An examination over effects of capital structure on risk indices in

Tehran Stock Exchange member companies

Ali Sarafraz Ardakani 1 , Ali Fazel Yazdi 2 , Hosein Shirgholami 3

Abstract

Amongst problems and issues with which investment markets and stock exchanges all around the

world are facing, their own financial structure is an important issue. Suitable combination of debts

and equity in financial structure of companies along with creation of an optimum capital structure

causes investment costs to be at minimum level and ultimately value of the companies will increase.

On the other hand the concepts of risk, yield and various definitions and indices used in recent years

to describe the risk have received significant attention. Increasing financial leverage is a risk

creating factor itself; therefore an investment selection structure which can minimize the risk while

considering suitable return is needed to be in place; so that financial managers of companies can

steer towards their main goal – increasing wealth for shareholders. This study focuses on such

information which can assist decision makers through linking capital structure to the concept of

risk. Hypotheses of the study were tested using the method of correlation and single variable

regression along with “Panel Data” technique. Results show that a significant relationship exists

between capital structure and various measures of risk. Amongst these results, a higher adjusted

coefficient (65%) is observed for the relationship between capital structure and unwanted risk (half

variance of returns). Another results state that a significant relationship between yield and risk

measures.

Keywords: capital structure, risk indices, yield, Tehran Stock Exchange

1 Department of Accounting, Payame Noor University, PO BOX 19395-3697 Tehran, I.R of Iran. Email: A.sarafraz320@gmail.com2 Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran. Email: Fazel350@yahoo.com3 Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran. Email:hosein1284@yahoo.com

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1. Introduction

Evidences in the field of financial science research suggest that investors less frequently use

quantitative approaches to evaluate stocks and their associated risks, and they mostly use intuitive

judgment and unscientific information to do this task (Mohammadi, 2004). However, intuitive

images have to be replaced with scientific results in order to develop capital market activities and

prevent failures. Techniques of implementing known methods have to be taught to managers and

investors such that they could choose correct approaches and continue to participate in investment

markets (Shafiezadeh, 1996). Risk is a key factor in all types of investigation and financial

managers encounter various sources trying to find financial resources, each of those sources is

associated with issues and challenges. Providing financial resources such as loans requires the

ability to pay the premium on due date and interest on certain time sequences. Existence of fixed

financial costs such as interest causes financial managers to pay increasing attention to commercial

firm’s ability to pay those costs and use its financial leverage and leverage level calculations as

well. Capital structure is an important and challenging issue in the field of financing which

examines the effects of capital structure of companies on company value and somehow on cost of

capital and ultimately on yield and risk of the companies. Financial leverage indicates the resources

and available cash which create fixed costs for the company. Theoretically, the more this leverage

is, the more financial risk would be for a firm (Modarres, 2008). This type of risk originates from

leverage and is controllable for managers. Therefore, a manager needs to know adequately about

how to calculate and assess leverage. Also investors usually direct their savings into investing

opportunities which produce maximum yield in relation to imposed risks. Having those said,

present study is designed and conducted to answer this main question that “whether there is a

relationship between capital structure and various risk measures among TSE1 member companies?”

Since financial leverage can significantly influence the risk accepted by the company, special

attention needs to be paid to financial leverage and its associated risk when managers plan to 1 Tehran Stock Exchange

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increase the company value. And since there are various measures exist for risk assessment and

individuals may have different definitions of risk as well, determining the relationship between

financial leverage and different risk measures introduces the importance of the issue more clearly.

Section 2 presents research history and research literature are discussed in section 3. Then the

research method used in present study is explained in section 4. Results and findings are presented

and discussed upon in section 5. And final section includes a summery, our conclusions and

suggestions for future line of research.

2. Research history

This section indicates to some local and international researches conducted in this field.

