedge firm-specific

risk, the interests of managers and shareholders are no longer aligned. The reason is that, ceteris

paribus, firms evaluate managerial performance by only stock prices. When stock prices go up,

managerial wealth and firm valuation increase. On the other hand, when stock prices go down, firm

valuation decreases, but managers can use derivative instruments to cover their losses without

worrying about the negative effects of stock price movements on their wealth.3

To alleviate managerial moral hazards associated with managerial hedging, firms must design

performance-based compensation schemes that can partly align the interests of investors and

managers. Hölmstrom (1979) demonstrates that the efficiency of compensation mechanisms can be

improved if one performance measure can provide additional information on the actions of agents in

relation to original performance measures. The literature suggests that both stock- and

accounting-based performance measures are important in creating incentives for CEOs (Armstrong

et al., 2010; Baber et al., 1998; Cheng, 2004; Cheng and Indjejikian, 2009; Davila and Penalva, 2006;

Lambert, 2001; Lambert and Larcker, 1987; Ozkan et al., 2012; Sloan, 1993). Bushman and Smith

(2001) conclude that stock price information is becoming increasingly important in compensation

contracts. In addition, Armstrong et al. (2010) assert that stock price is a dominant measure in

compensation. Jayaraman and Milbourn (2011) use the market microstructure theory to demonstrate

that the pay-for-performance sensitivity (PPS) of CEOs to stock-based performance measures

increases with stock liquidity. Compared with these studies, we focus on the role of accounting

information, which is useful for performance evaluation and stewardship, in managerial

2 Due to the growing concern about the insiders’ use of derivative instruments, Bettis et al. (2012) find that prior to 2006

on average only one firm a year discloses bans of these instruments; nonetheless, the number of firms banning the use of

these instruments rises to 151 in 2006. In spite of the increasing in the use of these instruments, Bettis et al. (2012) still

conclude that “the number of firms that restrict the use of these [instruments], at least formally, still appears to be

small ”(p.35).

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compensation.4 Understanding their inability to obtain full information on managerial actions,

corporate boards use accounting-based performance measures, which can be observed ex post, to

develop efficient incentive schemes ex ante that will induce managers to take desired actions.

Therefore, this study tries to investigate the stewardship role of accounting information given

managerial hedging.

In the context of managerial hedging, stock-based performance measures cannot offer enough

incentive for managers to work hard. Regardless of the performance of stock price, managers can

win a fortune if they can utilize derivative instruments to undo the link between performance

measures and incentives. Meanwhile, compared with stock-based performance measures,

accounting-based performance measures cannot be undone by hedging strategies because the

underlying asset of derivative instruments is stock price, not accounting earnings. In addition, the

literature demonstrates that accounting- and stock-based performance measures have different

functions in compensation (Bushman and Smith, 2001; Core et al., 2003b; Lambert and Larcker,

1987). Bushman and Smith (2001) illustrate that accounting information can rebalance managerial

efforts across multiple activities. When managerial hedging is easy and firms rely on stock price

information to reward managers, managers may have the incentive to invest in projects that are too

risky for shareholders. If these investment projects earn positive cash flows in the end and stock

prices subsequently increase, managerial compensation may increase. In contrast, if the projects fail

and stock prices decrease, managers can use derivative instruments to cover their losses. Corporate

boards consequently design compensation schemes wherein accounting-based performance carries

more weight than stock-based performance. The incentive effect of stock-based performance is

reduced by managerial hedging, and the high sensitivity of compensation to accounting-based

performance measures can induce managers to avoid extravagant investment that is detrimental to

4 Kothari et al. (2010) define stewardship as “the role of the accounting system in ensuring that a firm’s invested capital

is maintained in such a way as to preserve the economic interest of shareholders and bondholders.” (p. 248)

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shareholder interest. More weight is placed on accounting-based than on stock-based performance in

compensation.

We follow Gao (2010) and use the indicator whether a firm has option trading in the option

market and average daily trading options volume to proxy for the hedging cost of a firm. The rational

is simple. When firm’s option is publicly tradable, managers have more accesses to use derivative

instruments to undo their incentive. It is beneficial because the indicator whether a firm has option

trading in the option market is an exogenous variable. Mayhew and Mihov (2004) find that the

decision for firms to have option markets is determined by options exchanges, not by firms

themselves.5 Higher daily trading options volume means that it is easier and more convenient to

execute hedging activities.

Meanwhile, corporate boards also understand the motivation behind managerial hedging.

Panousi and Papanikolaou (2012) indicate that managers holding large shares in firms bear more

firm-specific risk compared with those holding small shares, giving them more incentive to hedge.

Following this logic, corporate boards recognize that managers have more incentive to hedge when

they bear more firm-specific risk. In considering firm-specific risk in our research design, we use the

capital asset pricing model (CAPM) to decompose total risk into systematic risk and firm-specific

risk. We predict that managerial compensation is designed to put more weight on accounting-based

performance when managerial hedging cost is low and managerial hedging needs are high.6

In our cross-sectional results, we find that when managerial hedging cost is low, managerial

compensation places more emphasis on accounting-based than on stock-based performance. In

addition, we sort managerial ownership into three groups (“low own,” “medium own,” and “high

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Moreover, using the insider trading database of Thomson Reuters, we find in our sample 79 CEO-year observations

which CEOs purchase equity swaps, forward sales, or put options during 1996-2010. To further analyze, we find that a

CEO is more likely to execute explicit hedging transactions when the firm has options trading in option market. These

results support the effectiveness of our proxies for executive hedging cost. 6 We use the terms “hedging cost” and “hedging opportunities” interchangeably.

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own” groups) and find that the coefficient of the interaction between accounting-based performance

and managerial hedging cost monotonically increases with managerial ownership. We also divide our

sample into three groups based on firm-specific risk (“low risk,” “medium risk,” and “high risk”

groups) and find that the coefficient of the interaction between accounting-based performance and

managerial hedging cost monotonically increases with firm-specific risk. Furthermore, we construct

nine groups from interactions between the three firm-specific risk groups and three managerial

ownership groups, and find that when firm-specific risk is high and managerial hedging cost is low,

the weighting of accounting-based performance in compensation increases with managerial

ownership.

We also run tests to examine the robustness of our results. Specifically, we change the measures

of accounting- and stock-based performance, use the dollar value of managerial ownership to

substitute for managerial ownership, rule out alternative explanations related to firm characteristics,

exclude the possibility that our results are caused by high bonus-based compensation in our sample,

and control for the effect of managerial risk appetite. The results survive most of the robustness

checks.

This paper makes several contributions to the literature. First, although Bushman et al. (1998)

find that accounting information has gradually become less important in setting managerial cash

compensation, we show that accounting information is still useful in setting managerial

compensation (both cash compensation and total compensation) when managers can use derivative

instruments to unwind their incentives. To the best of our knowledge, this is the first paper that

empirically examines the importance of accounting information in managerial compensation in the

context of managerial hedging. Second, we prove that managerial hedging needs, represented by

managerial ownership and firm-specific risk, affect the interaction between managerial performance

and hedging cost. This paper shows that the effect of the interaction between accounting information

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and managerial hedging cost on compensation increases with the level of managerial hedging needs.

Finally, we find that firm-specific risk encourages corporate boards to design compensation schemes

that emphasize accounting-based performance, probably because they recognize that managers tend

to hedge firm-specific risk. All our results prove that corporate boards utilize accounting-based

performance measures, which can be observed ex post, to develop efficient incentive schemes ex

ante that will induce managers to take desired actions.

The article proceeds as follows. Section 2 reviews the literature and presents the research

hypotheses on the relationship between managerial hedging cost and the relative weighting of

accounting- and stock-based performance measures in compensation. Section 3 describes the data

and presents summary statistics, and Section 4 presents the primary results. Section 5 concludes the

paper.

2. Literature Review and Hypothesis Development

2.1 Background on Managerial Hedging

Compared with systematic risk, firm-specific risk plays a more crucial role in compensation

because it affects the appetite of managers. If managers hold well-diversified portfolios, they will

maximize the value of their portfolios, not the value of firms or their compensation (Aggarwal and

Samwick, 1999; Tirole, 2006).7 Some studies consider how managers can avoid risk exposure. Jin

(2002) documents that CEO compensation is related to stock market performance and finds that

managers can fully adjust their systematic risk exposure by trading market portfolios.8 Garvey and

Milbourn (2003) assert that the use of relative performance evaluation (RPE) is related to the ability

7 We emphasize managerial hedging not corporate hedging because the objective of corporate risk management is not to

provide managers with insurance. The types of risk management policies in firms are highly correlated to industry

attributes (Tufano, 1996). Our regression model controls industry effects. In addition, Guay and Kothari (2003) find that

only a small number of non-financial firms use derivatives to manage corporate risk. 8 To be precise, managers can very easily short market indices, such as S&P 500 Index, NASDAQ Composite, and Dow

Jones Industrial Average.

http://en.wikipedia.org/wiki/Nasdaq_Composite

http://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

http://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

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of managers to hedge market risk. Accordingly, most managers can adjust their exposure to market

risk easily and thereby reduce the use of RPE for managerial compensation. Furthermore, Acharya

and Bisin (2009) find that managers can substitute systematic risk for firm-specific risk by

implementing investment projects. In this study, we focus on firm-specific risk, not systematic risk,

because systematic risk (the market comovement) is outside managerial control. Firm-specific risk is

related to managerial actions; that is, it is under managerial control (Hölmstrom and Milgrom, 1987).

Although managers cannot legally short sell their shares in firms, they can legally buy put

options provided that the amount of securities underlying the put equivalent position does not exceed

the amount of underlying securities they own by managers (Section 16 (c) of Securities and

Exchange Act of 1934 and Rule 16c-4). According to a Wall Street Journal article written by Schultz

and Francis (2001), managerial shares not sold after option exercise are often hedged in transactions

that do not generate taxable income and that are not reported to the SEC. Jagolinzer et al. (2007) find

that corporate insiders can utilize prepaid variable forwards (PVFs) to avoid the downside risk of

stock ownership. Bisin et al. (2008) theoretically conclude that the monitoring cost of the sensitivity

of firm performance to compensation increases when managers can hedge their compensation. In

addition, Gao (2010) claims that managers can exploit the options market to buy put options and

diversify firm-specific risk, so the pay-for-performance sensitivity (PPS) decreases with hedging cost.

