Foreign Exchange Risk Hedging and Firm value:

Empirical Study from MNCs in China

Meng Zhang

ANR: 355134

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Foreign Exchange Risk Hedging and Firm value:

Empirical Study from MNCs in China

Meng Zhang

ANR: 355134

Tilburg University

August 2013

Master in Finance 2012

Supervisor: Dr. J.C. Rodriguez

Second Reader: M.R.R (Michel) van Bremen

Tilburg School of Economics and Management

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Abstract

This paper examines the relationship between foreign currency derivative usage and

firm value. It broadly follows the work of Allayannis and Weston (2001) but differs in

sample selection and extends the work to find the determinants of hedging decision. I

use a sample of 97 Chinese multinationals during 2007-2012 to test whether firms

using FCD are valued more by investor with higher market value than firms without

using. With the reform of Chinese currency regime, a floating exchange rate system

makes Chinese multinationals exposed to more currency risk. Therefore, a substantial

growth of hedging activities in Chinese firms makes empirical studies on Chinese

samples available and meaningful. Firstly, I perform a univariate test to identify the

hedging premium between hedgers and nonhedgers and find insignificant results.

Secondly, a linear regression without control variables is run to test the hypothesis.

No significant result is obtained for the argument that hedging can create value for

firms with currency risk exposure. Thirdly, pooled regressions adding control

variables and those with firm-fixed effects are used to test whether hedging is

value-creating. A significant hedging premium is only found when using fixed effects

while no meaningful evidence on FCD usage is found when we use cluster option to

run the pooled regressions. Thirdly, a logistic regression is performed to examine the

determinants of hedging. Some variables are identified to play important roles in

determining hedging. In a nutshell, the results for hedging premium is positive but

insignificant at most times, therefore, this paper provides only limited empirical

evidence on Chinese samples to examine the hedging-creating effect.

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Contents

1 Introduction................................................................................................................... 6

2 Literature Review .......................................................................................................... 9

2.1 Financial Derivatives and China ............................................................................... 9

2.11 Forward Settlement and Sale of Foreign Exchange ............................................... 9

2.12 Non-deliverable Forwards ................................................................................ 10

2.2 Risk management Theory ...................................................................................... 11

3. Data and Statistics....................................................................................................... 12

3.1 Sample Description ............................................................................................... 12

3.2 Dependent Variable ............................................................................................... 13

3.3 Independent Variable ............................................................................................. 14

3.4 Other explanatory Variable .................................................................................... 15

3.5 Control Variables .................................................................................................. 15

4. Results ....................................................................................................................... 17

4.1 Descriptive Statistics ............................................................................................. 17

4.2 Hedging Premium ................................................................................................. 18

4.3 Univariate Test...................................................................................................... 19

4.4 Multivariate Test ................................................................................................... 20

4.5 Firm-fixed Effect................................................................................................... 21

4.6 Determinants of the decision to hedge ..................................................................... 22

4.7 Summary of the Results ......................................................................................... 23

5. Conclusion and Limitation........................................................................................... 25

5.1 Conclusion and Discussion .................................................................................... 25

5.2 Limitation and Recommendation ............................................................................ 26

Reference ....................................................................................................................... 28

Table 1: Summary statistics ............................................................................................. 31

Table 2: Profile of firm’s hedging over time ..................................................................... 34

Table 3: Comparison of Q: hedgers versus nonhedgers...................................................... 35

Table 4: Estimates of the Relation between Firm Value and Hedging Behavior ................... 36

Table 5: Determiants of FC derivatives hedging................................................................ 38

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Appendix 1: The Renminbi-dollar Exchange Rate Movements in the Period 2007-2012 ...... 39

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1 Introduction

Risk management plays an important role in modern business strategy. The ISDA

research (2009) on world’s 500 largest companies reports that 92 of which use

derivative instruments to manage business and financial risks. Financial derivatives,

such as currency, interest rate and commodity derivatives are widely used by

corporations to control risks.

Due to the friction of M&M model, a substantial literature is developed to illustrate

the relation between hedging and firm value. Smith and Stulz (1985) identified that

hedging was induced because of the convex structure of tax code and the reduced

contracting cost of financial distress. Stulz (1996) pointed out “the primary goal of

risk management is to eliminate the possibility of costly lower-tail outcomes-those

that would cause financial distress or make a company unable to carry out its

investment strategy”. According to Froot et al. (1993), when the external financing is

more costly than self- financing, hedging activities are value-increasing because

hedging ensures the capability of financing profitable investment, which alleviate or

avoid underinvestment problem.

Empirical examinations of hedging theories are widely conducted after the

availability of data on hedging activities. On the one hand, Allayannis and Weston

(2001) and Carter et al. (2006) find a positive association between hedging and firm

value, indicating that firms using currency derivatives have higher value than firms

without using by 5%. Furthermore, different types of hedging instruments (futures,

options, swaps and insurance) can result in different value-enhancing effect, ranging

from 11% to 34% (Clark& Judge, 2009).

On the other hand, some other research studies conclude that hedging is not always

value-enhancing. Guay and Kothari(2003) declare that the amount of hedging

premium can be overlooked when considering firm size, investing cash flow,

suggesting that the effect of hedging are probably be overvalued or the value created

may attributed to other risk management or luck. Magee (2009) also finds that

positive and significant relation between hedging and firm value disappears after

controlling for the possibility that past level of firm value affects current level of

foreign currency hedging. Even more, hedging are probably be value-diminishing,

based on agency problems that managers may hedge on the benefit of themselves, not

to maximize value for shareholders (Stulz, 1984; Smith and Stulz, 1985)

It is evident to notice that few empirical research studies are performed on Chinese

firms to examine the corporate derivative use and firm value according with corporate

risk-management theories. This fact may be related with the short period of floating

currency policy and data availability of currency derivative usage in China. The

reform of Chinese currency regime started in 2005, indicating a managed floating

exchange rate system. In particular, except for one-off appreciation against dollar by

2.1%, the peg against dollar was replaced by a link to a basket of currencies. Until

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May, 2013, the accumulated appreciation amounts to 25%, rising from 8.2765 in June,

2007 to 6.2072 in May, 20131 (middle rate of month).

With the continuous appreciation of renminbi, Chinese corporations with

substantial exporting activities suffer with decreased revenues because the raised price

of products marked by foreign currency has reduced the volume of exporting.

However, corporations with large importing benefits from that. 2

Most of the research studies of foreign currency risks in China focus on

macro-aspects, such as the effect of floating currency on international trade and

employment policy. Besides, some empirical research explores the currency influence

on specific industry, district and stock market. Very few studies test whether

corporations use currency derivatives to hedge according with their risk management

policies.

Until 2007, the data availability of currency derivatives is feasible on firm level,

making the empirical research examining effects of hedging activities available. The

new Corporate Accounting Principles was first implemented in public firms on 1st,

January, 2007. In details, it requires all firms to report risk exposure and the according

formative factors, the goal of the risk management, the way to measure risks and the

information about financial derivatives on fiscal years ending. In particular, firms

must report details about the types of derivatives (e.g., options, futures, NDF and

swaps), the face, contract or notional amount of the financial instruments together

with the information on the profit and loss of those financial instruments.

In this paper, the main goal is to address the question whether foreign currency

derivative usage contributes anything to firm value for Chinese multinationals. The

basic structure is largely based on Allaynnis and Weston (2001) who conduct a study

to examine that whether firms with FC derivatives are rewarded with higher value. I

follow the methodology of them but differ in the sample selection and timing. The

authors use a sample of large non-financial corporations with more than 500 million

dollar total assets in U.S. that are listed in COMPUSTAT database over 1990-1995

and separate into two subsamples, one with foreign sales and another not. However, I

use a random sample of 97 large nonfinancial firms, those of which all have a certain

amount of foreign sales 3 . All firms are traded at Shanghai or Shenzhen Stock

exchange markets from 2007 to 2012, and have more than 1000 million yuan total

assets. Finally, I obtain a set of 485 firm-year observations to study the relationship

between hedging and firm value.

Like many previous research studies, I use Tobin’s q for firm value, stem from

Allayannis et al. (2009), whose formula requires basic financial and accounting

1 The data is derived from website of Stated Administration of Foreign Exchange www.safe.gov.cn 2 China has maintained great trade surplus for a few years , which is settled by foreign currency (e.g., dollar), indicating trading risk resulted by exchange rate movements for multinationals, for example, exporting activi ties or importing competi tion. 3 Some fi rms do not distinguish exporting sales and sales from foreign subsidiaries , so, in this paper, foreign sales

include both exporting sales and sales from foreign subsidiaries.