Matlabi Enzab (2001) studied the relationship between systematic risk and normal stock returns for

TSE member companies during 1995 to 1999 period. Results show that 59 percent of total risk

endured by cement and concrete companies was of systematic type in relation to normal yields of

companies; and this originates from role of government which interferes in price determination

activities in this industry. Ahmadi (2001) studied the relationship between capital structure and

company yields using a simple regression model. Results show that they could not make a solid

inference about existence of such a significant relationship. However it seems that such a

relationship is not totally ruled out. Derakhshande Dashti (2004) examined the influence of

company size and book value to market value ratio of normal stocks on stock returns and company

profitability among TSE member companies using a cross-sectional method. The results of that

study showed significant relationship between company size and stock returns during some years;

however existence of such a relationship was rejected for some other years. Significant relationships

between book to market value and stock returns and between company size and normal stock

returns were observed as well. Sadrai (2003) focused on examining the relationship between

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systematic risk and stock returns during 1998 to 2001 with emphasis on car manufacturing industry.

His results show no significant relationship between systematic risk and stock returns in car

manufacturing industry, i. e. returns could not be predicted based on systematic risk factor.

Soltanpanah and Hasani (2007) studied the relationship between yields of portfolio and financial

leverage in presence of systematic risk in chemical industry, machinery and transportation, food

industry, and plastics industry among TSE member companies. Results of hypotheses tests have

shown that there is a significant relationship between portfolio returns and systematic risk, but such

a relationship was not confirmed between financial leverage and systematic risk among TSE

member companies. Safari Jouybari (2007) studied the relationship between financial leverage and

systematic risk among TSE member companies as well. Results of that study showed significant

relationships between financial leverage and stock returns and investment yields. Study conducted

by Izadinia and Rahimi Dastjerdi (2008) examined the influence of capital structure on stock return

rate and earnings-per-share for TSE member companies. Obtained results show direct relationships

between the ratio of debt-to-equity (D/E) and stock return rate and earning-per-share (EPS) among

TSE member companies. A significant relationship between Debt-to-Assets ratio and EPS was

observed. Noravesh and Yazdani (2010) examined the relationship of financial leverage and

investment decisions among TSE member companies. They concluded that a negative and

significant relationship existed between leverage and investment. Sirani et. al. (2001) studied the

effect of liquidating risk and other factors on short-term stock yields among TSE member

companies. Results show that market risk, company size and floating stocks are significantly related

to stock yields. But no significant relation was observed between book-to-market value and

liquidating risk and stock returns. Arabsalehi et. al. (2011) studied the relationship between

environmental risks, company strategies and capital structure and performance of TSE member

companies during 2002 to 2009 period. Results obtained from this study show that significant

relationships exist between environmental risk and Free Cash Flow (FCF) per share, between

environmental risk and equity returns, and also between capital structure and FCF per share. Faff

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(2002) studied the positive relationship between financial leverage and beta risk. His results show

that relationship between those two variables should be considered in different groups of industries

when using them. Peterkort and Nielsen (2005) examined the relationship between risk and Book-

to-Market-value. They concluded that increase of Book-to-Market value along with leverage and

market value, and decrease of Book-to-Market value along with leverage and book value are good

reasons which show the ability of Book-to-Market value ratio to serve as the alternative variable for

its associated risk and return variables. Karma (2006) showed that a positive relationship exists

between leverage and risk, but risk is not merely in form of a linear function. Jin-Soo Lee and

colleagues (2007) studied the systematic risk in aviation industries. The results show that

profitability and growth are negatively correlated with systematic risk, while debt leverage and firm

size are positively related to the risk factor. Chathoth and Olsen (2007) examined the effect of

environmental risk, company’s strategy and capital structure on performance of the company. The

study results suggest that a large extent of deviations in company performance were originated from

these variables. Sivaprasad (2007) focused his study on examination of prevalent leverages and

risks in stock markets. Results of this study suggest that financial leverage significantly influences

the explanation of stock returns in London Stock Exchange. Jong et. al. (2008) concluded that

certain factors such as company size, commercial risk, growth, profitability and tangible assets are

significantly related to capital structure, while exclusive factors such as financial markets

development level, creditor rights patronage and GDP growth rate influence the capital structure of

companies; and that capital structure determinant factors are different in various countries. Chong

lee et. al. (2008) concluded that a reason for tax shields other than debts, profit fluctuability,

guarantee value of assets and company growth to be not connected with capital structure is that

those used indices are not represent the nature and characteristics proposed by financial theories yet

adequately enough.

