The effect of derivative instrument use on capitalmarket risk : evidence from banks in emergingand recently developed countries

- Mohamed-Rochdi KEFFALA (Université Lyon 1, Laboratoire SAF)- Christian DE PERETTI (Université Lyon 1, Laboratoire SAF)- Chia-Ying CHAN (Yuan Ze University, Taiwan)

2011.8 (WP 2145)

Laboratoire SAF – 50 Avenue Tony Garnier - 69366 Lyon cedex 07 http://www.isfa.fr/la_recherche

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The Effect of Derivative Instrument Use on Capital Market

Risk: Evidence from Banks in Emerging and Recently

Developed Countries

Mohamed Rochdi Keffala 1 *, Christian de Peretti 1, Chia-Ying Chan 2

1 Laboratory of Actuarial and Financial Sciences (SAF, EA2429), Institute of Financial and Insurance

Sciences (ISFA School), University Claude Bernard Lyon 1, University of Lyon, France.2 Department of Finance, College of Management, Yuan Ze University, Taiwan.

Abstract

This study investigates the use of derivative instruments by banks in both emerging

and recently developed countries in terms of capital market risk. Overall, the results

indicate that the use of options increases total return risk and unsystematic risk, while

the use of forwards and futures decreases total return risk. Swaps, in the meantime,

negatively affect systematic risk. The main conclusion is that banks in the sample do

not appear to be at risk by using derivative instruments.

JEL classification: G21; G32

Keywords: Derivatives, Bank, Capital market risk.

* Corresponding author: Mohamed Rochdi Keffala, ISFA, 50 avenue Tony Garnier, F-69366 Lyon

cedex 7, France. Tel.: +33 (0)6 13 73 24 09. Email: mrkeffala@yahoo.fr.

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1. Introduction

The rapid development and prevalence of derivatives in the securities market,

in addition to the global instability of pecuniary institutions following the recent

financial crisis, has fuelled the ongoing debate over the question of risk in terms of

derivative instruments. More specifically, the controversy focuses on the question of

derivatives either reducing or exacerbating risk in banks and other financial

institutions.

Thus, the purpose of this study is to examine whether the use of derivative

instruments affects the risk of banks in both emerging and recently developed

countries. An overview of the literature shows that only two articles have specifically

analysed the effect of derivative instruments usage on bank risk. For instance, both

Chaudhry et al. (2000) and Reichert and Shyu (2003) found that, in general, options

increase bank risk while swaps decrease bank risk. However, both studies focused

only on banks in developed countries. Moreover, Chaudhry et al. (2000), using the

sample period of 1989-1993 for U.S. banks, discovered that particular securities, such

as options, increase risk in practically all of the five capital market measures of risk

(total return risk, systematic risk, interest rate risk, foreign currency risk, and

unsystematic risk,) for each bank. In contrast, other types of derivatives, like

forwards, showed no significant effect with any type of capital market measure of

risk. Additionally, a third type of derivative, called swaps, might actually decrease

total risk and foreign currency risk.

Reichert and Shyu (2003) extended their sample to European and Japanese

banks using four capital market measures of risk: market beta, interest beta, currency

beta, and EvaR, during the period 1995-1997. Their results indicated that outside of

the United States, futures and forwards contracts had little consistent impact upon the

four measures of bank risk, while the use of options increased the interest beta for

banks in all three geographic areas. On the other hand, both interest rate and currency

swaps generally reduced risk.

This study contributes to the literature in several ways, particularly in terms of

the debate that derivative instruments are risky activities and are unfavourably linked

with the recent global financial crisis. Therefore, the explicit aim of this paper is to

assess the level of risk that banks face by using derivative instruments. Moreover,

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because of the limited number of papers that have studied the effects of derivative use

in bank risk, this study also attempts to fill this gap in the literature. Furthermore, this

paper will be the first to provide empirical evidence regarding the effect of derivative

instruments on bank risk in emerging as well as in recently developed countries.