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information. Besides, I also use the simple approximation for Tobin’s q (Kee H.Chung

and Stephen W. Pruitt,1994) to test the hypothesis that hedging is value creating and

find the same results.

The main hypothesis is that for firms with foreign sales, the users of foreign

currency derivatives (FCDs) are more likely to be rewarded by investors with higher

valuation in the market place. For example, hedging can substantially reduce the

contracting cost of financial distress.

This paper first examines whether users of FCDs have higher value than nonusers,

and I find that groups with derivative usage have consistently higher mean Qs than

their counterparts, but the hedging premiums between two groups are not significant.

The directions of currency movement are also taken into consideration- those may

affect firm value, so I use the same tests for RMB-appreciation and RMB-no

appreciation periods (From 2007 to 2012, there are no RMB depreciation periods) and

also find the hedging premium is higher for derivative users during RMB appreciation

period, but not significant. Besides, I add the explanatory variables to further test

whether hedging is valuable for firms and find the hedging is value-creating after

controlling for size, leverage, profitability, access to financial markets, growth

opportunity, geographic and industry diversification, segment(GIC-sector) and time

effects but not significant. I further add the cluster options to capture the robust

standard errors but no significant evidence is found. Until now, I cannot argue that

hedging is value-creating for multinationals. Furthermore, to control unobservable

firm characteristic that may affect market value, such as corporate management, I also

estimate a firm-fixed effect model. The outcomes show a positive and significant

hedging premium for all multinationals, suggesting FC derivatives usage value-adding

activities. Finally, a logistic regression is run to examine the factors determining

hedging decision. Some meaningful evidence is found.

Unlike Allaynnis and Weston (2001) who use the four-digit SIC to control the

industry diversification, this paper use GIC-sector instead. Considering the majority

of firms in the sample are not diversified across different industrial segments, it is

adequate to use simple industry control to capture industry effect.

The major contribution of this paper is to illustrate the relationship between

hedging activity and currency derivatives at firm level with the sample that is based

on Chinese multinationals. Prior empirical studies are heavily relied on samples of

corporations in developed countries, such as U.S. and UK. In the meanwhile, few

studies in China have tried to address the issue on currency risks and hedging

management at firm level. One reason is that there are colossal public firms in

Chinese exchange stock markets, making the empirical studies difficult and

time-consuming at firm level, so most previous studies choose to focus on some

specific industries (e.g., oil and cooper industry) to examine the hedging effect.

The paper is organized as follows. Section 2 presents the current state of risk

management for multinationals in China and reviews theoretical arguments on

derivative hedging. Section 3 describes the sample selection and definitions of

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dependent variables, independent variables and control variables and the

corresponding signs to test the main hypothesis. Section 4 is the main part of this

paper, which provides the descriptive statistics, two sample tests and regression

analysis to test the hedging effect and the determinants of hedging activities. Section 5

is the final part and conclusion.

2 Literature Review

2.1 Financial Derivatives and China

China has made tremendous strides after three decades of reforms and progressive

opening of markets. Finance plays a crucial role in modern economy and thereafter

China’s financial system has made great progress, which is in line with rapid

economic growth. Financial derivatives, as an important part of modern financial

system, have also experienced continuous growth in China.

As China’s share of international trade grows, renminbi turnover has a dramatic rise,

suggesting importers and exporters have to find sophisticated ways to manage foreign

exchange needs. Thereafter，demand for derivatives, especially those related to risk

management, has increased steadily from financial institutions and even from

non-financial companies and individual investors.

The Chinese foreign currency derivative markets include two main types of FC

derivatives: foreign forward exchange transactions and Non-diverable forwards.

2.11 Forward Settlement and Sale of Foreign Exchange

The prevailing financial derivative between renminbi and foreign currency is

limited to forward exchange transaction. In April, 1997, Bank of China IFC Bulletin

No 35 first begin the RMB forward exchange settlement and sales business, making

an important step in the development of Chinese derivative market4. Later in 2003,

three big national banks: Industrial and Commercial Bank of China Limited (ICBC),

Agricultural Bank of China (ABC) and China Construction Bank (CCB) are approved

to set up this type of business for the capital accounts.

Forward settlement and sale of foreign exchange refers to the transaction between

clients and banks to designate currencies at a specific time in the future. Under the

contract, the currency type, amount, term and foreign exchange rate of the forward

transaction have been settled by two parties. At the date that the spot contract settles,

the clients can buy and sell foreign currencies at the specific exchange rate, avoiding

the possible changes in currency prices in the future.

4 Gao yang, He fan, in their paper the development of foreign currency derivatives, have mentioned the order of

derivative development.

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The forward settlements and sale business in China have been restricted in several

ways.

First, the forward settlement and sale business require all applicants to provide the

documents that reflect real international trading background or certain transactions

under capital accounts approved by the State Administration of Foreign Exchange

(SAFE), excluding most financial transactions in practice. This principle, on one hand,

restricts the scale of forward settlement and sale business, on the other hand, cannot

reflect the supply and demand conditions of forward foreign currency.

Second, the number of banks that are qualified to set up the forward settlement and

sale business is strictly limited, suggesting strong monopoly, and a substantial

regulations on forward transactions largely affects foreign currency operating

autonomy. In particular, this forward settlement can only be made between banks and

corporations, not within banks. The quota management on synthetic positions,

including both current positions and forward positions, prevents banks to adjust the

volume of forward settlement and sale business in line with its own demands.

Third, the pricing method of foreign exchange rate is inconsistent and not

authoritative. In details, the calculation is based on covered interest rate parity (CIRP),

using renminbi inter-bank lending/borrowing interest rate, international foreign

exchange inter-bank lending/borrowing interest rate and spot interest rate. But the

problem within this calculation is that spot interest rate cannot reflect the real supply

and demand under the low level of interest market development. Therefore, the

forward exchange rate cannot be seen as accurate expectation of spot exchange rate in

the future.

Due to the factors described above, the trading volume of forward settlement and

sale business is quite smaller compared to spot settlement.

2.12 Non-deliverable Forwards

The renminbi Non-deliverable Forwards, begin to trade actively in countries with

foreign exchange control in early 1996 in Singapore.

NDF contracts are traded offshore and used to hedge against exchange rate

movements in non-convertible currencies. Especially, reminbi non-deliverable

forwards, refers to foreign exchange contract with renminbi denoted as standard, in

which two parties agree to buy or sell renminbi at a specific future date at a fixed

exchange rate. At maturity, the contracts are settled using dollar and no renminbi

transferred. Dollar payments are based on the difference between the prevailing spot

rate and the NDF rate. If, at maturity, renminbi has depreciated against the dollar, the

holder of the NDF has to pay a certain dollar amount. If the renminbi has appreciated,

the holder earns a certain dollar amount.

In particular, Singapore and HongKong are the two main off-shore RMB NDF

markets in Asian, indicating the global expectation of RMB currency. The main

participants in RMB NDF markets are big banks and investing institutions in USA

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and Europe, whose clients are multinationals with colossal revenues in RMB, or

Chinese mainland corporations setting headquarter in HongKong.

2.2 Risk management Theory

In the market perfection assumption, hedging cannot create value for firms (M&M

propositions, 1958). The theory debates that private investors are assumed to manage

their risks by holding well-diversified portfolio, and financial policies adopted by

corporations cannot create value, suggesting hedging is value-neutral in a perfect

capital market. Second, on the condition that capital market is imperfect, risk

management is believed to create value for firms. The market imperfections can be

summarized as: taxation (Smith and Stulz, 1985; Leland, 1998), underinvestment

(Froot et al., 1993), financial distress cost (Mayers and Smith, 1982; Smith and Stulz,

1985) and costs of managerial risk aversion (Stulz, 1984; Smith and Stulz, 1985).

All of the risk management theories developed on the market friction indicates that

hedging can create firm value by mitigating varies types of risk exposures. Based on

the research of Smith and Stulz (1985), when a firm faces tax-function convexity,

hedging may lower expected tax liabilities by reducing the variability of taxable

income, thus inducing the firm to hedge and increase the expected post-tax income.