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3. Research literature

3.1 Risk and risk measures

Risk and risk assessment is one of the most controversial issues in financial theory discussions

today. Risk could be explained as a result of lacking and not complete information; so when there is

not enough certitude about success. Risk is a mode or situation of suspicion, the possibility of

events in future that will cause loss to us, an unexpected result or event, lack of certainty, probable

changes in consequences, or any deviation from what was expected beforehand (Tehrani, 2008).

Various measures such as changes amplitude, quartile range, variance, standard deviation, absolute

deviation from mean and half variance have been introduced so far in order to quantify and evaluate

the risk. The most prevalent approach is using variance and calculating consequent beta based on

obtained value. To calculate standard deviation, first mean of the data is calculated, deviation

should be calculated and then mean sum of squares should be calculated using these deviation

figures. This is standard risk. But not any deviation from mean value can be considered as risk. To

tackle this problem, we can use half variance as a measure of undesired risk. Another reason for

using undesired risk is that stock returns data distribution may be other than normal; in that case, the

usual variance and beta values cannot satisfy the needs of risk analysts any more. Markwitz and

Roy published two independent papers in 1952 and introduced half variance as a measure of risk.

Roy did not receive much fame just because he published his paper three months after Markwitz

did. however, his researches were such important that Markwitz commented that “if Roy aimed for

introducing a method of extracting an efficient set using half variance, the portfolio theory had to be

called Roy portfolio theory” (Tehrani 2008).

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Markwitz confirmed the results obtained by Roy’s study and stated that an investor craves for

minimizing undesired risk for two reasons:

1. More consistency of undesired risk with reality and concept

2. The risk associated with possibility of un-normal distribution in stock returns.

Although half variance as a standard for measuring undesired risk was better than variance in many

aspects, Markwitz used variance in his model due to calculation problems; because he needed to

calculate matrix of half variance-cosmic variance in order to calculate undesired risk. Calculation

volume for this would be two times calculation volume for variance-covariance matrix.

3.2 Types of risk

All types of risk have to be in mind when making decisions about financial and investment issues.

Some types of risk are:

1. Business risk: is a type of risk due to fluctuations in profit before interest and tax deduction

(operational profit) (Modarres, 2009). In other words, business risk is a risk which usual

shareholders may experience even there is no debt. This type of risk originates from

uncertainties in amount of operational profit. Business risk depends on factors like demand

fluctuability, sell price fluctuability, cost of inputs fluctuability, ability of changing cost of

outputs to change of input costs and ability of producing new products in a timely manner

and under condition of higher profits than expenditures (Hampton, 2009).

2. Financial risk: originates from fluctuations in profit before tax (after interest). Financial risk

depends on fixed financial costs including interest and premium stock profit (Modarres,

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2009). In other words, additional risk which normal shareholders bear as a consequence of

decision for monetary provision through loans (Hampton, 2009).

3. Liquidating risk: Indicates the possibility of not selling assets at the current market price.

4. Payment inability risk: The risk of borrower not being able to pay back the loan or premium.

5. Market risk: is a type of risk which indicates stock price fluctuations in relation to stock

market atmosphere change.

6. Interest rate risk: The risk caused by fluctuations of asset value due to changes in interest

rate.

7. Risk of purchase power: is the risk originating from fluctuations in attainable volume of an

asset for a certain amount due to changes in price (inflation) (Modarres, 2009).

3.3 Theory of Capital Structure

Capital structure in a company is in tandem relationship with capital costs. Capital structure is the

composition of long term cash resources the company uses and any change in this composition

would lead to changes in capital costs for that company. Capital structure decisions are mainly

made in order to create suitable composition of long term cash, to minimize the capital costs of the

company through which, the market value of the company can be maximized. This composition is

called “optimum capital structure”. However, there are different opinions about existence of

optimum capital structure. The main focus of these viewpoints is that whether a company can really

influence the process of evaluation and capital costs of itself through changing the composition of

resources it uses? (Modarres, 2008).