The hedging market enhances the ability of managers to take risks while reducing their incentive to

work hard. Hence, an optimal contract should provide high-powered incentives to induce managerial

efforts. Furthermore, corporate boards should use other governance mechanisms to avoid managerial

agency problems in the context of managerial hedging. In this study, we consider how corporate

boards account for the use of managerial derivatives in determining the relative weighting of

performance measures in compensation.

Bettis et al. (2012) state that most corporate boards do not ban insiders from using derivative

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instruments. Indeed, Bettis et al. (2001) find that the reported insider trading data may be understated

due to the difficulty of identifying insider trading by SEC reporting rule, unclearness of the reporting,

and the innovation of new instruments. According to Smith and Eisinger (2004), the SEC doubts that

all corporate insiders disclose their sales to investors. Younglai (2009) states that a former director

of the SEC’s New York office emphasizes that “it is difficult for the SEC to detect insider trading

using derivatives because there is no central market and hence no ability to conduct real-time

surveillance.” In our research design, we follow Gao (2010) and use the indicator whether a firm has

option trading in the option market to measure managerial hedging cost.

2.2 Accounting- and Stock-based Performance Measures in Managerial Compensation

According to Hölmstrom (1979), a new effort-related performance measure that can provide

new information, which old performance measures cannot provide, is useful in evaluating managerial

actions. Therefore, the relative weight of measures is an issue. Banker and Datar (1989) demonstrate

that the relative weight of a performance measure in compensation is an increasing function of its

“signal-to-noise” ratio with respect to managerial efforts. Both accounting operating performance

and stock price are important measures for performance evaluation, so many studies discuss their

relative weighting in managerial compensation (Armstrong et al., 2010; Baber et al., 1998; Bushman

and Indjejikian, 1993; Cheng and Indjejikian, 2009; Davila and Penalva, 2006; Kim and Suh, 1993;

Lambert, 2001; Lambert and Larcker, 1987; Ozkan et al., 2012; Sloan, 1993).

Bushman and Smith (2001) review previous studies and conclude that stock price information is

becoming increasingly important in compensation contracts. Jayaraman and Milbourn (2011) find

that the PPS of CEOs to stock-based performance measures increases with stock liquidity. However,

accounting-based performance measures can filter out effort-unrelated noise in stock-based

performance measures and refocus managerial attention to activities that benefit firms. The volatility

of accounting earnings is much lower than that of stock returns, making accounting earnings more

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precise in evaluating managerial efforts. In addition, when managerial performance is evaluated from

multiple activities, accounting- and stock-based performance measures can induce managers to

rebalance their efforts on different activities (Bushman and Smith, 2001). In this study, we argue that

accounting information is very important in the context of managerial hedging. Managerial

incentives and stockholder interest can get misaligned when managers are rewarded based on

stock-based performance. When corporate boards evaluate managers only by stock-based

performance measures, managers will choose to adopt some extravagant investment projects that are

beyond shareholder expectations because the volatility of firm stock price is not relevant to

managerial wealth. Managers can be rewarded with bonuses when investment projects result in

positive cash flows, but they are not penalized when investment projects result in negative cash flows.

This asymmetric compensation mechanism emerges from the ability of managers to unwind their

incentives through derivative instruments. The ability is lost when corporate boards use

accounting-based performance measures, so managerial attention can be refocused to activities

related to the fundamental value of firms. Thus, corporate boards identify accounting-based

performance measures, which can be observed ex post, to develop efficient incentive schemes ex

ante that will induce managers to take desired actions. This leads to the following hypothesis:

Hypothesis1: Ceteris paribus, compensation is designed to emphasize accounting-based

performance more than stock-based performance when managerial hedging cost is low.

In this study, we try to prove the relationship between compensation schemes and the relative

weighting of stock- and accounting-based performance measures, considering managerial hedging

cost. Not every manager, however, wants to engage in hedging. For example, given no firm

ownership or low firm-specific risk, managers might have no incentive to hedge. On the other hand,

given large firm ownership or high firm-specific risk, managers have more incentives to execute

hedging transactions in options markets. Therefore, we use managerial ownership and firm-specific

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risk to represent managerial hedging needs, which must be controlled when we examine the

relationship between managerial hedging cost and compensation schemes. This leads to the

following hypothesis:

Hypothesis 2: Ceteris paribus, compensation is designed to emphasize accounting-based

performance more than stock-based performance when managerial hedging cost is low and

managerial hedging needs are high.

When managers can hedge easily, they maximize their portfolio value, not stockholder value.

Consequently, the interests of managers and shareholders become less aligned. Under this

circumstance, accounting-based performance measures are more effective than stock-based

performance measures in controlling managerial actions. In other words, when managers can hedge

firm-specific risk, the optimal contract should put more weight on accounting-based performance

measures than on stock-based performance measures because managers cannot hedge the risk of

accounting-based performance measures even though they can hedge the risk of stock returns. The

literature on the relative weighting of accounting-based and stock-based performance measures does

not consider the effect of managerial hedging behavior. In this study, we expect the use of

accounting-based performance evaluation as a defensive measure for firms to mitigate the

dysfunctional behavior of managers. We follow Gao (2010) and use two variables, (a) a dummy

indicating whether firms have options markets and (b) put options trading volume, as proxy variables

for managerial hedging cost or hedging opportunities. Therefore, if the cost for managers to hedge

firm-specific risk is low, corporate boards use accounting-based performance measures and enhance

managerial incentives.

Based on the preceding discussion, investigating the interactions between managerial hedging

cost and the relative performance weighting of accounting- and stock-based performance measures

becomes key to resolving the compensation issue. Therefore, to test Hypothesis 1, we examine the

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effects of these interactions on CEO compensation using the following equation:

where i indexes firms and t indexes year. Prior studies (Cheng and Indjejikian, 2009; Core et al.,

2003b; Davila and Penalva, 2006; Ozkan et al., 2012) on CEO compensation typically use two

measures of CEO compensation: cash pay (CashPay) and total direct compensation (TotalPay). The

dependent variable is the change in compensation measured by and

. The use of Return and is consistent with the measurement of accounting-

and stock-based performance in the compensation literature (Sloan, 1993). Year dummies and Fama

and French (1997) 48 industry dummies are used to control for year and industry variation in CEO

compensation schemes. If the results support Hypothesis 1, the coefficient of the interaction between

accounting-based performance and hedging cost should be larger than that between stock-based

performance and hedging cost, which means and .

To test Hypothesis 2, we sort our observations into three groups (“low own,” “medium own,”

and “high own” groups) based on the firm ownership of CEOs. We control for the effect of

managerial ownership on the motivation to hedge. Managers who hold more shares have more

incentive to hedge. Similarly, we sort our observations into three groups (“low risk,” “medium risk,”

and “high risk” groups) based on firm-specific risk to control for managerial hedging needs. We

expect the coefficient of the interaction between accounting-based performance and hedging cost to

increase with managerial hedging needs. Furthermore, we construct nine groups from the interactions

between the three firm-specific risk groups and three managerial ownership groups to examine which

factor—managerial ownership or firm-specific risk—induces corporate boards to design

compensation schemes that emphasize accounting-based performance measures.

2.3 Measurement of Variables

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Measures of compensation

CEO compensation is measured by CEO total pay (TotalPay) and CEO cash pay (CashPay).

CashPay includes a CEO’s salary and annual bonus, whereas TotalPay includes CashPay and

noncash pay including stock options, restricted stock, long-term incentive plans, and all other annual

compensation. Accounting-based performance is more important in setting CashPay than in setting

TotalPay, so prior studies exclusively focus on cash compensation (Gaver and Gaver, 1998; Lambert

and Larcker, 1987). We use cash compensation to make our study comparable to prior studies.

However, Bushman and Smith (2001) find that both the percentage of cash compensation in total

compensation and top executives’ PPS to cash compensation are decreasing. Core et al. (2003b)

document that little managerial incentive comes from cash pay and recommend that future studies on

performance measures use total compensation. Therefore, we follow recent studies (Cheng and

Indjejikian, 2009; Davila and Penalva, 2006; Ozkan et al., 2012) and use cash compensation and

total direct compensation as compensation measures. Furthermore, to mitigate the effect of

non-normal distributions, we use and ; that is, the change in the

log values of CashPay and TotalPay, respectively.

Measures of accounting- and stock-based performance

The literature indicates that CEO compensation is associated with stock- and accounting-based

performance measures (Baber et al., 1998; Bushman and Indjejikian, 1993; Bushman and Smith,

2001; Kim and Suh, 1993; Lambert and Larcker, 1987; Sloan, 1993). Following previous studies, we

use change in ROA as a proxy for accounting-based performance and stock returns as a proxy for

stock-based performance. ROA is computed as earnings before interest and taxes divided by the book

value of assets at the end of the fiscal year (Sloan, 1993). Annual stock returns (Return) are

calculated using monthly buy-and-hold returns. Our results are qualitatively the same if we use

earnings before interest, taxes, depreciation, and amortization or income before extraordinary items

in ROA calculation.

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Measures of managerial hedging cost

Following Gao (2010), the important explanatory variable in this study is the cost of managerial

hedging, which can be equivalently interpreted as the hedging cost managers have. Hedge(Dummy)

is used as a proxy for hedging cost and is equal to 1 if the firm’s options are traded in the six US

options exchanges; otherwise, it is equal to zero.9 The economic intuition behind this variable is that

managers can hedge easily and hedging cost is low when the firm’s options can be traded in options

markets.10

The second proxy is the firm’s options trading volume, Hedge(trading volume), which is

the natural log of the average daily options trading volume of the firm during the fiscal year.11

Intuitively, a high trading volume indicates the relative ease and convenience of trading the firm’s

options. If the firm does not have options traded in options markets, Hedge(trading volume) is equal

to zero. In this study, we emphasize managerial hedging cost through public options markets.