Lastly, this paper will also be the first to provide evidence concerning the relationship

between capital market risk and derivative instruments usage.

Most experts agree that the use of options has a positive effect on bank risk,

while forwards, futures and swaps have a negative effect. As a result, since forwards

and swaps are popular derivative instruments, they are useful in the study of

management risk. In addition, several economic analysts have been critical of the risk

effect of derivative usage and the implications they suggested in recent financial

crisis. The findings of this paper contradict this point of view. Thus, based on the

results of this study, regulators should continue to encourage banks to be involved in

derivative activities, despite scepticism about derivatives both during and after the

recent financial crisis.

The remainder of the paper is organised as follows. Section 2 not only

contains statistics about derivative use in both emerging and recently developed

countries, but also presents a literature review concerning the association between the

uses and risks of derivative instruments. In Section 3, both the data and sample sets

are described, as well as the model, the methodology, and the variables used in the

study. In Section 4, the empirical results are interpreted and analysed. Lastly, Section

5 provides a summary and conclusions with policy implications.

2. Background

2.1 Overview of derivative use in both emerging and recently developedcountries

The market for derivative instruments has developed dramatically and rapidly

in both emerging as well as in recently developed countries (see Table 2 for country

classification). Data on the value and volume of derivative instruments traded, using

Hong Kong and Israel as representative of recently developed countries and Turkey

and Malaysia as representative of emerging countries, clearly shows that a remarkable

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increase and expansion in the use of derivative instruments has taken place in both

emerging and recently developed countries in the last two decades.

For example, options contract value traded on the Hong Kong Stock Exchange

has skyrocketed, from USD $683 million in 1999 to USD $9.6 billion in 2009. Data

showing this growth is summarized in the Figure 1.

Source: www.hkex.com.hk

Figure 1. Growth of options contract value traded in Hong Kong Stock Exchange

During the same period, data from the Israeli Stock Exchange shows that similar

growth in options contract value also occurred, as illustrated in Figure 2.

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Source: www.tase.co.il

Figure 2. Growth of options contract value traded in Israeli Stock Exchange

On the other hand, in regard to futures, data from the Turkish Derivatives

Exchange, as shown below in the Figure 3, demonstrates spectacular growth in futures

trading, as value grew dramatically from USD $1,88 billion in 2005 to USD $215

billion in 20091.

Source: www.turkdex.org.trFigure 3. Growth of futures trading value in Turkish Derivatives Exchange

1 Source: Turkish Derivatives Exchange www.turkdex.org.tr

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Moreover, the dramatic rise in the number of futures contracts from 2002 to 2009 on

the Bursa Malaysia exchange is shown in Figure 4.

Source: www.bursamalaysia.com

Figure 4. Growth of Futures trading contracts in Malaysia

Thus, as shown, with the obvious increase and expansion of derivative instruments

usage in both emerging and recently developed countries during the last decade, it is

important to study the effects that these financial activities have had on banks and

other financial institutions, particularly because of the linkage and connections that

have been made in terms of derivatives and the recent financial crisis.

2.2. Derivative activities and risks: a literature review

In their study of derivatives, Bali, Hume and Martell (2004) demonstrated that

credit derivatives had no significant effect on interest rate exposure. In contrast,

Bartram et al. (2008) deduced that the use of credit derivatives actually decreased

both the total risk and the systematic risk of firms. Additionally, Chung (2002) found

that the use of derivatives decreased corporate risk. Furthermore, Hentschel and

Kothari (2001) also concluded that those who made use of derivatives experienced

less risk than those who used other types of securities or investments. The results of

Nguyen and Faff (2002) indicated that currency derivatives reduced the exchange risk

of firms. However, more recently, Clark and Mefteh (2010) found that the

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relationship between foreign currency derivatives use and foreign currency exposure

was limited.