3.4 Ratios in capital structure

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Two important ratios are used for analyzing and determining the relationship between debt and

equity in concept of capital structure composition in companies:

1. The Debts to Equity ratio (D/E ratio) (special value)

2. Total debts to total assets ratio

These ratios show that how much assets of the company is provided by debts and how much is

provided through financial investment. These provide important information about facilities and

financial provision resources in the future. If the ratio of debts is high in a company, it will face

problems in future to provide required cash through lending or new loans. In this case, the company

can only take loans with high interest rate. On the other hand, low debts ratio (and company without

debts) show company’s failure to implement low interest rate loans which causes decrement in

earnings per share.

There are three main ways to implement capital structure ratios:

To identify cash resources: Company uses debt sources or financial provision capital to

satisfy all its financial needs. The usage amount for each financial source is determined by

ratios from capital structure.

To measure monetary risk: A measure for determining risk level which is created by

financial provision through debt would be calculated using these ratios.

To predict loans perspective: If the company is in financial need to expand its activities,

capital structure ratios can determine whether debt cash is available or not. In case these

ratios are very high, the company may not be able to borrow (Vakili fard, 2012).

4. Research method

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Present research method is chosen with consideration of goal, nature, subject and our available

operational facilities. This research is of applied research type. Our research method is field based

which uses event history as post-event data and is performed based on financial lists information of

the companies. A library research approach was used to study literature about research topic. Data

about independent and dependent variables were extracted from reported information of financial

listings and descriptive notes created by sample companies between 2006 and 2009. Those data

were gathered using “Rahavard-e Novin” and “Aria Sahm” from TSE, DVDs containing financial

data of TSE member companies, and management bureau of research, development and Islamic

studies online database. Correlation coefficient method and data panel regression method using

Eviews software were applied in order to test research hypotheses. The statistical population

included all companies which were accepted as members of TSE. This statistical population was

chosen because financial data for TSE member companies are easily available and also data are

homogeneous due to TSE applied regulations. Therefore, data analysis would be done better.

Considering spatial and time scope of the research, the statistical sample was selected so that

sample companies are not investment firms and brokers while their managerial and financial data

required for our study are available.

4.1 Research hypotheses

Present study consists of one main hypothesis and three subsidiary hypotheses as follows:

Main hypothesis

There is a significant relationship between capital structure and various risk gauges for TSE

member companies.

Subsidiary hypotheses

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1. A significant relationship exists between financial leverage and risk sensitivity measure

(beta coefficient) for TSE member companies.

2. A significant relationship exists between financial leverage and risk fluctuation measure

(yield variance) for TSE member companies.

3. A significant relationship exists between financial leverage and undesired risk measure (beta

half coefficient) for TSE member companies.

5. Study results

5.1 Descriptive statistics of the research

As mentioned before, the statistical sample included 70 companies which are active in TSE and

their financial data over 2006 to 2009 period were examined. Those data were extracted from

“Rahavard” software and also from TSE website. Were transported to excel spreadsheets in which

required calculations were made in order to calculate financial ratios (leverage), variance, and half

variance. Data in Table (1) contain descriptive statistics information.

Table 1- Descriptive statistics of four year period (research findings)

Variables No. Min. Max. Mean Std. Dev.D/E 280 0.25 40.98 1.6 15.41D/Em 280 0.09 9.73 2.34 2.65D/A 280 0.23 1.12 0.65 0.19β 280 -2.82 8.40 0.53 1.28yield variance 280 0.00 2596 159.09 302.83yield half var. 280 0.00 622.85 52.23 72.56yield 280 -66.21 820.16 35.91 92.19

5.2 Testing first subsidiary hypothesis

H0: There is no significant relationship between financial leverage and risk sensitivity measure (β)

for TSE member companies.

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H1: There is a significant relationship between financial leverage and risk sensitivity measure (β)

for TSE member companies.

Three variables representing financial leverage in the company are: ratio of debt to equity book

value (D/E), ratio of debt to equity market value (D/EM), and ratio of debt to assets book value

(D/A). Correlation and regression tests are used to test those hypotheses. The obtained results are

summarized in Table 2. Note that hypothesis H0 is rejected whenever prob ≤ 0.05 and therefore H1

is confirmed and vice versa.