Control variables

The literature suggests a set of variables that affect compensation schemes. The following are

taken as control variables:

Var( ): The variance of over five years prior to the current year. Banker and

Datar (1989) define noise in performance measures as the effect of factors other than managerial

efforts. We use Var( ) to control for accounting-based performance unrelated to managerial

efforts.

Var(Return): This is the stock return variance over the past five years. Following Banker and

Datar (1989), we use Var(Return) to control for stock price performance unrelated to managerial

efforts.

9 The six exchanges are the American Stock Exchange, Boston Options Exchange, Chicago Board Options Exchange,

International Securities Exchange, Pacific Exchange, and Philadelphia Stock Exchange. 10

Gao (2010) mentions that the use of Hedge(Dummy) is beneficial because it is an exogenous variable. The decision of

firms to have options markets is determined by options exchanges, not by firms themselves (Mayhew and Mihov, 2004). 11

We do not separate call options from put options in calculating the average daily trading volume of options because

the demand for options trading is generated by investors who own the underlying assets and wish to write covered calls

or buy protective puts.

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Leverage: This is the book value of total debt divided by the book value of total assets. If the

equity value is larger than the debt value, the debt value and the equity value will have a flat

relationship. No matter how much value managers create, debt holders can only have fixed face

value. Hence, leverage affects managerial incentive, and we take leverage as a control variable

(Coles et al., 2006).

Size: Firm size is an important variable affecting compensation (Core and Guay, 2001, 2002;

Frydman and Saks, 2010). To control for firm size effect, we compute firm size by taking the natural

log of total assets.

Market-to-book ratio (MB): When companies are at the growth stage, shareholders have trouble

evaluating managerial decisions. Hence, companies give managers more stock-based compensation

(Yermack, 1995). We use MB to control for the growth opportunity of firms.

ln(Cash): Lack of cash may make firms substitute equity-based compensation for cash

compensation. Hence, the availability of cash plays an important role in deciding compensation

components (Hall and Liebman, 1998). We measure ln(Cash) as the natural log of cash and

short-term investment.

CEO tenure: Tenure may be associated with the risk appetite, reputation, and wealth of CEOs

(Chava et al., 2010). We measure CEO tenure as the time between fiscal year-end and the day the

executive becomes CEO.

Own: Panousi and Papanikolaou (2012) indicate that when CEO ownership is large, CEOs

suffer more from firm-specific risk. In addition, they may have more incentive to hedge.

Firm-specific risk: Hölmstrom and Milgrom (1987) assert that firm-specific risk is a sufficient

statistic indicating the action of agents. We calculate this measure by the average monthly standard

deviation of daily returns adjusted for market beta using a CAPM-based regression model.12

12 We also examine the robustness of our results to alternative measures of firm-specific risk. Specifically, we calculate

firm-specific risk from residuals using Fama and French (1993) three-factor model. These two measures of firm-specific

risk (derived by CAPM model and the three-factor model) are highly correlated, leading to qualitatively and

quantitatively similar results.

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Industry dummy and year dummy: Fama and French’s (1997) 48 industry dummies and year

dummies are used to control for industry and time variations in executive compensation schemes.

3. Data and Descriptive Statistics

We use the ExecuComp database as the source of CEO compensation data. We collect stock

returns from the Center for Research in Security Prices (CRSP), accounting information from

Compustat, and options trading data from OptionMetrics. OptionMetrics provides all US

exchange-listed equity options from January 1996, so our sample starts from fiscal year 1996 to 2010.

In addition, we remove financial firms (SIC codes 6000–6999) and utility firms (SIC codes

4900–4999). To mitigate the effect of outliers, we delete all continuous variables at the 1% level in

both tails of the distribution.

The final sample consists of 14,781 CEO-year observations from 1996 to 2010, 84.8% of which

have options traded on the US options markets (as compared to 74% in Gao (2010)).13

Not

surprisingly, most of the sample firms have options traded in options markets because ExecuComp

mostly covers S&P 1,500 firms. The log value of the average number of daily options contracts

traded in our sample is 4.673 (as compared to 5.09 in Gao (2010)).

We merge data from ExecuComp, CRSP, Compustat, and OptionMetrics, and the resulting

sample is presented in Table 1. Panel A of Table 1 presents summary statistics for all sample years,

and Panel B shows summary statistics based on whether or not companies have options traded in

options markets. We first present the levels of all annual compensation variables. As seen in Panel A,

the natural log values of ln(TotalPay) and ln(CashPay) are 7.899 and 6.825 on average, respectively.

Cash compensation is over half of total direct compensation. In addition, the mean values of

and are very close (0.058 and 0.066, respectively). The sample

firms have a mean stock return of 15.9% and of -0.3%. Although the mean is

13

Observations on cash pay and total compensation are different in ExecuComp. We obtain 14,781 CEO total

compensation-year observations and 15,127 CEO cash compensation-year observations. We use observations from total

compensation to report our sample statistics.

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negative, the positive average value of ROA (9.3%) suggests profitability.

Panel B of Table 1 indicates that the characteristics of CEO compensation in firms with and

without options markets are quite similar. For example, the median

( ) is 0.04 (0.074) in firms without options markets and 0.049 (0.068) in firms with

options markets. Furthermore, the median (Return) is 0% (8.7%) for firms without options

markets and 0.1% (8.6%) for firms with options markets. Panel B shows that performance measures

and compensation packages in firms both with and without options markets are quite similar.

However, hedging cost makes these two subsamples different; that is, hedging cost is low in firms

with options markets but high in firms without options markets.

The last rows of each panel in Table 1 present summary statistics on the characteristics of firms

and CEOs. Panel A shows that the sample includes mostly growing and big firms with mean MB of

3.366 and mean natural log of size of 7.271. Additionally, the sample firms are moderately leveraged

with mean leverage ratio of 20.7% and mean natural log of cash and short-term investment of 0.149.

The average variance of (Return) is 0.052 (0.480). Hence, in our sample, stock price

information is much noisier than accounting information. The average CEO tenure (CEO ownership)

is about 9 years (2.09%).

In Panel B of Table 1, we divide our sample firms into firms with and without options traded in

options markets. Characteristics, such as Var( ), Var(Return), Leverage, CEO tenure, ln(Cash),

Size, MB, and firm-specific risk, are very similar. CEO ownership (OWN) is different between the

two subsamples. The mean CEO ownership for firms with options traded in options markets is less

than that for firms without (1.827% vs. 3.581%).

We provide correlations between key variables in Table 2. Not surprisingly, CEO compensation

and accounting- and stock-based performance measures have strong and positive correlations. The

remaining correlations are typical of other compensation studies.

4. Empirical Tests

17

We present our main empirical results in this section.

4.1 Hedging Cost and Relative Weighting of Performance Measures in CEO Compensation

Table 3 presents results on the relationship between managerial hedging cost and the structure

of CEO compensation. Panel A reports results for when the options dummy variable, indicating

whether or not firms have options markets, is used as a proxy for managerial hedging cost.

Meanwhile, Panel B reports results for when average options trading volume is used as a proxy for

hedging cost. We report results using cash pay and total compensation as dependent variables. In

addition, when estimating PPS, we use OLS regression with robust standard errors clustered at

firm-level and fixed-effect regression. Managerial hedging behavior is affected by unobserved

personal characteristics, such as personal wealth, risk appetite, and liquidity needs, so we use

fixed-effect regressions to control for these unobserved factors. Furthermore, fixed-effect regressions

can control for other firm aspects affecting managerial compensation, such as risk management

policies.

Panel A presents results related to the change in cash pay as the dependent variable in OLS (first

column) and fixed-effect (second column) regressions. The coefficients of year and industry

dummies are not reported. If hedging cost affects the relative weighting of accounting- and

stock-based performance measures, at least one of the coefficients of the interaction between hedging

cost and performance measures will be statistically significant. We find that the interaction between

hedging cost and accounting-based performance ( ) is positive and statistically

significant for the cash pay compensation variable in both OLS and fixed-effect regressions,

supporting Hypothesis 1 and suggesting that the sensitivity of CEO compensation to

accounting-based performance increases when managers can hedge their positions. Specifically, the

coefficient of the interaction between Hedge and is 0.694 (t=5.399; first column). The

effect of managerial hedging on CEO performance-based compensation is sizable. Consider a CEO

with a median cash pay of $899,645 (e6.802

*1000) as reported in Table 1. The first column of Table 3

18

suggests that accounting-based performance increases by one standard deviation (0.082 from Table1),

so this CEO’s cash compensation increases by about $16,452 [(e0.082*0.221

-1)*899,645] when

managerial hedging cost is high. Meanwhile, the same CEO’s cash compensation increases by about

$70,097 [(e0.082*(0.221+0.694)

-1)*899,645] when managerial hedging cost is low. The “median” CEO

cash compensation comes more from accounting-based performance (about $53,645) when the CEO

is more likely to hedge. In addition, the interaction between hedging cost and stock-based

performance ( ) is statistically significant in neither OLS nor fixed-effect

regressions, suggesting that the sensitivity of CEO cash compensation to stock-based performance is

not related to managerial hedging behavior. The coefficient of the interaction between Hedge and

Return is 0.008 (t=0.446; first column).

Bushman and Smith (2001) find that both the percentage of cash compensation to total

compensation and top executives’ PPS to cash compensation have decreased in the last three decades.

Cash salary and bonuses provide managers with relatively low-powered incentives (Jensen and

Murphy, 1990). Core et al. (2003b) document that compared with cash compensation, total

compensation is more consistent with the theoretical principal–agent model in setting managerial

incentives. Therefore, we also use total direct compensation as a proxy for CEO compensation. Table

3 presents results related to the change in total direct compensation as a dependent variable in OLS

(third column) and fixed-effect (fourth column) regressions. The results are consistent with those

found when cash pay is used as a proxy. The interaction between hedging cost and accounting-based

performance ( ) is positive and statistically significant for the total compensation

variable in both OLS and fixed-effect regressions, but the coefficient of the interaction between

hedging cost and stock-based performance ( ) is not statistically significant.