Ross (1996) and Leland (1998) argue that hedging can increase the firm’s debt

capacity through a reduction in variability of pre-tax income. After adding the

leverage, the firm gets tax reduction advantage through an increase in interest

deduction, leading to higher firm value. In the paper of Froot, Scharfstein, and Stein

(1993), when the external financing is costly, hedging can reduce the cash flow

volatility and thus reducing the underinvestment problem.

Financial distress costs are believed to generate costs associated with bankruptcy

costs, as well as moral hazard, contracting, agency costs, which can lead to decreased

market value (Myers, 1984). Hedging, as a useful way to reduce the variability of

earnings or cash flows, can then result to a lower possibility of expected costs of

financial distress according to Smith and Stulz (1985). Dolde (1995), Haushalter

(2000), and Howton and Perfect (1999) measure the expected costs of financial

distress using debt ratio and identify that higher debt ratio leads to greater hedging.

Higher expected costs of financial distress can cause firms to hedge more on the

assumption that firms with higher debt ratio would face higher possibilities of

financial distress. Geczy, Minton and Schrand (1997) have also claimed that firms

with greater growth opportunities and tighter financial constraints are more likely to

use currency derivatives by reducing cash flow variation and enable firms to perform

valuable projects. Further, Stulz (1996) argues that hedging can lower the likelihood

of left-tail outcomes that can cause distress costs or make firms unable to carry out

positive NPV projects.

Managerial risk aversion gives firms an incentive to hedge, but different

compensation plans for managers can influence the specific hedging choices (Smith

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and Stulz, 1985). Managers who own large proportion of shares would hedge more to

reduce the variance of share price. Then, the stock price volatility is the main risk

measure to be concerned for managers. On the contrary, for managers whose

compensation plans are option- like, they will hedge less to take more risks. The utility

function of managerial wealth has a shape of convex function of firm profits, and the

larger volatility of firm earnings, the larger possibility managers get greater benefits.

3. Data and Statistics

3.1 Sample Description

To carry out the empirical study, the initial sample consists of large nonfinancial

firms with A shares5 (include A+B shares and A+H shares types)6 that are listed in

Shanghai and Shenzhen exchange stock markets and have total asset larger than 1000

million renminbi in the period 2007-2012.

In this paper, I only examine whether multinationals7 with foreign sales can be

rewarded with higher firm value, so firms without foreign sales, having missing data

on important financial and transaction data (for example, total asset, size, revenues

and share price) are excluded. Geczy, Minton and Schrand (1997) have identified the

positive association between the value of firms exposed to extensive exchange rate

risks and currency derivatives usage. Moreover, because financial firms are the

providers of financial derivatives whose motivations of using financial derivatives are

different from nonfinancial firms (for example, financial firms use financial

derivatives for speculation, not for hedge risks), I also removed these data. Public

utilities are also deleted from the sample because of heavily regulation. Further, my

sample does not include those types of firms: Firms that are first listed during the

sample period8; ST firms9 or firms with significant reorganization during the sample

period (such as change the main business segment). Finally, I obtain 97 firms, a

sample of 485 firm-year observations during 2007-2012.

Most of the financial data can be obtained using Compustat database, and share

price of each firms in each fiscal year end are derived from Datastream database.

5 A share is specialized share of the renminbi currency that are purchased and traded on Shanghai and Shenzhen stock exchange markets . 6 B shares are traded using foreign currencies on Shanghai and Shenzhen s tock exchanges . H shares refer to

those companies incorporate in mainland China and traded on the HongKong s tock exchange. Many fi rms simultaneously traded on both two mainland China s tock exchanges and HongKong s tock market. 7 Multinationals refer to companies with foreign sales more than 10% of total sales. (Jorion, 1990; He & Ng, 1998) According to Corporate Accounting Principle NO.35, fi rms should report the business and district that generate 10 % revenues . But, in this paper, some fi rms in my sample do not have more 10% foreign sales, but the average of foreign sales ratio is more than 22%. 8 Fi rms that are fi rs t listed in two mainland China s tock exchanges during the period cannot have complete stock price data. 9 ST is short for Special Treatment, refers to stocks of listed companies with abnormal financial conditions . These

kinds of stocks have investment risks, which should be cautious for investing.

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However, some specific variables, which are not disclosed in main databases, such as

foreign sales, foreign currency derivative usage, geographic diversification, industry

diversification are hand collected from annual reports of each firm. Foreign currency

derive users are defined to those firms that make reference in the annual reports to

hedge FC exposure or report the notional value (or fair value) of foreign currency

derivative (or NDF) 10 or firms report the profits and loss by using FCDs in the

financial expense items. From the collected information on derivative usage, I find

that firms in China do not choose foreign currency swaps or foreign currency options 11to hedge currency risks, so in my sample, FCDs only include forward contracts and

NDF.

For the firms in my sample, I do not obtain all data of notional value on forward

contracts during 2007-2012. One important reason is that not all firms report the fair

or notional value of FCDs derivatives in their annual reports. Instead, they only make

reference on whether they use FCDs during the operating period in the footnotes.12

This incomplete information may lead to the measurement error and make this paper

unable to be performed using hedging ratio (a ratio of notional value of FCD to total

assets) as the measurement of foreign currency derivative level. 13 But Geczy, Minton

and Schrand (1997) also mentioned the samples of hedgers would decrease

dramatically when using the level of FCD usage to measure, and the notional amounts

as a risk exposure can be quite noisy because of aggregation and netting, so I perform

my test by constructing binary variable, 1 refers to firms using FCD, and 0 refers to

the counterparts.

3.2 Dependent Variable

The dependent variable in this paper is Tobin’s q, a proxy for firm value, defined as

the ratio of market value of a firm to the replacement cost of its assets. As previous

research study, I follow a methodology of Tobin’s q (Allayannis et al., 2009), defined

as the ratio of total assets minus the book value of equity plus the market value of

equity to the book value of assets. There are also some other methods to construct

Tobin’s q. L-R algorithm are quite complex and cumbersome that is highly unlikely to

undertake. A simple approximation of Tobin’s q proposed by Chung & Pruitt (1994)

can account for at least 96.6% of the variability of Tobin’s q, which is easy to perform.

Likewise, in Allayannis and Weston (2001) paper, three measures are used to test the

10

Most fi rms disclosure the foreign currency derivative usage under the held for trading financial asset i tems or make any reference on FCDs usage when analyze currency risks . 11 SAFS firs t set up foreign currency swaps business in 2007 and until April , 2011, SAFS firs t set up foreign

currency option business only for European options . 12 According to Corporate Accounting Principles, fi rms should report the types of derivative usage, the notional or fair value of derivatives. However, because of the ineffective regulation of fi rms, a certain number of fi rms do not follow closely the rules of Accounting Principles , which make my empirical s tudy difficul t to collect that data. So, I decide not to collect the notional value of foreign contracts , but only obtain the information on whether fi rms use FCDs or not on year-end during 2007-2012. 13 Maker & Huffman, 2001; Kim et al . 2006 and Magee, 2009 all use hedging ratio to measure the level of FCD

usage.

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relationship, which make no significant difference in results. To test the robustness of

the results, alternative measures are also considered. One simple alternative measure

for Tobin’s q is the ratio of market value of the firm to the book value of the

assets.(Allayannis and Weston, 2001) Another measure is used by Chung & Pruitt,

1994, ), the ratio defined as the market value of equity plus the liquidating value of

preferred stock and plus the book value of debt14. We find the similar results by using

alternative measurements of Tobin’s q but not reported.

I calculate Tobin’s q for the whole sample and find the mean value is 1.70 while the

median value is 1.42, indicating the distribution of Tobin’s q is skew. In order to

control the skewness and make it more symmetric, I use the methodology by

constructing natural log of Tobin’s q and employ it in all multivariate tests (Allayannis

and Weston, 2001).

3.3 Independent Variable

The independent variable in this paper is the foreign currency derivative dummy

variable, with 1 indicates hedgers and 0 nonhedgers. As mentioned above, all data of

FCD usage are collected from annual reports of all firms. Clark and Judge (2009)

argues that the choice of hedging instruments depend on the type of exposure, with

short-term instruments such as FC forwards and options are used to hedge short-term

exposure generated from exporting activities, while FC debt and swaps into foreign

currency are used to hedge long-term activities with assets located in foreign locations.