Table 2- Results from financial leverage hypothesis test using beta (research findings)

Var

iabl

es

Beta coefficient

Adjusted R2 Durbin-Watson Coefficient Prob coef. Acceptance

D/E 0.51 2.04 0.003 0 Accept

D/Em 0.41 1.97 -0.11 0 Accept

D/A 0.42 1.92 0.99 0 Accept

Regarding first subsidiary hypothesis, the relationship between capital structure and systematic risk

gauge was tested. Three variables of debt to equity book value, debt to equity market value and debt

to assets book value ratios were considered as representing indices for capital structure. Obtained

results show that:

Since prob ≤ 0.05 , we can say there is a significant relationship between capital structure

and beta coefficient (β, systematic risk index).

Above mentioned coefficients show the existence of a direct relationship between D/E , D/A

and β coefficient; i. e. as debt amount increases in capital structure, systematic risk does

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increase as well. This result is in concordance with theoretical viewpoint and results

obtained by Jalilvand, Poorkasgary (1996), Mandelker (1984), Hamada and Masolis (1983).

However they are in contradiction with results of Keshtkar (2001), Ahooyee (2004) and

Ghrbani (1999). However the relationship between D/EM and β coefficient is a reverse

relationship which contradicts theoretical concepts.

Adjusted R2 coefficient shows that 51 percent of changes in systematic risk (pertaining to

ratio of debt to equity book value) can be justified in relation to capital structure ratios. Since

the level of adjusted R2 is higher for relationship between D/E ratio and β, we can claim that

D/E ratio has more strength than other two ratios to influence systematic risk fluctuations.

The durbin-watson statistic also suggests lack of correlation between error term

(1.5 ≤ D.W ≤ 2.5).

5.3 Testing second subsidiary hypothesis

H0: There is no significant relationship exists between financial leverage and risk fluctuation

measure (yield variance) among TSE member companies.

H1: A significant relationship exists between financial leverage and risk fluctuation measure (yield

variance) among TSE member companies.

Three ratios of debt to equity book value, debt to equity market value and debt to assets book value

are the indicators of financial leverage of companies. Table 3 shows information required for testing

hypothesis of correlation between financial leverage and yield variance.

Table 3- Statistics resulted from correlation test between financial leverage and yield variance

(research findings)

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Var

iabl

es yield variance

Adjusted R2 Durbin-Watson Coefficient prob coef. Acceptacne

D/E 0.45 2.37 0.8 0.05 Accepted

D/Em 0.45 2.39 5.93 0 Accepted

D/A 0.46 2.38 221.27 0 AcceptedThe results obtained from testing second subsidiary hypothesis are as following:

The values of prob statistic for each test suggest that there is a significant relationship

between capital structure indices and yield variance gauge (prob ≤ 0.05).

Coefficients in table 3 show a direct relationship between capital structure and yield

variance, i. e. the more debt in capital structure, the more fluctuations in yield would be; and

that means more risk for the company. These results are in concordance with theoretical

viewpoints.

Adjusted determination coefficient (Adjusted R2) in this hypothesis shows that 46 percent

(related to D/A ratio) can be determined via changes of yield variance through capital

structure indices.

Durbin-watson statistic also suggests that no correlation exists between error terms in this

test.

5.4 Testing third subsidiary hypothesis

H0: There is no significant relationship between financial leverage and undesired risk measure (half

variance of the yield) among TSE member companies.

H1: A significant relationship exists between financial leverage and undesired risk measure (half

variance of the yield) among TSE member companies.

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Three ratios of debt to equity book value, debt to equity market value and debt to assets book value

are the indicators of financial leverage of companies. In concept of third hypothesis, the relationship

between capital structure and measure of undesired risk (yield half variance) was investigated.

Obtained results are shown in Table 4.

Table 4- Results of testing financial leverage with half variance of the yield (research findings)

Var

iabl

es yield half variance

Adjusted R2 Durbin-Watson Coefficient prob coef. Acceptance

D/E 0.65 2.5 0.26 0.003 Accepted

D/Em 0.65 2.5 3.95 0 Accepted

D/A 0.59 2.5 34.9 0.005 Accepted

As the statistics in Table 4 suggest:

There is a significant relationship between capital structure and yield half variance (probe ≤

0.05).

As the amount of debts in capital structure increases, undesired risk increases as well (direct

relationship). This result is in concordance with theoretical viewpoints.