Specifically, the coefficient of the interaction between Hedge and is 0.542 (t=2.853; third

column), whereas that between Hedge and Return is 0.024 (t=0.915; third column). Similarly,

consider a CEO with a median total direct compensation of $2,683,830 (e7.895

*1000) as reported in

Table 1. The third column of Table 3 suggests that accounting-based performance increases by one

19

standard deviation (0.082 from Table 1), so this CEO’s total compensation increases by about

$86,534 [(e0.082*0.387

-1)* 2,683,830] when managerial hedging cost is high. Meanwhile, this CEO’s

total compensation increases by about $212,438 [(e0.082*(0.387+0.542)

-1)* 2,683,830] when managerial

hedging cost is low. The “median” CEO’s total compensation comes more from accounting-based

performance (about $125,904) when the CEO is more likely to hedge. In Panel B, we use average

options trading volume, ln(trading volume), as a proxy for hedging cost. The results are similar to

those in Panel A.

These results are consistent with our expectation in Hypothesis 1 that when managers can hedge

firm-specific risk easily, firms design a counteracting compensation mechanism. The compensation

scheme is designed to put more weight on accounting-based than on stock-based performance. In the

case of accounting-based performance, managers cannot use stock options to diversify firm-specific

risk, leading them to bear the risk and share stockholder interest.

4.2 Hedging Cost and Relative Weighting of Performance Measures in CEO Compensation after

Considering Managerial Hedging Needs

To test Hypothesis 2, we control for the effects of managerial motivation to hedge, represented

by managerial ownership and firm-specific risk, on compensation schemes. Managers are more

likely to hedge given managerial ownership and firm-specific risk, so corporate boards design

compensation schemes that emphasize accounting-based performance.

First, we expect that managerial hedging behavior is affected by managerial ownership. We

collect CEO ownership data from ExecuComp. CEO ownership is reported by companies in their

proxy statements. We classify CEO ownership into three groups: a “low own” group (CEO

ownership below 0.010%), a “medium own” group (CEO ownership between 0.010% and 0.900%),

and a “high own” group (CEO ownership larger than 0.900%).14

The mean (median) levels of CEO

ownership for the “medium own” and “high own” groups are 0.350% (0.300%) and 7.000%

14

Firms are not required to disclose the percentage if it is below 0.010% because the ownership is not material. We

classify these firms under the “low own” group.

20

(3.040%), respectively. Table 4 and Table 5 show results given total direct compensation and cash

pay as dependent variables, respectively. We use the options dummy as a proxy for hedging cost in

Panel A and average options trading volume as a proxy for hedging cost in Panel B. In addition, we

report results from OLS (first to third columns) and fixed-effect (fourth to sixth columns)

regressions.

In the “low own” group (first and fourth columns of Panel A of Table 4), the interaction between

hedging cost and performance is not statistically and significantly correlated with total compensation,

suggesting that regardless of whether managerial hedging cost is high or low, accounting-based

performance does not play an important role in determining compensation when managerial hedging

needs are low. This is consistent with our expectation that when managers have underlying stocks in

firms, they have the incentive to hedge. Consequently, corporate boards emphasize accounting-based

performance when setting compensation as an internal control mechanism to curb managerial

hedging behavior. In the “medium own” group (second and fifth columns of Panel A), the interaction

between hedging cost and accounting-based performance is statistically significant (in both columns,

the coefficient is above 0.500). In the “high own” group (third and sixth columns of Panel A), the

interaction between hedging cost and accounting-based performance is also statistically significant

(in both columns, the coefficient is above 0.891). Meanwhile, the interaction between hedging cost

and stock-based performance is not significant in all regressions. The coefficient of the interaction

between hedging cost and accounting-based performance monotonically increases with managerial

ownership. These results support Hypothesis 2 that when managers own a larger proportion of shares,

they have higher hedging needs. Consequently, managerial compensation is designed to put more

weight on accounting-based performance. In Panel B, average options trading volume is used as a

proxy for hedging cost. The results are almost the same as those in Panel A, suggesting that our

results are robust.

In Table 5, cash pay is used as a proxy for CEO compensation. In Panel A, with the options

dummy as a proxy for hedging cost, the interaction between managerial hedging cost and

21

accounting-based performance is statistically significant regardless of the level of managerial

ownership because accounting-based performance is important in creating incentives more in terms

of cash pay than in terms of total pay (Gaver and Gaver, 1998; Lamber and Larcker, 1987). The

coefficient of the interaction between hedging cost and accounting-based performance monotonically

increases with managerial ownership in Panel A. In the OLS regression for example, the coefficient

of the interaction between hedging cost and accounting-based performance increases from 0.497 to

0.870. When the average options trading volume is used as a proxy for hedging cost in Panel B, the

results are consistent with aforementioned analyses and the coefficient of the interaction between

hedging cost and accounting performance also monotonically increases (from 0.033 to 0.115) with

managerial ownership. These results are consistent with our expectation. The amount of underlying

assets affects the managerial need to hedge.15

Second, we expect that managerial hedging behavior is affected by firm-specific risk. We

classify firms into three firm-specific risk groups: “low risk,” “medium risk,” and “high risk” groups.

The mean (median) levels for firms in the “low risk,” “medium risk,” and “high risk” groups are

1.310% (1.346%), 2.055% (2.034%), and 3.552% (3.236%), respectively. Table 6 and Table 7 show

the results when total direct compensation and cash pay are used as dependent variables,

respectively.16

Regardless of whether total compensation or cash compensation is used as a

dependent variable, the coefficient of the interaction between hedging cost and accounting-based

performance still monotonically increases with firm-specific risk. These results support Hypothesis 2

that the coefficient of the interaction between accounting-based performance and hedging cost

15

We also try to use interactions between hedging cost, managerial ownership, and performance measures to examine

whether managerial ownership affects the weighting of accounting-based performance in compensation. The results are

the same as those for sorted ownership groups (Table 4 and Table 5). We use sorted ownership groups in our main

analysis because firms are not required to disclose managerial ownership if managerial ownership is below 0.01%. Once

managerial ownership is below 0.01%, the value of managerial ownership in ExecComp is missing. To examine

interactions between hedging cost, managerial ownership, and performance measures, we need to replace the missing

value of managerial ownership with zero, but this does not mean that managerial ownership is zero. Therefore, we use

sorted ownership groups to investigate the effect of managerial hedging cost on the design of compensation schemes. 16

In calculating firm-specific risk using CAPM, the number of observations is reduced to 13,291 for total compensation

and 13,633 for cash compensation.

22

increases with managerial hedging needs.17

Finally, we construct nine groups from interactions between the three firm-specific risk groups

and three managerial ownership groups to examine which factor, managerial ownership or

firm-specific risk, leads corporate boards to design compensation schemes that emphasize

accounting-based performance. Table 8 shows that when firm-specific risk is high, the coefficient of

the interaction between accounting-based performance and hedging cost increases with managerial

ownership.18

For example, under OLS regression (Panel A of Table 8), when firm-specific risk is

high, corporate boards recognize that managers are more likely to hedge regardless of whether

managerial ownership is high or low. Therefore, the coefficient of the interaction between

accounting-based performance and hedging cost is positive and statistically significant: 0.293

(t-stat=1.233), 0.833 (t-stat=4.693), and 0.840 (t-stat=4.481) for the “low own,” “medium own,” and

“high own” groups, respectively. We further consider the effect of the increase in managerial

ownership on the design of compensation schemes. When firm-specific risk is high, the coefficient of

the interaction between accounting-based performance and hedging cost increases from 0.293 for the

“low own” group to 0.840 for the “high own” group. Panel B of Table 8 reports results with total

compensation as the dependent variable. The interaction between managerial hedging cost and

accounting-based performance is statically significant only in groups with high firm-specific risk and

high managerial ownership. Similar to results in Panel A, when firm-specific risk is high, the

coefficient of the interaction between accounting-based performance and hedging cost increases from

0.078 for the “low own” group to 1.169 for the “high own” group. These results confirm our

17

We also try to use interactions between hedging cost, firm-specific risk, and performance measures to examine

whether managerial ownership affects the weighting of accounting-based performance in compensation. However, the

interactions between hedging cost, firm-specific risk, and accounting-based performance (stock-based performance

measure) are statistically insignificant. These results are due to high collinearity in interactions between these variables

(the VIF values of interactions in our regression model are larger than 10). Therefore, we divide our sample into three

subsamples based on firm-specific risk. 18

When investigating managerial hedging needs in terms of both managerial ownership and firm-specific risk, we report

results using a dummy variable indicating whether the firm has options markets as the proxy for hedging cost. Results

using average options trading volume as a proxy for hedging cost are almost the same as those in Table 8. Therefore, we

do not tabulate results from the use of average options trading volume as the proxy for hedging cost.

23

prediction that high firm-specific risk leads managers to hedge and thereby draws the attention of

corporate boards.19

Taken together, our empirical results support the prediction that accounting-based performance

measures are used by companies as a control mechanism to prevent managers from using stock

options to avoid firm-specific risk. Whenever managers have less cost to hedge firm-specific risk,

corporate boards identify accounting-based performance measures, which can be observed ex post,

and use them to develop efficient incentive schemes ex ante that will induce managers to take desired

actions.

Robustness checks

The results are qualitatively the same if we use earnings before interest, taxes, depreciation, and

amortization or income before extraordinary items in ROA calculation. We also use industry-adjusted

returns to substitute for raw returns because industry-adjusted returns preclude the effect of the

business cycle on stock-based performance measures. The results are almost the same as those in

Table 3. However, when cash compensation is used as the dependent variable, the coefficient of the

interaction between hedging cost and stock-based performance becomes negative despite the

statistical insignificance. Moreover, to understand the dollar effect of managerial ownership on

compensation when managers can hedge easily, we multiply managerial ownership by the market

value of firms. We redo the analysis in Tables 4 and 5, and the results are almost the same. However,

when cash compensation is used as the dependent variable in fixed-effect regression, the coefficient

of the interaction between hedging cost and accounting-based performance no longer obviously

increases with the dollar effect of managerial ownership.