Again, the literature concerning the effects of derivatives on bank risk is also

quite limited. The study undertaken by Chaudhry et al. (2000) on US commercial

banks revealed that the use of options tended to increase all types of bank risk for U.S.

banks. However, in contrast, the same study not only found that swaps had a negative

effect on bank risk, but also, the effect of forwards on bank risk was insignificant. In

addition, Reichert and Shyu (2003) found that the use of options increased the interest

rate beta for all US, European and Japanese banks, while both interest rate and

currency swaps generally reduced risk.

In another study, which focused solely on credit derivatives, Instefjord (2005)

deduced that credit derivatives increased bank risk in England. Recently, and without

splitting derivatives by instruments, Yong et al. (2009) found that the use of

derivative activities increased long-term interest rate exposure and decreased short-

term interest rate exposure of Asia-Pacific banks.

In addition, several unpublished papers have also investigated the effects of

derivative instrument use on different types of bank risk. For example, Shanker

(1996) found that the use of swaps, futures, and options reduced interest-rate risk.

Meanwhile, Choi and Elyasiani (1996) not only found that options were positively

related to both interest-rate and currency risk, but also, currency swaps reduced

exchange rate risk. Finally, following the study conducted by Yong el al. (2009),

Hirtle (1996) found that the use of interest-rate derivatives increased the interest-rate

exposure of bank holding companies (BHC).

In a different way, Cyree and Huang (2006) concluded that those who engaged

in the derivatives market were at a higher risk in comparison to those who dealt solely

in other securities and investments. Additionally, the results of Pai and Curcio (2005)

confirmed that derivatives enhanced both the credit risk and liquid risk exposures of

bank holding companies. In another work, Pai et al. (2006) found that while credit

risk exposure was reduced by using interest rate derivatives, it was increased by using

exchange rate currency derivatives. Finally, Shao and Yeager (2007) found that while

the use of credit derivatives as a form of buyer protection reduced total risk, using

derivatives as seller protection increased risk.

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3. Data and methodology

3.1. Data

Daily capital market data, including stock prices and the market indices for

each country, were obtained from stock exchange websites2.

3.1.2 Sample statistics

The sample is composed of 52 banks spread over five regions. European banks

represent 38.461% of the sample, while Asian banks represent 40.384%. However,

only two banks from Saudi Arabia and two banks from Israel represent the Persian

Gulf region. Furthermore, only one bank, from Chile, represents Latin America.

While six banks represent Africa, five of them are from South Africa. Thus, banks

from emerging countries represent 61.538% of total sample while 38.462% of total

sample characterize banks from recently developed countries. Additionally, the

sample also includes eight dealer banks, which represent 15.384% of the total banks3.

In terms of the research sample, with the exception of Imperial Bank, each

bank made use of forwards. Swaps were the second most used instruments with 49

banks. Moreover, three quarter of banks were involved in using options, while only

44.23% of banks used futures. In general, the two most commonly used instruments

were forwards and swaps, which were utilized by 92.31% of all banks, as shown in

Table 1.

Table 1. Number and percentage of banks per derivative instruments used

Instruments Number of banks PercentageFWD+SWP+OPT+FUT 23 44.23%FWD+SWP+OPT 39 75.00%FWD+SWP+FUT 23 44.23%FWD+OPT+FUT 23 44.23%SWP+OPT+FUT 23 44.23%FWD+SWP 48 92.31%FWD+OPT 39 75.00%

2 www.bolsadesantiago.com, http://zse.hr, www.pse.cz, www.cse.com.cy, www.tse.ee , http://www.hkex.com.hk/eng/index.htm,www.idx.co.id, http://www.tase.co.il , www.klse.com.my, www.stockexchangeofmauritius.com, www.nasdaqomxbaltic.com,www.pse.com.ph, http://www.gpw.pl/root_en, www.tadawul.com.sa, www.sgx.com, http://www.jse.co.za , eng.krx.co.kr,http://www.twse.com.tw/en , www.set.or.th, http://www.ise.org/Home.aspx3 Hellenic Cyprus Bank, Hang Seng Bank, Hapoalim, EON Berhard, BRE Polish, First Rand Bank,ABSA, Industrial Bank of Korea.