Adjusted determination coefficient (Adjusted R2) suggests that 65 percent of changes in half

variance of the yield can be justified through capital structure.

Durbin-watson statistic also suggests that no correlation exists between error terms in this

hypothesis.

6. Summary, conclusion and propositions

Financial managers and investors are paying more and more attention to subject of decisions related

to capital structure and its effects on yield and risk in companies. Various opinions and theories

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exist about capital; and each of them involves some assumptions not in full accordance with real

world, however acceptable results could be achieved through omitting an assumption on each stage.

Miller and Modiliani did some studies on capital structure in 1958. Their study included

assumptions like efficient market, no bankruptcy, no taxes … which were in contradiction with real

world. They concluded that the value of a economical unit is independent of its capital structure.

When the issues of tax facilities, bankruptcy costs and representative costs were proposed, it was

shown that using financial leverage at first stages causes the value of company to increase (due to

tax advantages), but however costs of bankruptcy and representing would decrease company’s

value when financial leverage crosses some limit amount. Each of those factors influence on yield

of the company and lead to increase of earnings per share if the company can create yield which is

higher than interest rate, and vice versa. In theory, increasing financial leverage causes financial

risk to increase as a result of higher leverage; and may lead to bankruptcy and breakup in bad

situations. Financial managers have different choices before them for financial provision and need

to evaluate various choices in sense of risk, flexibility, control, etc. They have to choose the best

way to maximize wealth for stockholders. Considering existing theoretical concept in capital market

and financial leverage, and their effects on yield and company value, also considering that each

choice of financial supply can influence the flexibility, yield, risk, etc. of the company; this question

raises that “Whether there is a significant relationship between capital structure of the companies,

their risk and yield in TSE? And whether capital structure can state a certain measure of risk?” The

research hypotheses were tested through a proposed pattern and using correlation coefficient and

regression methods of data panel by “Eviews” software. Results from mentioned software were

analyzed afterwards. Results pertaining to the first hypothesis suggest that a significant relationship

exists between mentioned measures and systematic risk. While the models based on D/E and D/A

leverage measures confirm the existence of a positive relationship between capital structure and

systematic risk gauge; and show a negative relationship between D/EM and systematic risk. Thus,

only the model based on relationship between debt and equity market value was not consistent with

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theoretical concepts. Moreover, the model based on D/E ratio justified 51 percent of changes in

systematic risk which was better than other models in this regard. Results obtained from second

hypothesis test showed a positive and significant relationship between all three representatives of

capital structure and yield variance measure. Note that adjusted determinant coefficient statistic

values were almost equal for all three cases, which shows equal strength of these measures to justify

risk fluctuations. Results of third hypothesis tests suggest that a positive and significant relationship

exists between three representatives of capital structure and undesired risk. Again note that the

value of adjusted determinant coefficient in this hypothesis is higher than its value in other two.

Since according to theoretical concepts undesired risk is considered to be a better measure in

asymmetric markets, it seems that results of this hypothesis show the weakness and some extent of

asymmetry of capital market in Iran. Since the relationship between capital structure measures and

undesired risk (yield half variance) were stronger than in other models, we recommend investors to

pay more attention to this measure when examining risk in companies, and although some

experimental researchers did excess care about systematic risk measure (β), but this measure is not

an adequate gauge of company risk because of weak performance of Iranian capital market.

Therefore, we recommend investors and financial analysts to pay less attention to this measure and

assign lower weight to it when making decisions about investment.

Since the results obtained from present study can be used by future researches in this field, we

recommend the following items to be considered in future researches:

Some industries use higher levels of debts in their capital structure. Therefore we propose

the relationship between capital structure and risk be studied in sense of industry type.

We suggest current TSE member companies to be categorized according to their lifetime and

mentioned hypotheses be tested in those cases.

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Many factors have their effects on risk. Thus we propose to consider other factors such as

ratio of market value to share book value, sales growth, profit etc. in adequate models and

test for their separate and aggregated effects on risk.

We propose the effect of foreign exchange facilities on risk and company yields to be

examined and analyzed.

Since most of the conducted researches in this field have covered a short time period, more long

term studies are recommend in order to increase reliability of the results.

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