CHAPTER 2 LITERATURE REVIEWshodhganga.inflibnet.ac.in/bitstream/10603/72419/8/chapter 2.pdf · developed under assumptions that characterize an ideal capital market (also called a

CHAPTER 2

LITERATURE REVIEW

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CHAPTER П

REVIEW OF LITERATURE

2.1. Firm valuation models

Some of the most important contributions to financial economics are models

of the valuation of securities and their implications for corporate financing decisions

developed under assumptions that characterize an ideal capital market (also called a

perfect capital market). Researchers developed theoretical models of the valuation of

financial assets. Each model has distinct characteristics based on distinct approaches

to the problem of valuation, yet all have been developed under ideal capital market

assumption. Remarkably, all of the models are discussed are jointly reconcilable.

These valuation models have two important implications. (a) They provide

explicit valuation models for a firm and its debt and equity securities; and (b) they

specify the effects of the firm’s choice of capital structure (i.e., mix of debt and

equity financing) on the risk and required expected returns of its securities.

The first and third models that is discussed, the Modigliani-Miller (1958)

capital structure irrelevance theorems and Black-Scholes (1973) option pricing

model, yield conditional specifications of the values, risk, and required expected

returns on corporate securities based on arbitrage arguments. The second model, the

capital asset pricing model (Sharpe 1964; Lintner 1965; Mossion 1966), provides

general equilibrium specifications of the values, risk, and expected returns on assets

based on jointly reconcilable, that are under specified conditions, the three models

yield the same results with respect to the values, risk and expected returns on a

levered firm’s debt and equity securities. The reconcilability of these theoretical

models constitutes an important unification theory as it relates to both valuation and

corporate financing decisions under ideal market conditions.

Defining an ideal capital market

An ideal capital market is defined by a set of five assumptions.

Assumption 1: capital markets are frictionless. Market participants face no

transaction costs or taxes. Investors face no brokerage commissions or fees on

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trades, and short selling is unrestricted. Firms face no transaction costs in issuing or

retiring securities, and there are no costs associated with bankruptcy.

Assumption 2: All market participants share homogenous expectation, value-

relevant information is costlessly available to all market participants, and all

participants rationally process such information to determine the value of any

security. Thus, all participants share common expectations about the prospects of

investments.

Assumption 3: All market participants are atomistic. No single market participant

can affect the market price of a security via trades.

Assumption 4: The firm’s investment program is fixed and known. The firm’s

capital investment program, and therefore its assets, operations, and strategies, are

fixed and known to all investors.

Assumption 5: The firm’s financing is fixed. Once chosen, the firm’s capital

structure is fixed.

In establishing these assumptions, it is recognized that they may conflict with

activities actually observed in the real world (i.e., in actual capital market). The

purpose of studying theory under ideal capital is twofold. First, insights into the

effects of a firm’s decisions on the values and risk of its securities is gained (i.e.

such decisions may yet have the predicted effects even if real-world conditions only

approximate the ideal). Second, armed with an understanding of the effects of

corporate financial decisions under ideal conditions, it is a better position to

understand the incremental effects (where the increments may be large) of certain

real-world factors (which constitute violations of one or more of the ideal capital

market assumptions).

Modigliani and Miller’s Original propositions

In 1958, Franco Modigliani and Merton Miller (henceforth, M&M)

published a land mark paper in the American Economic Review: “The cost of

capital, corporation finance and the theory of investment.” In this paper they defined

the assumptions of an ideal capital market, and developed two important (and

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controversial) propositions concerning the effects of corporate financing decisions

on the values and risk of a firm’s debt and equity securities.

M&M Proposition I: the market value of a firm is constant regardless of the

amount of leverage. (i.e., debt relative to equity) that the firm uses to finance its

assets.

Proposition I implies that firm’s management cannot change the market

value of the firm merely by altering its capital structure. This proposition is also

referred to as the leverage Irrelevance Theorem or the capital structure Irrelevance

theorem.

M&M proposition II: the expected return on a firm’s equity is an increasing

function of the firm’s leverage.

As it will be observable, proposition II follows directly from proposition I. It

is important because it shows that leverage does have effects_ specifically, on the

risk and expected return of a firm’s equity_ despite the conclusion from proposition

I that leverage has no effect on the overall value of the firm.

Analysis of M & M proposition I

Market Value of a Firm

The market value of a firm is, by definition, equal to the sum of the market

values of all claims on its cash flows (i.e., all of the firm’s outstanding securities).

Consequently, the market value of an unlevered firm is defined as the total market

value of the firm’s equity shares. Whereas the market value of a levered firm is

defined as the sum of the total market values of its debt and equity securities. In

addition, because investors can derive value from holding the firm’s securities only

because the firm holds assets that have value and produce income, against which the

security holders have a claim, we can interchangeably refer to the value of the firm

or the value of the firm’s assets. Thus, equation 2.1 and 2.2 can be stated in

definition form:

For an unlevered firm: VU ≡ EU (2.1)

And

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For a levered firm: VL≡ D + EL (2.2)

In equation 2.1, VU denotes the market value of (the assets of) an unlevered

firm and EU denotes the total market value of its equity shares. In equation 2.2, VL

denotes the market value of (the assets of) a levered firm, and D and EL denote the

total market value of its debt and equity securities, respectively.