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FWD+FUT 23 44.23%SWP+OPT 39 75.00%SWP+FUT 23 44.23%OPT+FUT 23 44.23%FWD 51 98.08%SWP 49 94.23%OPT 39 75.00%FUT 23 44.23%

The four derivative instruments, forwards, swaps, options, and futures,

represent 190.36% of assets, covering the period from 2003 to 2009, with an average

bank size of approximately $10 billion. During the study period, swaps were the most

represented instruments, with a notional value equal to USD $10,836,706 trillion, or

106.36% of the total assets, while futures represented 6.37% of total assets.

Moreover, in terms of yearly totals, the highest notional value occurred in

2005, when swaps represented 131.00% of assets. In contrast, the lowest percentage

occurred in 2008, when futures comprised only 3.86% of total assets. More details

concerning derivative instruments statistics are summarized in the Table 4.

Stock prices were used to determine the volatility of stock returns. Daily

returns on individual bank stocks i, for each country, were computed using the

following formula:

1,

1,,,

ti

tititi P

PPR . (1)

Market indices were used to calculate the of each bank i following the standard

definition of market risk :

)var(),cov(

,

,,,

tm

tmtiim R

RR . (2)

3.1.1. Sample description

In total, 52 banks, from 12 emerging countries and 9 from recently developed

countries, define the sample for this study. The latest classification by the United

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Nations Office based on the Human Development Index 4 is used to distinguish

between emerging and recently developed countries. The Table 2 below presents this

classification, while Table 3 includes lists of banks by country.

Table 2. Countries classification

Emerging countries Recently developed countries

Chile; Croatia; Cyprus; Indonesia;

Malaysia; Mauritius; Philippines;

Poland; Saudi Arabia; South

Africa; Thailand; Turkey

Czech Republic; Estonia; Hong

Kong; Israel; Latvia; Lithuania;

Singapore; South Korea; Taiwan

Table 3. Banks and their countries

Countries and bank names Countries and bank namesChile Philippines1.1 Banco de Chile 13.1 Philippine National Bank

Croatia Poland2.1 ERSTE & STEIERMÄRKISCHE BANK D.D 14.1 Bank BPH SA2.2 Privrednabanka Zagreb 14.2 Bank Pekao S.A.2.3 Zagrebacka Banka 14.3 Bank Zachodni WBK

14.4 BRE PolishCyprus 14.5 Kredyt Bank S.A.3.1 Bank of Cyprus Group 14.6 Nordea Bank Polska S.A.3.2 Hellenic Cyprus Bank

Saudi ArabiaCzech Republic 15.1 Arab National Bank4.1 Komerční Banka 15.2 Saudi British Bank

Estonia Singapore5.1 Swedbank Estonia 16.1 DBS Bank

16.2 United Overseas BankHong Kong6.1 BEA South Africa6.2 Chong Hing 17.1 ABSA6.3 DAH SING Bank 17.2 Capitec bank6.4 Fubon Bank 17.3 First Rand Bank6.5 Hang Seng Bank 17.4 Imperial6.6 Wing Hang Bank 17.5 Sasfin

Indonesia South Korea7.1 DANAMON 18.1 Industrial Bank of Korea

18.2 Korea Exchange BankIsrael8.1 FIBI Taiwan

4 http://hdr.undp.org/en/

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8.2 Hapoalim 19.1 Hua Nan Commercial Bank19.2 Mega International Commercial Bank

Malaysia 19.3 Taiwan Business Bank9.1 CIMB Bank Berhard Malaysia9.2 EON Berhard Thailand