This paper aims to explore whether the firms with currency exposure can generate

higher value by using FCD, without distinguishing the long-term or short-term

exposure.

Like U.S. firms, the currency forward is by far the most popular financial

instruments. Forward-type (volatility reduction) instruments are arise to hedge foreign

exchange rate risk in U.S. contractual commitments (account payables/receivables), as

recommended by international financial literature (Shapiro, 1996). Some other

hedging channels are combined to be used in corporate practice, for example,

operational hedging (Pantzalis, Simkins and Laux, 2001), impacts significantly on

exchange rate exposure. Firms with greater breadth 15of MNC network are less

exposed to currency risk whereas firms with more concentrated networks (greater

depth) are more exposed. However, due to the limited accounting disclosure, this

paper primarily examines the FC derivative usage at firm level (Bartram et al. 2009).

Allayannis et al, (2009) use foreign currency derivative as proxy for hedging as well.

14

The book value of debt here refers to the value of short-term liabilities minus short-term assets and plus the book value of long-term debt. 15 Pantzalis, Simkins and Laux, 2001 examine the influence of foreign operating hedging on exchange rate risk exposure. Breadth and depth measure the different dimensions of fi rm’s degree of multinationality. Greater breadth means the fi rm is spread out over many countries and greater depth indicates a large proportion of the

link is concentrated within two top countries of the MNC network.

15

3.4 Other explanatory Variable

This paper focus on the FCD use of multinationals, indicating one of the top

variables is the amount of exposure of foreign currency rate risks, defined as

geographic diversification.

A substantial number of surveys have examined characteristics and practices of U.S.

nonfinancial firms using derivatives (Bodnar and Gebhardt, 1998; Treasury

Measurement Association, 1996; Papaioannou) and find that the larger currency risk

exposure of U.S. nonfinancial firms, the more likely is to use financial hedging

instruments. Following Allayannis et al. (2009) and Lel (2009), this study uses the

ratio of foreign sales to total sales as the measure for geographic diversification. All

the data are hand collected from annual reports of each firms, and then I exclude all

the firms without foreign sales and only keep firms with sales from other countries.

The difference between this paper and the literature by Allayannis and Weston

(2001) lies in the sample selection. The financial derivative markets in China are in

the beginning developing stage, suggesting the lack of financial hedging instruments

usage among Chinese firms. In particular, with the great loss of several big Chinese

firms using financial hedging instruments, great debate on the influence and

characteristics of financial derivatives are prevalent16. Thus, firms without sales from

other countries are less likely to use FDC to hedge currency risks. For the accuracy of

the research, firms without foreign sales are excluded.

. Previous studies have not reach a common conclusion on the effect of

geographical diversification. Allayannis and Weston (2001) find positive relation

between geographic diversification and firm value based on 508 U.S. firms. Kim et.al

(2006) find that firms with only exporting activities are more likely to use FCD to

hedge, but both foreign operating and FCD usage can increase firm value, except the

foreign operating have better hedging effect.

3.5 Control Variables

In order to get rid of other factors that may affect firm value, previous empirical

literature have provided us with ample reference (Lang and Stulz, 1994; Allayannis

and Weston, 2001).

One of the variables is size. Based on the method of Wald (1999) and Mackay and

Philips (2002), this paper uses the log of total assets to measure firm size. Small firms

are more likely to encounter financial distress or bad operating conditions, so they

have more incentive to carry out hedging activities. But due to the set-up costs of

16 In 2008, Standardization Administration of China (SAC) counts at least 23 national fi rms suffered great financial loss by using financial hedging derivatives. For example, CITIC Pacific aims to lock the cost of buying Australian dollar by purchasing Accumulator option. However, this option cannot effectively hedge and reduce risks, but

lead to great defici t.

16

hedging, larger firms are more likely to hedge than smaller firms in empirical studies.

To control for the profitability of firms, I include return on assets, defined as net

income divided by total assets (Allayannis et al, 2009). And the profitability is

expected positively related with firm value.

Another factor should be controlled is future investment opportunities. Smith and

Watts (1992) have claimed that investment opportunities can affect firm performance

in a positive way. Thus, firms with more investment opportunities can have better firm

performance. In line with Yermack (1996), I use the ratio of capital expenditure to

sales as the measure of future investment opportunities. Alternative measurements,

such as R&D expenditures are used in several papers to proxy for growth

opportunities (Allayannis and Weston, 2001). However, due to the disclosure

restriction of R&D expenditure, this paper does not use this measurement.17

Moreover, a variable to control the access to financial market is included. Serveas

(1996) have argued that firms with restricted access to financial markets obtain

greater firm value because those constrained firms would only choose positive and

highest net positive value (NPV) projects to undertake while bypass the less highest

NPV projects. Follow Allayannis and Weston (2001), I construct dividend dummy

variable to proxy for the ability to access financial markets, with dummy variable

equals to 1 if the firm pays dividends in the current year. And I expect a negative

association between dividends paid and firm value.

Besides, the firm’s leverage should also be taken into account. A variable defined as

long-term debt divided by equity is used as a measure. Haushalter (2000) have found

that the financial derivative use can lead to the reduction of expected bankruptcy costs,

which should increase firm value. Firms with larger leverage ratio are more likely to

hedge, and the hedging can increase more value for firms with more debt. A positive

relation between leverage and firm value is expected.

Furthermore, a dummy variable indicates the industry diversification is included. If

it equals to 1, then the firm operates in more than one business segments at the

GIC-sector factor, and zero otherwise. The effects of industry diversification on firm

value are mixed. Berger and Ofek (1995) find an industry diversification discount for

U.S. firms while in Lins and Servaes (1999) literature, they find that industry

diversification is not value-destroying for German firms.

Finally, the paper controls the industry and year effect. I use a 2-digit GIC-sector to

construct a dummy variable for industry effect and a year dummy for each of the four

years examined in the sample.

17 In most Chinese fi rms annual reports, no specific item on R&D expenditures in profi t and loss accounts are

reported.

17

4. Results

4.1 Descriptive Statistics

Panel A of table 1 provides summary statistics for all firms in the sample. There is a

large cross-sectional variation in the FCD usage among the firms, ranging from 100%

to 0%. On average, 29% of the sample firms uses foreign currency derivatives to

hedge currency risks, which is smaller compared to 60% of all U.S. firms with foreign

sales in Allayannis and Weston (2001) study and 61% in Bartram et al (2009b). The

facts that less multinationals would like to use financial instruments to hedge are

associated with the ability of risk avoidance, the type of risks that firm would like to

bear and the level of risks occurred to different types of firms.

Moreover, the mean (median) value of Tobin’s q is 1.70 (1.42), suggesting the

average firm is profitable with valuable investment opportunities. At the same time,

these numbers are larger than U.S. based study, for example, the average (median)

value reported in Allayannis and Weston (2001) is only 1.20 (0.99). However, the

average value is not as large as the one reported in Allayannis et al, (2009), 1.70

compared to 2.213.

The distribution of Tobin’s q is skewed, with mean 1.70 and median 1.42. To

eliminate the effect of skewness, a natural log of tobin’s q is used to run all the

regressions (Belghitar et al, 2008).

The mean (median) value of total assets is 29189 (5870) and the mean (median)

value of sales is 158234 (4182). The mean (median) foreign sales to total sales ratio is

0.22 (0.15).

The table also shows that only 31% of all firms are industry diversified in my

sample, while in U.S. based study, the percentage amounts to 68.3% (Allayannis et

al, 2009) and 70.2% (Magee, 2009), suggesting the low level of industry

diversification of Chinese multinationals.

The average profitability, defined as the ratio of net income to total assets, is

quite low, only at 4% and has large variation, ranging from 0.2% to 10.2%.

The mean value of leverage is only at 0.26, and some firms in my sample even

do not borrow any debt to run the operations. This big difference among between my

study and other U.S. based study lies in the types of firms and the specific strategy

used in the firms.

Panel B of table 1 provides information of variables for hedgers and Pane C for

non-hedgers. It is obvious to find that hedgers have larger total assets than nonhedgers,

29218.38 compared to 29176.52. This is in line with Allayannis and Weston (2001)

that larger firms are more likely to hedge currency risks than small firms because

hedging is costly and small firms would not like to bear the large fixed set up costs.