We need to rule out alternative explanations related to firm characteristics. Lambert and Larcker

(1987) find that firms put more weight on accounting-based performance in compensation under

three situations: when the variance of accounting-based performance measures is much lower than

19

We also use Ln(Volume) as proxy for hedging cost and rerun the analysis in Table 8. The untabulated results are

consistent.

24

that of stock-based performance measures; when firms are in the mature stage; and when managerial

ownership is high. In Panel B of Table 1, we divide our sample into firms without options markets

(representing high managerial hedging cost) and firms with options markets (representing low

managerial hedging cost). The mean of the variance of accounting-based performance, represented

by Var( ), and the mean of the variance of stock-based performance, represented by

Var(Return), of the two subsamples are qualitatively similar. Specifically, the mean values of the

variance of accounting- and stock-based performance are 0.055 and 0.430, respectively, in firms with

high managerial hedging cost. Meanwhile, the mean values of the variance of accounting- and

stock-based performance are 0.052 and 0.489, respectively, in firms with low managerial hedging

cost. From these sample statistics, we can rule out the possibility that the noise in accounting- and

stock-based performance measures in these two subsamples induces corporate boards to put more

weight on accounting-based performance in compensation. In addition, growth opportunity,

represented by MB, is higher in firms with low managerial hedging cost (3.537) than in firms with

high managerial hedging cost (2.414). Therefore, we exclude the second explanation that our results

are due to lower growth opportunities in firms with low managerial hedging cost. Furthermore, we

examine managerial ownership, represented by OWN, between these two subsamples. Managerial

ownership is lower in firms with low managerial hedging cost (1.827%) than in firms with high

managerial hedging cost (3.581%), leading us to preclude the explanation that our results come from

high ownership in firms with low hedging cost.

Bonus plans depend on accounting earnings (Healy, 1985). Murphy (2000) finds that 91% of his

sample firms use at least one measure of accounting profits in their annual bonus plans. We rule out

the explanation that our results come from the high percentage of bonuses in total compensation in

the subsample of firms with options markets. We analyze the bonus component of total compensation.

The result shows that the average percentage of bonuses in total compensation in firms without

options markets (16.8%) is higher than that in firms with options markets (13.3%), proving that our

main results in Table 3 are not due to bonus plans.

25

To control for the motivation of managers to hedge, we use managerial age (CEO age) and a

proxy for CEOs’ financial wealth (CEO wealth) to control for CEOs’ hedging cost and managerial

risk appetite. Younger managers or managers with less financial wealth are more likely to face

constraints in hedging; they have, for instance, fewer types or lesser amounts of available derivatives.

Meanwhile, older managers or managers with greater financial wealth are more flexible in hedging

transactions. We follow Garvey and Milbourn (2003) and use the sum of total compensation received

by CEOs over the past five years as a proxy for CEO financial wealth. Because we need at least six

years of CEO compensation observations in this robustness check, the number of our observations is

reduced to about 9,000. The results are shown in Table 9. After controlling for CEO age and wealth,

our results do not change; firms put more weight on accounting-based performance when managers

can hedge. Our findings are robust after considering alternative explanations and empirical designs.

5. Conclusion

The main contribution of this study lies in proposing that accounting-based performance

measures play an important role in the context of managerial hedging. When managers can hedge

easily, stock-based incentive schemes cannot offer them enough motivation to work hard. Compared

with stock-based performance measures, accounting-based performance measures cannot be hedged

by derivative instruments. We find that when managerial hedging cost is low, corporate boards

design compensation schemes that emphasize accounting-based more than stock-based performance.

Corporate boards take advantage of accounting-based performance measures, which can be observed

ex post, and use them to develop efficient incentive schemes ex ante that will induce managers to

take desired actions. Moreover, corporate boards recognize that managerial ownership and

firm-specific risk motivate managerial hedging. Compensation, therefore, is designed to put more

weight on accounting-based than on stock-based performance when managerial hedging cost is low

and managerial hedging needs are high.

26

Overall, we find that accounting information clarifies our understanding of how firms evaluate

managers in the context of managerial hedging. In this study, however, we do not focus on the effect

of corporate risk management policies on managerial hedging behavior. These policies can also

affect the design of managerial compensation schemes. To broaden our understanding of how

managerial incentives are used to avoid moral hazards, we suggest that future studies explore how

corporate risk management policies affect managerial hedging behavior.

27

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Table 1 Descriptive statistics on sample firms.

The sample consists of 14,781 firm-year observations from 1996 to 2010. In the sample, 12,532 firm-year observations have options

traded in US options exchanges. We obtain stock return data from CRSP, accounting data from Compustat, CEO compensation data

from ExecuComp, and options trading data from OptionMetrics. In Panel A, TotalPay is the natural log of Execucomp data item tdc1.

CashPay is defined as the natural log of the sum of data items annual salary and bonus. is the change in the natural

log of total pay. is the change in the natural log of cash pay. Hedge(Dummy) is equal to one if the firm has options

traded in US options markets; otherwise, it is zero. Hedge(Trading volume) is the natural log of the average daily options trading

volume of the firm during the fiscal year. Following Sloan (1993), is the change in return on assets, where ROA is income

before interest and taxes divided by total assets at the end of year. Return is monthly CRSP buy-and-hold return over the firm’s fiscal

year. Var( ) is defined as variance of over five years prior to the current year. Var(Return) is the stock return

variance over the past five years. Leverage is the book value of long-term debt, including the current position, divided by total assets.

CEO tenure is the time between fiscal year-end and the day the executive becomes CEO. ln(Cash) is the natural log of cash and

short-term investment. OWN is the ownership of CEOs as reported by companies in their proxy statements; firms are not required to

disclose the percentage if it is below 0.01%, so we replace missing values with zero. Size is defined as the natural log of total assets.

MB is the ratio of market value of equity to book value of equity measured at the end of the period. Firm-specific risk is measured by

the average monthly standard deviation of daily returns adjusted for CAPM. Panel B presents summary statistics on variables with and

without options markets.

Panel A: All sample year

Variables Mean S.D. Q1 Median Q3

CEO Compensation

ln(TotalPay) 7.899 1.107 7.168 7.895 8.625

ln(CashPay) 6.825 0.907 6.385 6.802 7.255

0.066 0.683 -0.239 0.069 0.404

0.058 0.615 -0.063 0.048 0.216

Explanatory Variables

Hedge(Dummy) 0.848 0.359 1.000 1.000 1.000

Hedge(Trading volume) 4.673 2.809 2.939 4.886 6.698

Return 0.159 0.571 -0.166 0.087 0.359

ROA 0.093 0.117 0.054 0.096 0.144

-0.003 0.082 -0.023 0.001 0.020

Other Variables

Var( ) 0.052 0.068 0.019 0.033 0.060

Var(Return) 0.480 0.386 0.241 0.369 0.580

Leverage 0.207 0.164 0.053 0.199 0.319

CEO tenure 8.589 7.536 3.000 6.000 11.000

ln(Cash) 0.149 0.169 0.024 0.081 0.219

OWN (%) 2.094 5.671 0.000 0.160 1.176

Size 7.271 1.532 6.186 7.136 8.259

MB 3.366 4.670 1.527 2.315 3.680

Firm-specific risk (%) 2.314 1.142 1.524 2.042 2.816

Panel B: Sample with and without options markets

Without options traded in markets With options traded in markets

Variables N Mean p50 N Mean p50

CEO Compensation

ln(TotalPay) 2249 7.070 7.028 12532 8.048 8.068

ln(CashPay) 2249 6.474 6.452 12532 6.888 6.856

2249 0.071 0.074 12532 0.065 0.068

2249 0.083 0.040 12532 0.053 0.049

Panel C. Payoff of a manager.

31

Explanatory Variables

Return 2249 0.177 0.087 12532 0.155 0.086

ROA 2249 0.065 0.081 12532 0.098 0.099

2249 -0.002 0.000 12532 -0.004 0.001

Other Variables

Var( ) 2249 0.055 0.031 12532 0.052 0.033

Var(Return) 2249 0.430 0.328 12532 0.489 0.378

Leverage 2249 0.204 0.196 12532 0.207 0.200

CEO tenure 2249 9.011 6.000 12532 8.513 6.000

ln(Cash) 2249 0.124 0.051 12532 0.153 0.087

OWN(%) 2249 3.581 0.500 12532 1.827 0.110

Size 2249 6.005 6.006 12532 7.498 7.391

MB 2249 2.414 1.726 12532 3.537 2.449

Firm-specific risk (%) 2249 2.551 2.170 12532 2.268 2.011

32

Table 2 Pearson correlations between compensation and performance variables.

Notations ***

, **

, and * denote statistical significance at 1%, 5%, and 10% levels, respectively.

Hedge(Dummy) Hedge(trading volume) Return

-0.023*** -0.029***

(0.000) (0.000)

-0.036*** -0.054*** 0.328***

(0.000) (0.000) (0.000)

Return -0.004** 0.002 0.125*** 0.118***

(0.026) (0.266) (0.000) (0.000)

0.002 0.002 0.022*** 0.019*** 0.043***

(0.211) (0.261) (0.000) (0.000) (0.000)

33

Table 3 Effect of relative weight and managerial hedging cost on CEO compensation.

This table reports firm-year observations from 1996 to 2010. Industry dummies are constructed based on 48 industries in Fama and

French (1997). Corresponding t-statistics are reported in brackets. The t-statistic for OLS regressions is based on robust standard errors

clustered at firm level. Notations ***, **, and * denote statistical significance at 1%, 5%, and 10% levels, respectively. All variables are

defined in Table 1.