20.1 Bangkok ThailandLatvia 20.2 Bank of Ayudhya10.1 DNB Nord Banka 20.3 Kasikorn

20.4 KTB BankLithuania11.1 ŠIAULIU BANKAS AB Turkey11.2 Swedbank Lithuania 21.1 AKBANK

21.2 Anadolubank Anonim ŞirketiMauritius 21.3 Garanti Bank12.1 MCB 21.4 Seker

The main motivation of integrating banks from emerging countries into the

sample is the fragility of the financial system in these countries as well as the higher

likelihood that banks in these countries may fail. In addition, no other studies have

analysed banks from emerging countries in investigating the effect of derivative

instruments use on bank risk. Moreover, the only published articles that look at the

relationship between derivative instruments use and bank risk, by Chaudhry et al.

(2000) and Reichert and Shyu (2003), are limited only to banks from developed

countries, particularly the United States of America.

Table 4. Description of derivative notional amounts per year

FWD SWP OPT FUT FWD+SWP+OPT+FUT Total assets

Year Amount % Amount % Amount % Amount % Amount % Amount2003 409,397 39.67 482,793 46.79 119,096 11.54 116,967 11.33 1,128,253 109.35 1,031,7712004 499,209 44.79 1,230,617 110.43 133,088 11.94 105,147 9.43 1,968,062 176.60 1,114,3602005 525,800 42.16 1,633,515 131.00 183,158 14.68 82,888 6.64 2,425,364 194.50 1,246,9532006 633,066 43.98 1,665,128 115.70 274,342 19.06 117,222 8.14 2,689,759 186.89 1,439,1552007 1,081,489 66.86 1,992,877 123.21 348,547 21.55 79,838 4.93 3,502,753 216.56 1,617,3852008 1,557,473 85.16 2,052,719 112.23 382,281 20.90 70,708 3.86 4,063,182 222.16 1,828,8782009 1,518,484 79.58 1,779,054 93.23 245,780 12.88 76,632 4.01 3,619,951 189.71 1,908,072

Total 6,222,836 61.07 10,836,706 106.35 1,686,294 16.55 649,404 6.37 19,395,241 190.35 10,188,821Amounts are in US$ millions.

3.2. Methodology

3.2.1. Variables description

The market model is adopted from the Capital Asset Pricing Model (CAPM):

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Rit = αmi + βmi Rmt + εit, (3)

where Rit is the holding period return for the ith bank’s stock in a given month t, Rmt is

the holding period return on a weighted portfolio of common stocks, approximated by

a stock market index, and εit is the usual error term. This model is estimated for each

bank sample i to provide the three different measures of capital market risk. This

model yields the following capital market measures of risk for each bank sample i:

standard deviation of Rit, σRi, measures the total return risk for bank i;

parameter βmi, measures the systematic risk for bank i;

standard deviation of εit, σεi, measures the unsystematic risk for bank i.

Differences in the systematic risk measures across banks reflect differences in the

sensitivity of bank stocks to the market return. Differences in total return and

unsystematic risk, in turn, reflect aggregate and diversifiable risk. These capital

market risk measures are used as dependent variables. Table 5 presents the dependent

variables employed in this study along with their definitions and use in previous

studies.

Table 5. Description of dependent variables

Labels Description Proxy for References

RRISK The annualized standard deviationof the banks’ daily stock returns

Total returnrisk

Chaudhry et al. (2000),Agusman et al. (2008),Nguyen and Faff (2003)

BETA The beta of the banks’ stockreturns

Systematicrisk

Chaudhry et al. (2000),Agusman et al. (2008)

SDERRORThe annualized standard deviationof residual errors from the marketmodel

Non-systematic risk

Chaudhry et al. (2000),Agusman et al. (2008)

These dependent variables are regressed on derivative instruments and control

variables. Control variables are defined by net interest margin, size of the bank, and

dummy variables reflecting dealer bank and country. Regarding the heterogeneity of

the sample, which is similar to the study of Agusman et al. (2008), country dummy

variables are included to control for the differences in the banking structure and

regulatory environments, as well as the different economic and political

characteristics that may affect the relation between derivatives and capital market

measures of risk. Table 6 presents the independent variables employed along with

their definitions and use in previous studies.