18

On average, firms with FCD usage are more profitable (0.05 versus 0.04), and have

larger total sales (28410.06 versus 10598.15), better access to external financial

markets (0.13 versus 0.04), lower leverage and growth opportunities. Moreover,

hedgers are less industry diversified but more geographic diversified.

The hedgers have larger Tobin’s q than nonhedgers (1.77 versus 1.67). It seems that

hedging can increase firm value. But only based on these facts, I still cannot make

sure whether the difference in premium between hedgers and nonhedgers is caused by

hedging decision. Some other variables that may affect firm value, such as size,

profitability, access to financial market should be examined. The further tests will go

deep to examine these questions.

Panel D of table 1 provides an overview of financial instruments usage by each

industry. The percentage of FCD usage among different industries varies. For example,

50% of firms in Information Technology industry choose to hedge whereas only 18%

in Materials industry use FCD to hedge. The difference in using FCD among different

industries indicates the importance to control industry in further regressions. At the

same time, these results may be related with the number of firms in different

industries, which can influence the results of the study. For example, the sample

number in Energy industry is only 2, with all firms being nonhedgers. The sample

collection is quite time-consuming, and I only include firms with foreign sales and

require no missing data on all important financial information for 5 years. Therefore,

the number of firms in different industries is varied.

4.2 Hedging Premium

Like Allayannis and Weston (2001), I first examine the number of firms using

currency derivatives over time in my sample. Table 2 provides the summary statistics

on the usage of FC derivatives for the whole sample over 2007-2012. But the

difference between their study and this paper is that no gross notional value of foreign

currency derivatives is reported because of the incomplete information of notional

value of FCD disclosed by firms in my sample. Therefore, I cannot figure out whether

the level of FCD usage increases in my sample during the whole period.

The percentage of firms using FCD goes upward over time. In specific, only 17.65%

of firms in 2007 choose to hedge currency risks whereas the percentage rises

dramatically to 35.19% in 2012, suggesting more firms are engaged in hedging

activities over time. This is in line with the results of Allayannis and Weston (2001),

in their paper, a certain increase in the percentage of hedgers is found during 1990 to

1995, for example, 32% in 1990 rises to 40% in 1995.

Furthermore, the increase of FCD usage in Chinese firms is more dramatic, 17.54%

compared to 8%. The great increase may be related with the development of financial

instruments in China. SAFS first set up foreign currency swaps business in 2007 and

until April, 2011, SAFS first set up foreign currency option business only for

European options.

19

4.3 Univariate Test

In this part, I test my hypothesis that whether firms with currency derivatives have

greater value, by comparing the Tobin’s q of hedgers and nonhedgers. The tests are

performed for all firms in my sample. As mentioned above, all firms have foreign

sales, which are assumed to be exposed to exchange rate risk. Firms with exporting

activities are influenced by exchange rate movements by foreign revenues and foreign

debt. Firms with foreign subsidiaries are affected through translation into compound

reports.

Allayannis and Weston (2001) documents that the direction of dollar movement can

affect firm value when they are exposed to exchange rate risks. In specific, the

hedging premium among firms with foreign currency exposure is highest in dollar

appreciation period, suggesting investors have higher valuation on hedging firms in

which hedging activities can provide positive payoffs. Cater, Rogers and Simkins

(2006), in their study on U.S. airplane study also identifies that hedging premiums

increased over time and reach the highest in 2002 and 200318. For example, if a

Chinese exporting firm has foreign sales 6 months later, in order to prevent renminbi

appreciation, the firm will hedge. The value of hedgers is higher than that of

nonhedgers, when the renminbi appreciates, while the hedgers will destroy value

when the renminbi depreciates. The difference in value between hedgers and

nonhedgers should not fluctuate a lot when the renminbi remains stable. Unlike

Allayannis and Weston (2001), this paper separates between years in which renminbi

appreciates and in which renminbi not appreciates. Since the renminbi regime begins

to change in 2007, there is a huge renminbi appreciation except a stationary in 2009.

Appendix 1 provides the chart of exchange rate of renminbi to dollar.

Table 3 provides the mean value of Tobin’s q for all firms in my sample.

In the whole period, column (1) shows that the average firm value for nonhedgers

is 1.67 and column (2) shows that the average firm value for hedgers is 1.77. Column

(3) presents the difference in premium between hedgers and nonhedgers when they all

have currency risk exposure. The hedging premium is 0.1, but not significant, as

shown in column (6) (t-statistics -1.11). Therefore, I cannot conclude that hedgers are

rewarded with higher valuation by investors than nonhedgers. Contrary to my results,

Allayannis and Weston (2001) find a significant hedging premium at the 1% level.

In the further tests during the years in which renminbi appreciate or remain stable,

the results are different with the ones derived by Allaynnis and Weston (2001). In

their study, they find a significant hedging premium regardless the behavior of dollar.

On the contrary, in my study, when renminbi appreciated, the mean Q for those do not

use foreign currency derivatives is 1.78, compared with a mean value for those use

foreign currency derivatives by 1.91, suggesting a hedging premium of 0.12. Like my

first test, this hedging premium is not significant, with a t-statistics of -1.12.

18

The dollar began a long upward climb in 2002

20

Furthermore, during years in which renminbi without fluctuation, the opposite results

are obtained. The average value of nonhedgers is higher than that of nonhedgers, 1.17

compared to 1.16, suggesting a small hedging discount of 0.01. Due to the low t-stat,

no conclusion about value-destroying of hedging is included.

4.4 Multivariate Test

In this section, I use multivariate methods to test the influence of hedging on firm

value after control the explanatory variables. I start by analyzing the relationship of

FCD usage and firm value in a univariate setting using a simple OLS regression

(regression 1). Then, I add some explanatory variables that may affect firm value to

further test the relationship in regression 2 and use cluster option in regression 3.

Regression 1 of table 4 presents the outcome of OLS regression to test the effect of

hedging on firm market value without control variables. More specific, the coefficient

shows that the value of those who use currency derivatives is higher than those who

do not use by 2.76%. The hedging premium is not significant. The results are

consistent with my univariate tests in 4.3. The argument that hedging is value-adding

is not inclusive.

In regression 2 of table 4, the control variables are added into the OLS regression.

My model is constructed similar to those used by Allayannis and Weston (2001) and

the following explanatory variables are included. (1) The amount of currency risk

exposure (geographic diversification), defined as the ratio of foreign sales to total

sales. (2) Size, defined as the natural log of total assets. (3) Profitability, defined as

the net income divided by total assets. (3) Leverage, defined as the long-term debt

divided by common equity. (4) The growth opportunity, defined as capital expenditure

divided by total sales. (5) Industry diversification, using dummy variable equals to 1

if firm operates in more than business segments. (6) Dividend dummy variable equals

to 1 if firms pay dividends that year. (7) Industry effect, using 2-digit GIC-sector as

controls. (8) Year effect, using year dummy.

Regression 2 of table 4 presents the results of my hypothesis by controlling

explanatory variables. The R2 increasing from 0.44 to 0.54 shows the improvement of

the regression after adding control variables. The coefficient shows the consistent sign

with my first tests in regression 1 that users of currency derivatives are rewarded with

higher valuation than nonusers (2.18% hedging premium). The hedging premium

decreased a little after control some explanatory variables, from 2.76% to 2.18%. On

the contrary, the t-statistics is only 0.6, which is too low to reject the null hypothesis.

Therefore, no statistical difference in the value is found between users of FC

derivatives and nonusers.

Previous empirical studies also get mixed results on this relationship. Allayannis

(2009) do find a statistical significant relationship between the use of FCD and firm

value in their study for firms with foreign sales. Carter et al.(2006) also documents a

substantial hedging premium, over 10% in airline industry when tests whether

21

hedging can increase firm value. On the contrary, Belghitar, Clark and Mefteh (2012)

examines that FC derivative usage is not significant for the samples, indicating FC

derivative cannot create value for firms. It argues that hedging can effectively reduce

risks but the profits gained from risk reduction are not large enough to offset the

hedging costs.

Most of the control variables show the expected effect on firm value and

statistically significant, which is in line with Allayannis and Weston (2001). In

specific, the firm size is negatively related with firm value; the larger geographic

diversification, the larger firm value; the profitability of firm is positive with its

market value; the coefficient on growth opportunities is positive, indicating firms with

more growth opportunities are rewarded by investors with higher market valuation.