Panel A: Using options dummy as the proxy for hedging cost

(1) (2) (3) (4)

OLS Fixed effect OLS Fixed effect

Constant 0.229*** 0.298*** 0.075 0.121

(6.344) (4.019) (1.310) (0.977)

Hedge 0.007 0.015 -0.017 -0.055**

(0.746) (0.894) (-1.317) (-1.984)

Return 0.134*** 0.139*** 0.166*** 0.141***

(7.813) (8.881) (7.252) (5.259)

0.221** 0.204*** 0.387*** 0.395***

(2.108) (2.808) (2.617) (3.241)

Hedge*Return 0.008 0.000 0.024 0.031

(0.446) (0.026) (0.915) (1.057)

Hedge* 0.694*** 0.765*** 0.542*** 0.558***

(5.399) (8.222) (2.853) (3.612)

Var( ) -0.013 0.008 -0.353*** -0.292*

(-0.248) (0.081) (-3.467) (-1.788)

Var(Return) -0.051*** -0.060*** -0.041** -0.022

(-6.107) (-4.130) (-2.494) (-0.891)

Leverage 0.056*** 0.094** -0.041 -0.112

(2.786) (2.186) (-1.384) (-1.561)

CEO tenure -0.005*** -0.009*** -0.000 -0.004***

(-11.748) (-11.509) (-0.763) (-3.163)

ln(Cash) 0.046** 0.101** 0.032 0.122

(2.032) (2.185) (0.891) (1.575)

Size -0.015*** -0.019* 0.011*** 0.016

(-6.501) (-1.767) (3.158) (0.863)

MB -0.002** -0.001 0.001 0.004**

(-2.403) (-0.927) (0.699) (2.279)

Year dummy Yes Yes Yes Yes

Industry dummy Yes No Yes No

Firm fixed effect No Yes No Yes

Observations 15,127 15,127 14,781 14,781

Adjusted-R2/Overall-R2 0.147 0.145 0.051 0.049

Panel B: Using Ln(Volume) as the proxy for hedging cost

(1) (2) (4) (5)


Constant 0.231*** 0.287*** 0.029 0.059

(6.067) (3.702) (0.484) (0.456)

Hedge -0.001 -0.005 -0.008*** -0.012**

(-0.424) (-1.334) (-2.938) (-2.131)

Return 0.125*** 0.122*** 0.157*** 0.136***

(8.192) (9.750) (7.259) (6.409)

0.383*** 0.387*** 0.516*** 0.511***

(2.655) (5.782) (3.095) (4.575)

Hedge*Return 0.004 0.004* 0.006 0.007*

(1.333) (1.744) (1.359) (1.761)

Hedge* 0.073*** 0.078*** 0.057* 0.063***

(2.796) (5.783) (1.702) (2.792)

34

Var( ) -0.016 0.009 -0.336*** -0.283*

(-0.327) (0.096) (-3.455) (-1.728)

Var(Return) -0.050*** -0.053*** -0.031* -0.012

(-5.698) (-3.588) (-1.856) (-0.477)

Leverage 0.053*** 0.080* -0.053* -0.126*

(2.614) (1.837) (-1.777) (-1.741)

CEO tenure -0.005*** -0.009*** -0.000 -0.004***

(-11.777) (-11.550) (-0.703) (-3.174)

ln(Cash) 0.047** 0.102** 0.049 0.127

(2.010) (2.196) (1.326) (1.628)

Size -0.013*** -0.013 0.020*** 0.024

(-4.156) (-1.147) (3.964) (1.233)

MB -0.002** -0.001 0.001 0.004**

(-2.405) (-0.889) (0.910) (2.312)




Observations 15,127 15,127 14,781 14,781


35

Table 4 Stratified CEO ownership and effect of relative weight and managerial hedging cost on CEO total compensation.

Panels A and B report 14,781 firm-year observations from 1996 to 2010. For Panel A, Hedge is a dummy variable. For Panel B, Hedge

is the average number of daily options contracts. Industry dummies are constructed based on 48 industries in Fama and French (1997).

Corresponding t-statistics are reported in brackets. The t-statistic for OLS regressions is based on robust standard errors clustered at

firm level. Notations ***, **, and * denote statistical significance at 1%, 5%, and 10% levels, respectively. All variables are defined in

Table 1.


(1) (2) (3) (4) (5) (6)

OLS OLS OLS Fixed effect Fixed effect Fixed effect

Low own Medium own High own Low own Medium own High own

Constant -0.037 0.198 0.179 -0.253 0.138 0.167

(-0.207) (0.991) (0.751) (-1.043) (0.534) (0.620)

Hedge -0.047 0.018 -0.011 -0.050 -0.015 -0.085

(-1.464) (0.555) (-0.362) (-0.877) (-0.272) (-1.602)

Return 0.211*** 0.167*** 0.130*** 0.080 0.148*** 0.105**

(3.933) (3.949) (3.590) (1.228) (2.906) (2.488)

0.629** 0.172 0.368* 0.842*** 0.057 0.399*

(2.474) (1.027) (1.873) (2.971) (0.280) (1.838)

Hedge*Return -0.006 0.033 0.028 0.085 0.018 0.062

(-0.108) (0.725) (0.709) (1.236) (0.328) (1.326)

Hedge* 0.263 0.507** 0.891*** -0.102 0.755*** 0.993***

(0.903) (2.281) (3.415) (-0.308) (2.818) (3.317)

Var( ) -0.333* -0.637*** -0.130 0.025 -0.305 -0.107

(-1.943) (-3.901) (-0.790) (0.069) (-0.991) (-0.308)

Var(Return) -0.028 -0.053* -0.047 0.029 -0.063 -0.048

(-0.919) (-1.738) (-1.568) (0.572) (-1.271) (-1.032)

Leverage -0.050 -0.036 -0.031 -0.184 0.054 -0.252*

(-0.743) (-0.510) (-0.422) (-1.387) (0.367) (-1.661)

CEO tenure -0.001 -0.001 -0.001 -0.005** 0.002 -0.007**

(-0.671) (-0.730) (-0.523) (-1.965) (0.687) (-2.318)

ln(Cash) -0.121 0.075 0.096 -0.047 0.347** 0.274*

(-1.549) (1.002) (1.222) (-0.307) (2.359) (1.669)

Size 0.020*** 0.001 0.008 0.070** -0.010 0.020

(2.866) (0.073) (0.768) (2.141) (-0.263) (0.464)

MB -0.003 0.004* 0.003 -0.001 0.011*** 0.003

(-1.509) (1.871) (1.075) (-0.269) (2.827) (0.739)

Year dummy Yes Yes Yes Yes Yes Yes

Industry dummy Yes Yes Yes No No No

Firm fixed effect No No No Yes Yes Yes

N 6215 4319 4247 6215 4319 4247

Adjusted-R2/Overall-R2 0.050 0.062 0.042 0.039 0.057 0.044


(1) (2) (3) (4) (5) (6)



Constant -0.113 0.225 0.142 -0.269 0.202 -0.027

(-0.617) (1.098) (0.591) (-1.079) (0.741) (-0.096)

Hedge -0.012** 0.001 -0.008 -0.000 0.005 -0.036***

(-2.018) (0.166) (-1.370) (-0.017) (0.459) (-3.017)

Return 0.178*** 0.164*** 0.137*** 0.099** 0.136*** 0.113***

(4.348) (4.745) (4.612) (2.075) (3.279) (3.274)

0.755*** 0.265* 0.540*** 0.674*** 0.184 0.534***

(3.476) (1.702) (2.941) (2.746) (0.973) (2.613)

Hedge*Return 0.005 0.007 0.004 0.010 0.008 0.009

36

(0.751) (1.200) (0.695) (1.365) (1.024) (1.403)

Hedge* 0.016 0.058* 0.102** 0.021 0.092** 0.127***

(0.404) (1.782) (2.439) (0.480) (2.331) (2.651)

Var( ) -0.296* -0.657*** -0.141 0.067 -0.366 -0.064

(-1.715) (-3.962) (-0.853) (0.184) (-1.193) (-0.185)

Var(Return) -0.016 -0.052* -0.038 0.030 -0.064 -0.031

(-0.521) (-1.651) (-1.228) (0.575) (-1.264) (-0.658)

Leverage -0.069 -0.038 -0.045 -0.176 0.066 -0.306**

(-1.009) (-0.536) (-0.602) (-1.311) (0.450) (-2.010)

CEO tenure -0.001 -0.001 -0.001 -0.005* 0.003 -0.007**

(-0.668) (-0.717) (-0.513) (-1.943) (0.694) (-2.357)

ln(Cash) -0.092 0.073 0.115 -0.045 0.334** 0.276*

(-1.140) (0.941) (1.445) (-0.295) (2.256) (1.686)

Size 0.032*** -0.000 0.018 0.066* -0.024 0.058

(3.061) (-0.037) (1.395) (1.895) (-0.566) (1.241)

MB -0.002 0.004* 0.003 -0.001 0.010*** 0.004

(-1.233) (1.776) (1.251) (-0.365) (2.624) (1.005)




N 6215 4319 4247 6215 4319 4247


37

Table 5 Stratified CEO ownership and effect of relative weight and managerial hedging cost on CEO cash compensation.





Table 1.