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Table 6. Description of independent variables

Labels Description Proxyfor

Expectedsign

References

Derivative instruments

FWD Notional value of forwards divided bytotal assets Forwards ? Chaudhry et

al. (2000)

SWP Notional value of swaps divided by totalassets Swaps Negative

Chaudhry et al.(2000); Reichertand Shyu (2003)

OPT Notional value of options divided bytotal assets Options Positive

Chaudhry et al.(2000); Reichertand Shyu (2003)

FUT Notional value of futures divided by totalassets Futures ? Chaudhry et al.

(2000)Control variables

EQTA the ratio of book-value-equity-to-total-assets Capital Negative Chaudhry et al.

(2000)

LIQTA the ratio of liquid-assets-to-total-assets Liquidity Negative Chaudhry et al.(2000)

GLTA the ratio of gross-loans-to-total-assets Grossloan Negative Chaudhry et al.

(2000)

LLRTA the ratio of loan-loss-reserves-to-gross-loans

Loan lossreserve ? Chaudhry et al.

(2000)

NIMThe difference between total interestincome and total interest expenseexpressed, as a percentage of total assets.

Netinterestmargin

Positive Chaudhry etal. (2000)

SIZE Natural log of total assets Banksize Positive

Chaudhry etal. (2000) ;Reichert andShyu (2003)

Dummies

DEAL1 if bank is a member of the InternationalSwaps and Derivative Association(ISDA), 0 otherwise

Dealer ? Chaudhry etal. (2000);

COUNTRY Dummy variable equals 1 when bank isissued from, 0 otherwise

Countryvariable ? Agusman et al.

(2008)

The independent variables in this study can be divided in three groups. The

first group are the four derivative instruments, FWD, SWP, OPT and FUT, which

define respectively Forwards, Swaps, Options, and Futures. The second group are

control variables, defined by EQTA, LIQTA, GLTA, LLRTA, NIMTA and SIZE,

which define capital, liquidity, gross loan, loan loss reserve, net interest margin, and

bank size, respectively. The last group is defined by dummy variables, expressed by

DEAL and COUNTRY, which designate the country variable of each bank. The

dichotomous variable (DEAL) takes a value one for dealer banks and zero otherwise.

3.2.2. Empirical model

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Random effect panel regression models were conducted for each risk measure

as follows:

Risk measurei,t = γ0+ γ1 FWDi,t + γ2SWPi,t + γ3 OPTi,t + γ4 FUTi,t + γ5 EQTAi,t

+ γ6 LIQTAi,t + γ7 GLTAi,t + γ8 LLRTAi,t + γ9 NIMTAi,t + γ10 SIZEi,t + γ11

DEALi,t +

K

k 1

γ12,k COUNTRYi,t,k + ui + ei,t, (4)

where the risk measure is one of σRi , βmi or σεi. The aim is to test empirically the

relations between capital market risk measures and derivative instruments.

Firstly, we checked the stationarity of all the variables using the Augmented

Dickey Fuller Tests. Then, we used panel data methodologies to estimate the

parameter values. Finally, we used the instrumental variables method, defined by first

stage regression, in order to reduce problems associated with the correlation between

the error terms and the independent variables. In addition, the estimation method also

accounted for Heteroskedasticity, as computer software STATA 10 was used to

estimate regressions.

4. Empirical results

As seen below, an empirical relationship exists between the use of derivative

instruments and bank risk.

4.1. Descriptive statistics

Table 7 describes the statistical variables used in the model.