Unlike Allayannis (2009), the coefficient of industry diversification is positive with

Q. This is in line with Magee (2009) who also find a positive relationship between

industry diversification and firm value. But this coefficient is not statistica l significant,

I cannot conclude that more diversified firm have higher value. The relationship

between the access to financial markets and firm value is positive but not significant

in my study.

A difference in the methodology from Allayannis, et al (2009) is that I use cluster

options to specify that observations are not independent within the firm or cluster at

the firm level. The reason to use this methodology is that usage of FCD and other

control variables may correlated with each other within the firm, which makes the

residuals of the regressions are not independent at the firm level. These facts are

contrary to the assumptions of OLS regression that residuals are independent.

Regression 3 of table 4 provides the outcomes of multivariate tests with control

variables and cluster options. The R2 remains the same at 0.54. The coefficients on all

the variables do not change, while the t-statistics decreased substantially. The hedging

effect cannot be identified by the low t-stat (0.39). Only limited evidence is provided

by this test.

4.5 Firm-fixed Effect

It is well understood that unobserved firm heterogeneity is a fundamental challenge

in empirical study. Without controlling the unobservable firm heterogeneity that is

common across groups of observations, the common errors come out. The factors that

are related with variables of interest can lead to biased estimated parameters. For

example, unobserved factors- like corporate governance is common cross firms and

affect firm value. Failing to control such factors can cause spurious relationship

between firm value and hedging. Therefore, to consider the unobservable firm factors

that may affect firm value, I use a firm-fixed effect model to perform a test. For each

firm, the unobservable factors are assumed to be time-invariant.

Regression 4 in table 4 presents the results. I find a positive and significant

22

relationship between firm value and currency derivative usage. In specific, the users

of currency derivatives are valued about 13.83% more than nonusers. The magnitude

of hedging premium is much larger than that in the pooled regression (2.18%).

Therefore, the value-creating hypothesis of hedging is conclusive with controlling

firm heterogeneity.

Some outcomes on control variables are not similar to those in pooled regression:

size and firm value are positively related; more profitable firms have lower value; and

firms with more growth opportunities are valued less. Some of results are striking and

not intuitive, but these coefficients are not significant. Then, the conclusions on

control variables cannot hold in this regression. Other explanatory variables have

similar results but few of them are statistically significant.

4.6 Determinants of the decision to hedge

To test the factors that affect firms’ decision to hedge, I employ logistic (logit)

analysis. The FCD dummy variable is considered as dependent variable, with 1

indicating firms set up hedging activities and 0 otherwise. The natural log of Tobin’s q

is treated as independent variable, and all the control variables performed in the

pooled regressions are also used as continuous indicators.

Follow the definitions in Carter (2006), the ratio of capital expenditure to total sales

and Tobin’s q are used as proxy for the amount and productivity of investment

opportunities, respectively. Both variables are expected positively related with the

decision to hedge since hedging can alleviate the underinvestment problem (Froot et

al., 1993). Firm size, measured as the natural log of total assets, should be negatively

related with hedging decision, because the larger firm, the smaller possibility to go

bankruptcy. The leverage rises with the decision to hedge, suggesting the more debt

will lead more hedge activities (Ross, 1996). The geographic diversification is

expected to cause more hedging since firms with foreign sales are more influenced by

exchange rate movements. Other financial policies and operating method can also be

substitutes for hedging, because it reduces the transaction costs, agency costs or

expected taxes. The substitutes for hedging can lower the possibility to use financial

instruments. In Nance (1993), it uses convertible debt/value, preferred stock/value,

liquidity and dividend yield as proxy for alternative hedging to examine the ir

relationship with FCD usage decision. My study does not use this method because

few Chinese firms employ the alternative hedging through preferred stock.

The results are displayed in table 5. The coefficient (0.38) of Tobin’s q suggests that

the firm value is positively related with the decision to hedge, which is in line with

my expectation. The standard derivation of Tobin’s q is 0.47, one standard derivation

increase in Tobin’s q increase the possibility to hedge by 17.86% (=0.47*0.38). This

seems to indicate high firm value leads to higher probability of hedging. However, the

p-value is only 0.14, indicating the statistical insignificant result. I cannot conclude

that firms with higher firm value are more likely to hedge based on my analysis.

23

The relationship between firm size and hedging decision is positive and significant,

derived by the coefficient 0.62 and p-value 0.00, respectively. Although hedging is

more valuable for small firms in theoretical study, large firm are proved more likely to

hedge, indicating the information and transactional scale economies of hedging.

Combine this conclusion with the results of pooled regression, larger firms responds

to lower firm value, leading to the arguments that hedging destroys firm value.

The more extent of geographic diversification responds to higher possibility to

hedge, with the statistical significant coefficient by 3 and p-value 0.00. Following the

results of pooled regression, the coefficient of geographic diversification, measured

by foreign sales/total sales, is positive and statistical significant on firm value. I can

derive the conclusion that hedging can create firm value for firms with more currency

risk exposure.

The negative sign of growth opportunities on hedging decision is surprising

because normally the future growth options should be positively related with hedging

decision. Hedging can guarantee that positive NPV projects can be carried out when

the firm is underinvestment. Nance (1993) uses R&D/ value proxy for growth options

finds firms with more future growth opportunities are more like to hedge.

The estimated coefficient of the profitability is 5.41 and statistically significant at 1%

level, indicating the positive relationship between profitability and hedging decisions.

Other variables in this logit regression cannot provide meaningful results because

of the large p-value.

4.7 Summary of the Results

Firstly, I have split the samples into two groups: hedgers and nonhedgers. F rom the

descriptive statistical analysis, I can get the conclusion that firms have currency

derivative usage are valued more by investor than those have no currency derivative

usage, with Tobin’s q at 1.77 compared to those at 1.67. Moreover, firms who employ

hedging activities have larger sales, larger book assets, more exposure to currency risk

(more geographical diversification) and larger firm size. The average debt ratio is

around 0.2, as well as ROA about 0.05, respectively for both firms with FCD usage

and without, which are dramatically smaller compared to firms in U.S. In particular,

Allayannis and Weston (2001) document the mean debt ratio by 167, as well as ROA

by 4.03. This big difference illustrates the different financing policy between firms in

two countries.

Secondly, I perform the univariate tests in two ways to explore the hedging effect

on firm value. The first method is two-sample t test with equal variances. The results

show in the full year period, hedgers have greater value than nonhedgers, while the

difference in value is not significant with t-statistical by 1.11. The same results are

obtained in dollar appreciation period whereas nonhedgers are valued more than

hedgers in dollar without fluctuation period. The conclusions that hedgers have higher

24

value than nonhedgers are not hold because of the small t-statistic. The second

method is to use pooled regression without control variables. In line with the first

approach, I also find that firms with FCD usage have greater hedging premium

(2.76%) but not statistical significant.

Third, pooled regressions with control variables and firm-fixed effect model are

employed to documents the relationship between financial instruments usage and firm

value. The normal pooled regressions find a positive but not significant hedging

premium, on the contrary, firm-fixed effect model derives a positive hedging premium

by 13.83% and is statistical significant at 5% level. Then, the hedging value-creating

hypothesis can hold when the unobservable firm factors are fixed at firm level.

In terms of control variables in pooled regressions, most of the results are in line

with my expectation. Specifically, firm size has negative and statistical significant

relationship with firm value. Firms with more exposure to currency risk exposure are

more likely to have higher value, with the coefficient of foreign sales/total sales is

0.27 and significant at 5% level. The relationship between profitability and firm value

is positive and significant, indicating an intuitive argument that profitable firms are

rewarded by investors. The leverage ratio is negatively related with firm value and

significant at 5% level. The research on growth opportunities indicates that firms can

be valued more with greater growth opportunities, which corresponds to the

underinvestment hypothesis. Hedging can be value-adding when firms expect more

growth opportunities under the underinvestment circumstance.

After adding the firm-fixed effect, I cannot get the fruitful conclusion because most

coefficients of control variables are not statistical significant. This is due to the

unobservable variables affect both hedging decision and other control variables, as an

exogenous factor.

Fourthly, the logistic regression is used to examine what factors determine the firm

to hedge. The results of firm size declare that larger firms have more likelihood to use

currency derivatives to hedge, which is in line with the economy scale of risk

management. Large firms are more mature, have more capital and better governance,

indicating the ability to perform the hedging activity better compared to small firms.