(1) (2) (3) (4) (5) (6)



Constant 0.178 0.276** 0.288** 0.150 0.269* 0.396***

(1.530) (2.453) (2.414) (0.932) (1.918) (2.759)

Hedge -0.004 0.020 0.006 0.057 0.074** -0.025

(-0.179) (1.118) (0.358) (1.498) (2.481) (-0.878)

Return 0.159*** 0.128*** 0.129*** 0.160*** 0.143*** 0.125***

(4.505) (5.378) (6.890) (3.717) (5.123) (5.877)

0.524*** 0.074 0.204** 0.377** 0.108 0.171

(3.132) (0.793) (1.973) (2.022) (0.967) (1.537)

Hedge*Return 0.022 -0.024 0.009 0.023 -0.059* 0.016

(0.589) (-0.955) (0.435) (0.510) (-1.955) (0.657)

Hedge* 0.497** 0.634*** 0.870*** 0.839*** 0.743*** 0.915***

(2.572) (5.099) (6.244) (3.830) (5.069) (5.849)

Var( ) 0.004 0.065 -0.077 0.111 0.031 0.145

(0.040) (0.723) (-0.896) (0.458) (0.186) (0.804)

Var(Return) -0.054*** -0.053*** -0.035** -0.064* -0.046* -0.053**

(-2.679) (-3.156) (-2.199) (-1.929) (-1.733) (-2.135)

Leverage 0.085* 0.017 0.069* 0.119 0.091 0.083

(1.899) (0.433) (1.720) (1.358) (1.143) (1.028)

CEO tenure -0.009*** -0.005*** -0.001** -0.014*** -0.004** -0.006***

(-8.163) (-4.620) (-2.291) (-8.164) (-2.238) (-3.720)

ln(Cash) 0.084 0.005 0.038 0.256** 0.033 0.089

(1.631) (0.117) (0.908) (2.527) (0.414) (1.024)

Size -0.024*** -0.011** -0.014** 0.001 -0.024 -0.044*

(-5.208) (-2.118) (-2.470) (0.057) (-1.138) (-1.894)

MB -0.003*** 0.000 -0.001 -0.002 0.001 -0.000

(-2.680) (0.210) (-0.851) (-1.240) (0.446) (-0.131)




N 6318 4416 4393 6318 4416 4393


Panel B: Using ln(Volume) as the proxy for hedging cost

(1) (2) (3) (4) (5) (6)


Constant 0.161 0.332*** 0.282** 0.187 0.308** 0.339**

(1.355) (2.876) (2.337) (1.128) (2.071) (2.256)

Hedge -0.004 0.007** -0.002 -0.001 0.007 -0.012*

(-1.146) (2.053) (-0.553) (-0.118) (1.177) (-1.868)

Return 0.140*** 0.118*** 0.130*** 0.136*** 0.123*** 0.132***

(5.196) (6.128) (8.390) (4.319) (5.449) (7.399)

0.745*** 0.203** 0.329*** 0.684*** 0.261** 0.283***

(5.147) (2.320) (3.381) (4.169) (2.512) (2.679)

Hedge*Return 0.007 -0.001 0.002 0.008 -0.005 0.002

(1.645) (-0.314) (0.551) (1.594) (-1.343) (0.430)

38

Hedge* 0.033 0.070*** 0.115*** 0.067** 0.080*** 0.124***

(1.290) (3.813) (5.130) (2.320) (3.694) (4.910)

Var( ) 0.018 0.025 -0.087 0.103 -0.033 0.152

(0.166) (0.278) (-1.022) (0.425) (-0.198) (0.837)

Var(Return) -0.049** -0.060*** -0.032** -0.058* -0.046* -0.049*

(-2.340) (-3.448) (-1.962) (-1.704) (-1.687) (-1.913)

Leverage 0.076* 0.024 0.063 0.110 0.085 0.055

(1.692) (0.598) (1.562) (1.240) (1.056) (0.679)

CEO tenure -0.009*** -0.005*** -0.001** -0.014*** -0.004** -0.006***

(-8.164) (-4.721) (-2.292) (-8.209) (-2.218) (-3.744)

ln(Cash) 0.093* -0.014 0.044 0.245** 0.037 0.091

(1.740) (-0.322) (1.030) (2.410) (0.459) (1.042)

Size -0.019*** -0.019*** -0.010 0.004 -0.025 -0.033

(-2.761) (-2.750) (-1.500) (0.163) (-1.082) (-1.299)

MB -0.003** -0.000 -0.001 -0.002 0.001 0.000

(-2.489) (-0.150) (-0.753) (-1.282) (0.474) (0.106)




N 6318 4416 4393 6318 4416 4393


39

Table 6 Stratified firm-specific risk and effect of relative weight and managerial hedging cost on CEO total compensation.





Table 1.


(1) (2) (3) (4) (5) (6)


Low risk Medium risk High risk Low risk Medium risk High risk

Constant 0.032 -0.086 0.415*** 0.081 0.096 0.031

(0.375) (-0.401) (4.431) (0.270) (0.344) (0.129)

Hedge -0.044* -0.021 -0.035 -0.014 -0.158*** -0.071

(-1.709) (-0.701) (-1.336) (-0.238) (-2.771) (-1.217)

Return 0.232*** 0.166** 0.150*** 0.170 0.142* 0.140***

(2.861) (2.064) (5.530) (1.354) (1.713) (3.754)

2.807*** 2.320*** 0.189 2.063** 2.151*** 0.186

(3.385) (3.648) (1.519) (2.005) (2.922) (1.167)

Hedge*Return 0.120 0.064 0.015 0.135 0.067 -0.003

(1.352) (0.761) (0.478) (1.034) (0.767) (-0.075)

Hedge* -1.533* -1.086 0.630*** -0.395 -0.847 0.618***

(-1.756) (-1.584) (3.090) (-0.369) (-1.096) (2.796)

Var( ) -0.083 -0.393 -0.362*** 0.087 -0.192 -0.155

(-0.245) (-1.420) (-2.837) (0.140) (-0.448) (-0.620)

Var(Return) -0.130** 0.009 -0.035 0.013 0.063 -0.044

(-2.307) (0.263) (-1.412) (0.154) (1.071) (-1.026)

Leverage 0.075 -0.017 -0.091 0.106 -0.026 -0.261*

(1.203) (-0.259) (-1.497) (0.696) (-0.169) (-1.734)

CEO tenure -0.003*** -0.002 0.001 -0.007*** -0.007*** 0.003

(-2.733) (-1.544) (1.308) (-3.288) (-2.847) (1.072)

ln(Cash) 0.033 -0.075 0.130* 0.023 0.149 0.179

(0.418) (-0.951) (1.923) (0.123) (0.863) (1.197)

Size 0.010* 0.004 0.006 0.005 0.022 0.042

(1.716) (0.543) (0.675) (0.119) (0.521) (1.091)

MB -0.002 0.001 0.000 -0.001 0.002 0.007

(-1.536) (0.367) (0.049) (-0.250) (0.670) (1.558)


Industry dummy Yes Yes Yes Yes Yes Yes

Firm fixed effect No No No No No No

N 4469 4425 4397 4469 4425 4397



(1) (2) (3) (4) (5) (6)



Constant -0.064 -0.149 0.363*** 0.036 -0.096 -0.116

(-0.666) (-0.678) (3.594) (0.117) (-0.330) (-0.457)

Hedge -0.008 -0.009 -0.011* -0.008 -0.036*** -0.023*

(-1.475) (-1.327) (-1.894) (-0.636) (-2.922) (-1.834)

Return 0.336*** 0.192*** 0.138*** 0.272*** 0.143** 0.127***

(4.618) (3.478) (5.100) (2.956) (2.265) (4.087)

1.923*** 2.751*** 0.264* 1.654** 2.959*** 0.220

(3.280) (5.642) (1.912) (2.507) (5.711) (1.457)

Hedge*Return 0.001 0.005 0.006 0.004 0.010 0.002

40

(0.059) (0.512) (0.889) (0.254) (0.927) (0.423)

Hedge* -0.091 -0.245*** 0.085** 0.009 -0.267*** 0.096***

(-1.020) (-2.720) (2.449) (0.091) (-3.404) (2.730)

Var( ) -0.017 -0.310 -0.333*** 0.087 -0.096 -0.113

(-0.050) (-1.136) (-2.704) (0.140) (-0.225) (-0.450)

Var(Return) -0.117** 0.018 -0.025 0.024 0.085 -0.030

(-2.034) (0.480) (-0.987) (0.276) (1.426) (-0.669)

Leverage 0.070 -0.019 -0.114* 0.101 -0.032 -0.298*

(1.117) (-0.284) (-1.845) (0.658) (-0.205) (-1.952)

CEO tenure -0.003*** -0.001 0.002 -0.007*** -0.007*** 0.003

(-2.684) (-1.466) (1.351) (-3.291) (-2.633) (1.049)

ln(Cash) 0.057 -0.049 0.148** 0.025 0.195 0.198

(0.705) (-0.604) (2.161) (0.134) (1.121) (1.317)

Size 0.021** 0.015 0.020 0.012 0.047 0.071

(2.103) (1.119) (1.604) (0.295) (1.046) (1.617)

MB -0.001 0.001 0.001 -0.001 0.003 0.007*

(-1.102) (0.618) (0.131) (-0.206) (0.891) (1.658)

Year dummy Yes Yes Yes 0.000 0.000 0.000



N 4469 4425 4397 4469 4425 4397


41

Table 7 Stratified firm-specific risk and effect of relative weight and managerial hedging cost on CEO cash compensation.





Table 1.


(1) (2) (3) (4) (5) (6)



Constant 0.279*** 0.098 0.262*** 0.272 0.147 0.297**

(4.242) (1.140) (2.596) (1.358) (0.888) (2.204)

Hedge 0.003 -0.006 0.017 0.023 -0.005 0.009

(0.161) (-0.406) (0.935) (0.573) (-0.155) (0.260)

Return 0.189*** 0.150*** 0.124*** 0.217*** 0.099** 0.132***

(3.701) (4.061) (6.136) (2.579) (2.032) (6.427)

2.418*** 2.036*** 0.104 2.126*** 2.266*** 0.089

(3.158) (5.672) (1.204) (3.081) (5.171) (0.994)

Hedge*Return 0.026 -0.013 0.015 0.020 0.030 0.013

(0.470) (-0.313) (0.653) (0.229) (0.580) (0.578)

Hedge* -1.591** -0.935** 0.730*** -1.213* -1.080** 0.794***

(-2.032) (-2.410) (5.555) (-1.690) (-2.347) (6.366)

Var( ) -0.173 0.202 -0.033 0.158 0.336 -0.004

(-0.836) (1.160) (-0.473) (0.380) (1.352) (-0.033)

Var(Return) -0.063* -0.017 -0.060*** -0.088 -0.020 -0.080***

(-1.903) (-0.884) (-4.362) (-1.521) (-0.586) (-3.252)

Leverage 0.049 0.069* 0.049 0.148 0.128 0.072

(1.134) (1.737) (1.210) (1.446) (1.396) (0.843)

CEO tenure -0.006*** -0.004*** -0.006*** -0.011*** -0.008*** -0.009***

(-7.959) (-5.491) (-6.871) (-7.289) (-5.063) (-5.092)

ln(Cash) 0.039 0.015 0.060 0.027 0.095 0.005

(0.789) (0.339) (1.482) (0.218) (0.934) (0.058)