Table 7. Descriptive statistics of variables

Variable Mean Std. Dev. Min MaxFWD 0.38 0.95 0 6.93SWP 1.21 9.82 0 185.03OPT 0.093 0.23 0 1.71FUT 0.04 0.13 0 1.20RRISK 0.02 0.01 0 0.23BETA 4.55 10.62 1 166.20SDERROR 2.86 10.38 0.03 137.40

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EQTA 0.09 0.07 0.02 0.88LIQTA 0.08 0.10 0.00 0.98GLTA 0.58 0.14 0.03 0.93LLRTA 0.02 0.02 -0.02 0.19NIMTA 0.03 0.07 0.00 0.77SIZE 9.49 1.48 4.05 12.13

4.2. Regression analysis

Table 8 below presents the parameter estimates from Equation 4 for each of

the three risk measures. In this table, it should be noted that insignificant independent

variables were removed from the models, and the regressions re-estimated to get more

precise estimates.

Table 8. Estimated coefficients, years 2003—2009

Total return riskσRi

Systematic riskβmi

Non-systematic riskσεi

Constant 0.0306***(0.00268)

1.2110***(0.0743)

2.7181*(1.4739)

Derivative instrumentsFWD --0.0024***

(0.0006) insignificant insignificant

SWP insignificant -0.0042**(0.0018) insignificant

OPT 0.0064*(0.0033) insignificant 1.0491*

(0.6320)FUT --0.0131**

(0.0054) insignificant insignificantControl variables

EQTA insignificant insignificant insignificant

LIQTA insignificant insignificant insignificant

GLTA insignificant insignificant insignificant

LLRTA --0.0696**(0.0312) insignificant insignificant

NIM insignificant insignificant insignificant

LOG SIZE insignificant -0.2800*(0.1622) insignificant

DummiesDEAL insignificant -0.6294*

(0.3243) insignificantDummies for recently developed countries

Czech Republic insignificant 5.1833***(0.4075) Insignificant

Estonia --0.0206***(0.0040)

3.0204*(1.6038) Insignificant

Hong Kong --0.0087***(0.0029)

2.8161***(0.3198)

3.9721***(0.1229)

Israel --0.0143***(0.0034) insignificant Insignificant

Latvia insignificant -0.1868**(0.0743)

2.4454***(0.3657)

Lithuania --0.0158***(0.0038)

-0.2058***(0.0742)

5.6945***(0.4191)

Singapore --0.01268***(0.0024) insignificant 9.6561***

(0.3977)

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South Korea insignificant 7.8785***(1.1246)

1.1904*(0.3967)

Taiwan --0.0071**(0.0029) insignificant InsignificantDummies for emerging countries

Chile insignificant 11.7167***(3.9953) Insignificant

Croatia --0.0116**(0.0046)

7.8814***(2.4052) Insignificant

Cyprus --0.0064**(0.0025) insignificant 2.2789***

(0.1327)Indonesia insignificant insignificant InsignificantMalaysia --0.0146***

(0.0029) insignificant 1.0233***(0.1570)

Mauritius insignificant 26.3848***(7.4031) Insignificant

Philippines insignificant 34.6963*(20.7302) Insignificant

Poland insignificant insignificant 3.6181***(0.2106)

Saudi Arabia --0.0057**(0.0027)

-0.1744308**(0.0745211)

26.6053**(12.4175)

South Africa insignificant 2.1038***(0.6925) Insignificant

Thailand --0.0050**(0.0019)

5.4924***(0.2820) Insignificant

Turkey insignificant 2.6150***(0.3053) Insignificant

R-squared 0.1292 0.3421 0.2619F statistic 4.73*** 94.16*** 306.25***Number of obs. 364 364 364

*, ** and *** indicate statistical significance at the 10%, 5% and 1% level, respectively.( ) indicate standard deviation of the estimators.