The large fixed costs of currency derivatives also prevent small firms with margin

profits to carry out the hedging project.

Regarding the level of geographical diversification, the larger level of geographical

diversification leads firms to hedge. This result is intuitive since firms with more

currency risk exposure can be affected more by exchange rate movements.

More profitable firms have higher possibility to use FCD to hedge because those

firms have ample capital and effective management to perform the hedging activity. It

seems firms with high leverage ratio should be more likely to hedge since they face

larger possibility of financial distress. On the contrary, my result on debt ratio shows a

negative relationship with hedging decision but not significant. Besides, the

coefficient of growth opportunities is negative, indicating firms with more future

growth opportunities hedge less. Although this result violates my expectation that

25

firms with greater growth should hedge more under the underinvestment circumstance,

the low t-stat cannot hold the result.

5. Conclusion and Limitation

5.1 Conclusion and Discussion

This paper addresses the question whether firms that face currency risks using

foreign currency derivatives are rewarded with higher valuation by investors, based

on a sample of 485 firm-year observations in Shanghai and Shenzhen exchange stocks

during the year 2007-2012.

The outline is mainly developed based on Allayannis and Weston (2001). But

contrary to their results, we do not find a significant relationship between FC

derivatives usage and firm market value in both univariate tests and multivariate tests

with cluster options. While in a firm-fixed effect regression, we do find that users of

FC derivatives that exposed to currency risk have a 13.83% higher value than

nonusers at 10% level. Therefore, the conclusion that a hedging premium exists in

firms that face currency risks and have FC derivative usage is only inclusive in

regressions with controlling for firm-heterogeneity.

In addition, we further test what factors determine the firms to hedge by employing

a logistic regression. The FCD dummy variable is used as dependent variable with 1

refers to firms using FC derivatives and 0 otherwise. The results show that hedging

decision is significantly and positively related with geographic diversification, size,

profitability, access to financial markets, and negatively related with industry

diversification.

Finally, I cannot reach the conclusion that hedging can increase firm value

according to the empirical results of my research. It seems no difference in value

creating for users of FC derivatives and nonusers. This is in line with Belghital, Clark,

Mefteh (2012) who also find a positive but insignificant hedging premium based on a

sample of French firms. They already suggested that hedging can be only effective

when the overall gains from exposure reduction are greater than the costs and then

add value to the firms. But the evidence seems to indicate that FC derivative is

effective in reducing risk exposure of firms, but failed to add value because of the

greater costs.

There are some reasons to explain why FC derivatives cannot create value and have

little impact on firm performance. Copeland and Joshi (1996) have argued that risk

management may be ineffective to reduce exposures to losses. For example, when use

hedging derivatives to hedge price fluctuation, some other economic factors can also

be influenced and lead to greater risk exposure. Even when hedging activities are well

performed, gains from hedging may be inadequate to cover the costs associated with

human resource, physical, financial needed to execute hedging activities. Moreover,

26

financial instruments may be used to speculate rather than reduce risks, which may

lead to more risk exposure.

Endogeneity seems to be a big concern and Bartram et al, (2011) also find that the

premium is sensitive to endogeneity and measured with low precision. In particular,

Allayannis et al (2009) gives an example that an omitted variable can affect both firm

value and FC derivative usage. For example, an unobserved factor at firm level

increases the firm value, at the meanwhile raises the possibility of using FC

derivatives. Therefore, a biased conclusion that hedging may increase firm value is

included without considering the endogeneity.

5.2 Limitation and Recommendation

One of the limitations in this paper is the approximation of firm value, Tobin’s q,

defined as the ratio of total assets minus the book value of equity plus the market

value of equity to the book value of assets. This is a simple and general method to

construct Tobin’s q. Unlike Lindenberg and Ross (1981), who use a complicated

methodology to construct Tobin’s q:

RCt = TAt + RNPt - HNPt + RINVt - HINVt

RC: replacement cost

TA: total asset

RNP: net plant at replacement cost

HNP: net plant at historical value

RINV: inventories at net value

HINV: inventories at historical value

However, this method is too difficult to adopt and need much more financial

information, some of which may be not acquired directly from annual reports.

Besides, all firms in different industries use the same Tobin’s q to run all

regressions. However, a industry-adjusted Tobin’s q can be more effective to control

industry effects. Allayannis and Weston (2001) use a industry-adjusted Tobin’s q to

test the hypothesis whether hedging can add value to firms. They do this because of

greater percentage of industry diversification of firms in their sample (63%). While in

my paper, only 34% firms operate in more than one business segments, and I also use

GIC-sector to control industry effect, as well as variable indicates industry

diversification.

Another drawback of this paper is the lack of time-series analysis. I only test the

relationship between FC derivative usage and firm value, but not identify whether

hedging increase firm value or firms with large value are more likely to use FC

derivatives, leading to the reverse causality problem. One factor that limits this

analysis is the short-term disclosure of derivative usage information, which makes

difficult to perform the study in terms of time.

Finally, the measurement of hedging policies can be improved. In this paper, I

follow Allayannis and Weston (2001) to use a dummy variable to indicate whether

27

firms use FC derivatives or not. A more appropriate way used by Maker & Huffan

(2001) is to construct hedging ratio to proxy for the scale of hedging policy.

In spite of some rooms leaving for improvement, this paper clearly constructs the

model and the results show some useful insights of the FC derivatives usage for

Chinese firms with foreign sales. But it should be noticed that although firms in my

sample are exposed to currency risks, I cannot distinguish the reasons why they use

financial derivative (risk reduction or speculation), the level of hedging (single

derivative or portfolio) or the scale of hedging (hedging ratio). Therefore, I cannot

conclude firms using FC derivatives can increase firm value.

For future empirical studies on Chinese firms, more observations and derivative

information can be collected to increase the statistical power. Besides, more

complicated and accurate variables, such as hedge ratio are used to construct the

model. Furthermore, more tests can be added to examine the causality between

hedging policy and firm value. Last but not least, endogeneity should be mitigated, for

example, using instrumental variables approach (Allayannis et al, 2009).

28

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31

Table 1: Summary statistics

This stable illustrates summary statistics for my sample of all nonfinancial COMPUSTAT firms

with more than 1000 renminbi total asset in the period 2007-2012. All the firms in the sample have

foreign sales during the sample period. The FCD dummy equals to 1 if the firm make reference

the usage of FCD in their annual reports. Tobin’s q is defined as the ratio of market value of the

firm to the replacement cost of the firm. I follow the Allayannis (2009) to construct the Tobin’s q

by using the ratio of total assets minus the book value of equity plus the market value of equity

divided by the book value of assets. Return on asset is compounded net income divided by total

assets. Growth opportunities are proxied by the ratio of capital expenditure to total sales. Debt to

equity is the ratio of total debt to common equity. The dividend dummy is set equal to 1 if the firm

pays dividend that year and 0 otherwise. The industry diversification is included at dummy

variable at 2-digit GIC-sector, and 1 refers to more than one business segment.

Variables No.obs Mean Std.Dev Median

10th

percentile 90thpercentile

Panel A:

All firms

Sample description

Total assets (millions) 485 29189 310140 5870 1594 36463

Total sales (millions) 484 158234 37055 4182 912 40546

Foreign sales/ total sales 478 0.22 0.20 0.15 0.027 0.53

Market value of equity 485 11960 25232 4866 1301 23978

Market value of 485 26260 236245 6569 1791 36343

debt and equity

Derivative use

FCD dummy 485 0.29 0.46 0.00 0.00 1.00

Tobin’s Q 485 1.70 0.93 1.42 0.90 2.89

Log(Tobin’s Q)

389 0.49 0.47 0.44 -0.03 1.12

Controls

Size 485 8.81 1.21 8.68 7.37 10.50

Return on assets 485 0.04 0.05 0.032 0.002 0.102

Growth (Capex/sales) 484 0.11 0.13 0.07 0.02 0.26

Debt to equity ratio 485 0.26 0.44 0.11 0 0.57

Dividend dummy 485 0.07 0.25 0 0 0

Industry diversification 485 0.31 0.46 0 0 1

MNC 485 0.52 0.50 1 0 1

32

Variables No.obs Mean Std.Dev Median 10th

percentile

90th

percentile

Panel B:

