an examination over effects of capital structure on risk indices in tehran stock exchange member...
DESCRIPTION
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.TRANSCRIPT
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: [email protected] Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran. Email: [email protected] Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran. Email:[email protected]
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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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