Size -0.016*** -0.018*** -0.010 -0.018 -0.001 -0.021

(-3.852) (-3.358) (-1.516) (-0.686) (-0.052) (-0.932)

MB -0.002** -0.002* -0.002 -0.001 -0.001 -0.001

(-2.434) (-1.850) (-1.366) (-0.384) (-0.232) (-0.360)




N 4545 4544 4544 4545 4544 4544



(1) (2) (3) (4) (5) (6)



Constant 0.261*** 0.052 0.288*** 0.285 0.075 0.300**

(3.495) (0.584) (2.695) (1.398) (0.436) (2.081)

Hedge 0.000 -0.006* 0.005 0.004 -0.013* -0.001

(0.120) (-1.827) (1.211) (0.447) (-1.763) (-0.128)

Return 0.234*** 0.150*** 0.110*** 0.256*** 0.100*** 0.115***

(4.629) (5.332) (6.048) (4.164) (2.709) (6.658)

2.146*** 2.255*** 0.179 2.253*** 2.581*** 0.143*

(4.492) (8.019) (1.611) (5.118) (8.415) (1.686)

42

Hedge*Return -0.005 -0.003 0.007* -0.004 0.004 0.007**

(-0.524) (-0.596) (1.897) (-0.450) (0.589) (2.242)

Hedge* -0.205*** -0.184*** 0.105*** -0.217*** -0.219*** 0.123***

(-2.656) (-3.896) (4.011) (-3.182) (-4.696) (6.230)

Var( ) -0.115 0.257 -0.038 0.211 0.390 -0.006

(-0.556) (1.489) (-0.539) (0.506) (1.569) (-0.044)

Var(Return) -0.057* -0.010 -0.061*** -0.090 -0.009 -0.073***

(-1.731) (-0.520) (-4.309) (-1.515) (-0.260) (-2.920)

Leverage 0.053 0.067* 0.055 0.157 0.134 0.064

(1.228) (1.664) (1.348) (1.528) (1.444) (0.742)

CEO tenure -0.006*** -0.004*** -0.006*** -0.011*** -0.008*** -0.009***

(-7.849) (-5.472) (-6.863) (-7.219) (-4.985) (-5.134)

ln(Cash) 0.038 0.036 0.048 0.028 0.122 -0.000

(0.735) (0.825) (1.156) (0.225) (1.188) (-0.001)

Size -0.014** -0.009 -0.014* -0.019 0.013 -0.019

(-2.291) (-1.239) (-1.668) (-0.705) (0.503) (-0.780)

MB -0.002** -0.002 -0.002* -0.001 0.000 -0.001

(-2.343) (-1.343) (-1.797) (-0.344) (0.032) (-0.526)




N 4545 4544 4544 4545 4544 4544


43

Table 8 Stratified firm-specific risk and managerial ownership, and effect of relative weight and managerial hedging cost on CEO

compensation.

Panel A reports 13,633 firm-year observations from 1996 to 2010. Panel B reports 13,291 firm-year observations from 1996 to 2010.

For Panel A, the dependent variable is cash compensation. For Panel B, the dependent variable is total compensation. Corresponding

t-statistics are reported in brackets. Hedge is a dummy variable indicating whether the firm has options markets or not. The t-statistic

for OLS regressions is based on robust standard errors clustered at firm level. Notations ***, **, and * denote statistical significance at

1%, 5%, and 10% levels, respectively. All variables are defined in Table 1.

Panel A: Use as the dependent variable

Own Firm-specific risk

OLS

Firm-specific risk

Fixed effect

Low Medium High Low Medium High

Hedge*Return -0.032 -0.029 0.103** 0.048 -0.036 0.106

Low (-0.359) (-0.372) (2.048) (0.282) (-0.300) (1.464)

Hedge* -0.542 -1.002 0.293 1.360 -0.974 0.337

(-0.336) (-1.516) (1.233) (0.921) (-0.972) (1.091)

Hedge*Return 0.118 0.019 -0.029 0.123 0.095 -0.086**

Medium (1.245) (0.214) (-0.728) (0.747) (0.796) (-2.167)

Hedge* -2.806*** -2.253*** 0.833*** -3.289** -2.080* 1.026***

(-2.982) (-3.180) (4.693) (-2.334) (-1.962) (5.448)

Hedge*Return 0.111 0.034 0.004 0.104 -0.006 0.008

High (1.179) (0.696) (0.135) (0.699) (-0.071) (0.254)

Hedge* -1.129 0.202 0.840*** -0.323 0.183 0.847***

(-1.316) (0.360) (4.481) (-0.293) (0.269) (4.202)

Panel A: Use as the dependent variable

Own Firm-specific risk

OLS

Firm-specific risk

Fixed Effect

Low Medium High Low Medium High

Hedge*Return 0.036 -0.005 0.013 0.061 -0.031 0.008

Low (0.247) (-0.048) (0.172) (0.249) (-0.159) (0.075)

Hedge* -1.835 -0.414 0.078 -1.283 -0.484 -0.392

(-1.230) (-0.318) (0.201) (-0.605) (-0.300) (-0.805)

Hedge*Return 0.139 -0.145 0.054 0.034 -0.158 0.033

Medium (0.750) (-1.025) (1.215) (0.116) (-0.729) (0.428)

Hedge* 0.514 -1.714 0.407 0.622 -0.881 0.655*

(0.356) (-1.180) (1.428) (0.249) (-0.463) (1.805)

Hedge*Return 0.153 0.242* -0.023 0.232 0.275* -0.005

High (0.884) (1.726) (-0.430) (0.994) (1.759) (-0.077)

Hedge* -1.933 -0.795 1.169*** 0.003 -0.360 1.357***

(-1.561) (-1.039) (3.785) (0.002) (-0.276) (3.205)

44

Table 9 Effect of relative weight and managerial hedging cost on CEO compensation controlling for age and managerial wealth.

Panels A and B report firm-year observations from 1996 to 2010. For Panel A, Hedge is a dummy variable. For Panel B, Hedge is the

average number of daily options contracts. Industry dummies are constructed based on 48 industries in Fama and French (1997).

Corresponding t-statistics are reported in brackets. The t-statistic for OLS regressions is based on robust standard errors clustered at the


Table 1.


(1) (2) (3) (4)


Constant 0.422*** 0.807*** 0.849*** 2.467***

(7.869) (5.817) (4.861) (10.803)

Hedge 0.043*** 0.027 0.042*** 0.030

(4.728) (1.221) (2.609) (0.828)

Return 0.136*** 0.146*** 0.163*** 0.153***

(7.142) (6.657) (5.929) (4.238)

0.169 0.166 0.194 0.114

(1.361) (1.560) (0.871) (0.652)

Hedge*Return -0.002 -0.017 0.004 -0.013

(-0.097) (-0.713) (0.131) (-0.339)

Hedge* 0.815*** 0.838*** 0.901*** 1.023***

(5.137) (6.362) (3.305) (4.743)

Var( ) -0.010 -0.013 -0.003 0.006

(-0.172) (-0.085) (-0.025) (0.026)

Var(Return) -0.048*** -0.066*** -0.029 -0.044

(-4.078) (-3.356) (-1.251) (-1.347)

Leverage 0.046** 0.039 -0.031 -0.148

(2.119) (0.704) (-0.911) (-1.612)

CEO tenure -0.002*** -0.002 -0.001 0.001

(-3.537) (-1.407) (-1.034) (0.536)

ln(Cash) 0.066** 0.118* 0.096* 0.297***

(2.235) (1.836) (1.856) (2.815)

Size 0.005 -0.000 0.071*** 0.109***

(1.233) (-0.001) (5.269) (4.411)

MB -0.000 -0.000 0.003* 0.004

(-0.442) (-0.244) (1.767) (1.473)

CEO age -0.000 -0.002 -0.001 -0.004*

(-0.825) (-1.103) (-1.536) (-1.652)

CEO wealth -0.042*** -0.070*** -0.143*** -0.328***

(-5.507) (-6.808) (-6.064) (-19.486)




N 9001 9001 8939 8939



(1) (2) (3) (4)


Constant 0.476*** 0.805*** 0.908*** 2.454***

(8.156) (5.651) (4.833) (10.485)

Hedge 0.005*** -0.002 0.007* -0.002

(2.789) (-0.478) (1.782) (-0.280)

Return 0.122*** 0.124*** 0.173*** 0.156***

(6.107) (7.442) (5.898) (5.756)

0.404* 0.424*** 0.399 0.357**

45

(1.878) (4.404) (1.406) (2.272)

Hedge*Return 0.003 0.002 -0.000 -0.003

(1.013) (0.712) (-0.072) (-0.595)

Hedge* 0.072** 0.071*** 0.093* 0.102***

(1.962) (3.999) (1.754) (3.565)

Var( ) -0.083 -0.055 -0.079 -0.038

(-1.367) (-0.372) (-0.736) (-0.155)

Var(Return) -0.050*** -0.060*** -0.033 -0.038

(-4.101) (-2.959) (-1.355) (-1.145)

Leverage 0.051** 0.029 -0.026 -0.165*

(2.366) (0.511) (-0.747) (-1.786)

CEO tenure -0.002*** -0.002 -0.001 0.001

(-3.726) (-1.462) (-1.149) (0.512)

ln(Cash) 0.058** 0.127** 0.087* 0.313***

(1.962) (1.972) (1.655) (2.948)

Size 0.001 0.004 0.065*** 0.115***

(0.198) (0.250) (4.957) (4.367)

MB -0.001 -0.000 0.003 0.004

(-0.971) (-0.243) (1.530) (1.577)

CEO age -0.000 -0.001 -0.001 -0.004

(-0.649) (-1.047) (-1.386) (-1.619)

CEO wealth -0.042*** -0.070*** -0.145*** -0.328***

(-5.343) (-6.739) (-5.901) (-19.376)




N 9001 9001 8939 8939


Documents

CEO hedging opportunities and the weighting of performance measures …conference/conference2012/... · 2012-12-20 · Taychang Wang* Department of Accounting National Taiwan University