4.3. Discussion

After observing the effects of the four derivative instruments on the three bank

measures, it is clear that forwards, futures and swaps have a negative effect on bank

risk while options have a positive effect. Moreover, the association between forwards

and total return risk indicates a negative relationship at a level of significance equal to

1%. In addition, futures negatively affect the total return risk, but at a level of

significance equal to 5%. However, at the same time, the relationship between options

and total return risk is positively significant at a level of 10%. The fact that the

coefficient of options was so low confirms the notion that the effect of options on

total return risk is weak. However, the positive effect of options on unsystematic risk

is stronger at the same level of significance. In regard to systematic risk, the results

indicate that swaps also negatively affect beta market risk at a level of significance

equal to 5%. Additionally, loan loss reserve also has a negatively effect on the total

return risk at a level of significance equal to 5%.

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Another finding was that size has a negative effect on systematic risk, but at a

level of 10%. In contrast, capital, liquidity, gross loan and net interest margin seem to

have no significant effect on any type of risk measures. Consequently, it appears that

in general, the control variables used in this study have no significant effect on the

three risk measures.

The dummy variable that defines dealer banks is negatively significant only

with systematic risk at a level of significance that is equal to 10%. Moreover, this

result negates the argument that dealer banks are at risk. In regard to the effect of the

country variable regressions, only the variables representing banks from Indonesia did

not show any significant type of risk measures. As a result, Indonesian banks do not

follow the criteria set forth in our hypothesis for country variables.

In summary, the results indicate that forwards have a negative effect on total

return risk at 1% level of significance. Futures also negatively affect total return risk,

but at a level of significance equal to 5%. In contrast, options have a positive effect on

total return risk, at a 10% level of significance. Additionally, swaps have a negative

effect on systematic risk, at a level of significance equal to 5%. Finally, options

positively affect unsystematic risk at a 5% level of significance.

Overall, and in line with theory swaps reduce bank risk while options increase

bank risk. However, and contrary to the literature, futures and forwards decrease bank

risk.

Table 9 presents a summary of the regression results concerning the

association between the four derivative instruments and the three capital market risks.

Table 9. Summary table of regression coefficient signs

Forwards Swaps Options FuturesTotal return risk - + -Systematic risk -Unsystematic risk +

18

5. Conclusions

This paper aims to clarify the effect of derivative instruments on bank capital

market risk. To this end, the main question is as follows: “Do banks increase or

decrease their capital market risk by using derivative instruments?” Therefore, the

major objective of this study is to determine the risk that banks from both emerging as

well as from recently developed countries undertake when using derivatives.

Moreover, this study also analyses the impact of four derivative instruments

(options, swaps, forwards, and futures) on three measures of capital market risk,

which are total return risk, market risk, and unsystematic risk. Enhanced regression

results were found when banks from emerging countries and those from recently

developed countries were regrouped into the same equation regression. Additionally,

a country dummy was introduced in order to identify the specificity of each country.

As a result, this study is the first paper to combine banks from both emerging and

recently developed countries in order to investigate the relationship between

derivative instruments use and bank risk.

After analysis of the using pooled data from 2003 to 2009, as well as a sample

composed of 52 banks from both emerging and recently developed countries,

noteworthy conclusions can be drawn from the empirical results. In general, the use of

options tends to increase all types of bank risk for banks of any kind. In contrast,

swaps, forwards and futures negatively affect capital market risk. Thus, overall, and

as the results show, forwards, swaps and futures may be used effectively as hedging

tools, while options may be viewed in a more speculative fashion.

In sum, the evidence suggests that with exception of options, derivative

instruments do not increase risk. In addition, as the majority of banks generally make

use of forwards and swaps, it seems clear that sample banks are not at risk by using

derivative instruments. Hence, not only should the negative implications attributed to

derivatives in the recent financial crisis be reviewed, but also, more importantly, the

argument that derivative instruments were the principal cause of the most recent

financial crisis should be revised.

19

Acknowledgments

The authors gratefully acknowledge Olfa Benouda Sioud5 for providing the premises

and outlines of the paper.

5 Laboratoire d’Economie et Finance Appliquée (LEFA), IHEC Carthage, Tunisia

20

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