Firms with FCD

Sample description

Total assets (millions) 142 29218.38 51383.90 7838.59 1573.71 74014.31

Total sales (millions) 142 28410.06 58996.99 5940.21 1279.69 59329.77

Foreign sales/ total

sales

142 0.28 0.23 0.19 0.06 0.64

Market value of

equity

142 22340.95 42494.13 7575.47 1610.40 58716.27

Market value of 142 29224.86 50786.56 9812.63 1951.85 78897.75

debt and equity

Derivative use

Tobin’s Q 142 1.77 0.99 1.47 0.90 2.94

Controls 142

Size 142 9.20 1.48 8.97 7.36 11.21

Return on assets 142 0.05 0.06 0.05 0.00 0.11

Growth (Capex/sales) 142 0.10 0.10 0.08 0.02 0.22

Debt to equity ratio 142 0.23 0.31 0.13 0.00 0.53

Dividend dummy 142 0.13 0.34 0.00 0.00 1.00

Industry

diversification

142 0.23 0.42 0.00 0.00 1.00

MNC 142 0.75 0.44 0.00 0.00 1.00

33

Variables No.obs Mean Std.Dev Median 10th

percentile

90th

percentile

Panel C:

Firms without FCD

Sample description

Total assets (millions) 343 29176.52 367471.40 5138.31 1627.57 21634.15

Total sales (millions) 342 10598.15 20305.64 3489.38 872.58 27865.24

Foreign sales/ total

sales

337 0.19 0.18 0.14 0.03 0.47

Market value of

equity

343 7661.80 9655.51 4284.80 1168.33 17224.52

Market value of 343 25033.12 279135.50 5893.28 1774.98 25152.26

debt and equity

Derivative use

Tobin’s Q 343 1.67 0.90 1.41 0.90 2.79

Controls

Size 343 8.65 1.04 8.54 7.39 9.98

Return on assets 343 0.04 0.05 0.03 0.00 0.09

Growth (Capex/sales) 342 0.12 0.14 0.07 0.01 0.27

Debt to equity ratio 343 0.27 0.49 0.10 0.00 0.59

Dividend dummy 343 0.04 0.19 0.00 0.00 0.00

Industry

diversification

343 0.34 0.47 0.00 0.00 1.00

MNC 343 0.42 0.49 0.00 0.00 1.00

Panel D:

Industry diversification

FCD users FCD non-users Total

Industry category NO. Percentage NO. Percentage NO.

Energy 0 0% 10 100% 10

Materials 31 18% 139 82% 170

Industrials 53 39% 82 61% 135

Consumer Discretionary 35 35% 65 65% 100

Consumer Staples 4 20% 16 80% 20

Health Care 4 20% 16 80% 20

Information Technology 15 50% 15 50% 30

Total 142 343 485

34

Table 2: Profile of firm’s hedging over time

This table illustrates the use of foreign currency derivatives of all firms over the period 2007-2012.

A firm with FCD usage defined as firm report any forward contracts, NDF usage in their annual

reports. If firms do not report the notional or fair value of contracts, but instead, they mention the

use of financial derivatives to hedge currency risks or disclosure the profits or loss by using

financial instruments for hedging, they are assumed to be hedgers.

2007 2008 2009 2010 2011 2012

Number of firms using

FCD

1 12 26 27 31 27 19

Number of firms not

using FCD

2 56 60 69 64 59 35

Percent of sample using

FCD

3 17.65% 30.23% 28.13% 32.63% 31.40% 35.19%

35

Table 3: Comparison of Q: hedgers versus nonhedgers

Foreign sales > 0

Nonhedgers Hedgers

Difference

t-statistics

(1) (2) (3)=

(1)-(2)

Difference in means

All years

Mean 1.67 1.77 -0.10 -1.11

Std.Dev 0,05 0,09

N 343 142

Renminbi

appreciation

(2007-2008,2010-201

2)

Mean 1.78 1.91 -0.12 -1.12

Std.Dev 0,06 0,10

N 274 115

Renminbi without

fluctuation

(2008-2009)

Mean 1.17 1.16 0.01 0.13

Std.Dev 0,43 0,07

N 69 27

36

Table 4: Estimates of the Relation between Firm Value and Hedging Behavior

Table 4 provides the outcomes of the pooled and fixed-effect regressions for the whole sample to

examine the use of FCD on firm value. Panel A provides the results from OLS regressions. Panel

B shows the results from an firm-fixed effect. The sample is consists of firms with foreign

currency risk exposure, measured by foreign sales. The independent variable is firm value,

measured using ln(Tobin’s q), defined as the natural log of the ratio of total assets minus book

equity plus market equity to the book value of assets. The independent variable is foreign currency

derivative usage, measured using FCD dummy variable, one refers to those firms that report

currency derivative usage and zero otherwise. The firm size is defined as the natural log of total

assets in millions. ROA is defined as net income divided by total assets. Debt to equity is defined

as the ratio of long-term debt to common equity. Growth is defined as the ratio of capital

expenditure to total sales. Industry diversification is the dummy variable, one indicates firm

operates in more than one business segments, and zero otherwise. Dividend dummy variable

equals to 1 if firm pays dividends in that year and 0 otherwise. The regressions also include year

effect and 2-digit GIC sector industry control (only for regressions 1 and 2 in Panel A) but not

reported. ***, **,*, denote signif icance at the 1%, 5%, 1% levels, respectively.

Panel A

All firms with foreign sales>0

Pooled regression

Dependent variable: log (Tobin’s q) 1 2

Observations 485 478

R2

0.44 0.54

FCD dummy 0.0276(2.76%) 0.0218(2.18%)

0.44 0.6

Foreign sales/total sales 0.27

3.19

**

Size (log of total assets) -0.08

-5

ROA

1.36

4.33

***

Debt to equity -0.09

-2.23

**

Growth (Capex/sales) 0.24

1.82

*

Industry diversification 0.04

1.07

Dividend dummy 0.04

0.6

Year effect fixed fixed

Industry effect control control

37

Panel B All firms with foreign sales>0

Pooled regression Fixed effects

Dependent variable: log (Tobin’s q) 3 4

Observations 478 478

R2

0.54 0.80

FCD dummy 0.0218(2.18%) 0.14(13.83%)

0.39 2.23

**

Foreign sales/total sales 0.27 0.34

2.02

** 1.28

Size (log of total assets) -0.08 0.09

-3.57

*** 0.8

ROA 1.36 -0.11

2.30

** -0.19

Debt to equity -0.09 0.02

-2.66

** 0.32

Growth (Capex/sales) 0.24 -0.15

1.63

* -1.09

Industry diversification 0.04 1.12

0.56 5.86

***

Dividend dummy 0.04 0

0.31 -0.01

Year effect fixed fixed

Industry effect control control

38

Table 5: Determiants of FC derivatives hedging

Table 5 provides the results of regressions explaining the determinants of currency derivatives

used by firms for the whole sample. All firms are influenced by exchange rate movements,

measured by foreign sales. The dependent variable is an indicator equals to 1 if the firm use

currency derivatives to hedge currency risks and 0 otherwise. The independent variable is the firm

value, measured by the natural log of Tobin’s q. The firm size is defined as the natural log of total

assets in millions. ROA is defined as net income divided by total assets. Debt to equity is defined

as the ratio of long-term debt to common equity. Growth is defined as the ratio of capital

expenditure to total sales. Industry diversification is the dummy variable, one indicates firm

operates in more than one business segments, and zero otherwise. Dividend dummy variable

equals to 1 if firm pays dividends in that year and 0 otherwise. ***, **,*, denote significance at

the 1%, 5%, 1% levels, respectively.

Random effects logit

Dependent variable: FCD dummy variable

p-value

Observations 478

Pseudo R2 0.14

Tobin's q 0.38 0.14

1.49

Foreign sales/total sales 3.00 0.00

5.09

***

Size (log of total assets) 0.62 0.00

5.57

***

ROA 5.41 0.02

2.36

**

Debt to equity -0.28 0.40

-0.84

Growth (Capex/sales) -0.73 0.49

-0.69

Industry diversification -0.66 0.01

-2.61

**

Dividend dummy 0.75 0.09

1.72

*

39

Appendix 1: The Renminbi-dollar Exchange Rate Movements in the Period

2007-2012

5

5.5

6

6.5

7

7.5

2007/1/1 2009/1/1 2011/1/1

The renminbi-dollar exchange rate