Proof of M&M Proposition І via Arbitrage Argument

Given definitional equation 2.1 and 2.2, M&M proposition І states that

market value of a firm (defined by a fixed set of assets) is constant regardless of the

amount of leverage it employs. Proposition І is expressed in equation 2.3, which

holds that, for all possible levels of leverage

VU = VL (2.3)

Arbitrage is the basis for M&M proposition І. To explain the arbitrage

involved, consider two scenarios in which equation 2.3 does not hold. In the first

scenario, a firm’s assets are currently financed entirely with equity that has a total

market value of EU ≡ VU. But suppose the firm’s assets could instead be financed

with specified proportions of both debt and equity, and that the resulting market

value of the levered version of the firm is VL≡D + EL, where VL > VU. Under these

circumstances, any investor, acting as a arbitrageur, could simply (a) purchases the

fraction α of the existing firm’s equity at a cost of αVU, (b) place these equity shares

in a trust, and then (c) sell securities that present debt and equity claims against the

shares in a trust. The total proceeds that the investor would receive for these debt

and equity claims would be α (D+EL), or equivalently, αVL, given the inequality

specified above the investor would realize an instant arbitrage profit of α(VL – VU).

In the second scenario, the firm’s assets are currently financed with specific

proportions of both debt and equity such that the market value of the firm is VL≡D +

EL. however, let us assume that VL< VU, where VU ≡ EU is the market value of the

firm if it were instead financed entirely with equity. Under these circumstances, an

arbitrageur could simply (a) purchase equal proportions, α, of the debt and equity of

the firm at a cost of αVL = α(D +EL); (b) place these securities in a trust; and (c) sell

shares of a new security that represents equity ownership of the securities in the

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trust. The arbitrageur can sell these shares at a total price of αVU > αVL, and thereby

realize an instant arbitrage profit of α (VU- VL).

Note that, in either of these scenarios, all investors would attempt to perform

the indicated arbitrage, and their collective trading activity would alter market

values until any such arbitrage is eliminated.

Analysis of M&M Proposition ІІ

Modigliani and Miller’s Proposition ІІ, which relies on the result of

proposition І, states that the expected return on a firm’s equity increases with the

firm’s leverage. To explain proposition ІІ, a firm’s weighted average cost of capital,

or WACC, is defined.

A firm’s WACC is a value-weighted average of the required expected

returns on, or costs of, the firm’s debt and equity denoted as 푟 and 푟 respectively.

The formula for WACC is given in equation 2.4.

푊퐴퐶퐶 = 푟 [ ] + 푟 [ ] (2.4)

{source:(Ogden, et al., 2003)

A firm’s WACC can be interpreted as the implicit discount rate used by the

market on the firm’s future cash flows to determine the value of the firm’s assets

under a specified capital structure. As such, a firm’s WACC can be alternatively

denoted as 푟 , the required expected return on the firm’s assets under a specified

capital structure. Therefore, 푟 can be substituted for WACC in equation 2.4,

yielding equation 2.5.

푟 = 푟 [ ] + 푟 [ ] (2.5)


However, via proposition 1 the value of the firm’s assets does not vary with

change in the firm’s capital structure. Therefore, proposition І implies that 푟 must

also be constant regardless of the firm’s leverage. This is important because it

implies that the expected return on the firm’s assets (specifically the riskiness of the

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assets) and not on the firm’s capital structure. By extension, it implies that a firm’s

capital budgeting decisions (i.e., the firm’s choice of projects to pursue) should be

made by discounting the expected future cash flows of any proposed project (using a

discount rate based on the riskiness of the project, regardless of how it will be

financed and then comparing the present value of the expected future cash flows to

the initial cost of the project.

With this background, it can be now expressed proposition ІІ in equation

form. Solving equation 2.5 for 푟 yield equation 2.6:

푟 = (푟 − 푟 ) (2.6)


That is, the required expected return on a firm’s equity is equal to the

required expected return on the firm’s assets, 푟 , plus an adjustment that is the

product of a measure of the firm’s leverage ( ) and the difference between the

required expected returns on the firm’s assets and the firm’s debt (푟 − 푟 )

So does equation 2.6 automatically imply that proposition ІІ is true? Two

considerations can be combined to suggest that proposition ІІ is indeed correct. First,

we know from proposition І that 푟 is constant regardless of . Second assuming

that the firm’s assets are risky and investors require a premium on the expected

returns on risky assets (including securities), then 푟 will be greater than 푟 , and

thus (푟 − 푟 ) > 0. This will be so because the firm’s earnings (i.e., they get paid

first), and thus the risk they face is generally less than the risk of the firm’s overall

earnings. Therefore, if 푟 is constant and (푟 − 푟 ) > 0 it appears that 푟 will

increase with .

However, to address this question properly we must examine the behavior of

the terms on the right side of equation 2.6 more closely. We can do this best by

taking the derivative of 푟 in equation 2.6 with respect to , recalling in doing so

that rA is constant via proposition І. The result is given in equation 2.7

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= (푟 − 푟 )− (2.7)


In essence, proposition ІІ states that the derivative in equation 2.7 will be

positive for all levels of leverage. However, whether 푟 increases with depends

on the values of the two expressions on the right side of equation 2.7. To assess the

possible values of these expressions, it is needed more information about how the

market determines the required expected returns on the firm’s assets and its

securities. Specifically, more information on 푟 and 푟 is needed.

Suppose initially that investors are neutral with respect to the risk of the

firm’s assets – that is they do not demand a premium for risk of the firm’s assets.

Then 푟 = 푟 where 푟 is the return on a risk-free security such as a Government

treasury bill. Furthermore, the risk of both the firm’s debt and equity are strictly

functions of the risk of the firm’s debt and equity securities; therefore, 푟 = 푟 = 푟

will hold as well, regardless of the firm’s leverage. Note that, in this case, the values

of 푟 , 푟 , and 푟 are consistent with equation 2.6. However, the results are

inconsistent with proposition ІІ because 푟 does not vary with

A more realistic assumption is that 푟 contains a risk premium. In this case,

the expected return on the firm’s equity will also contain a risk premium, as will the

firm’s debt, if the debt is risky. But for the moment, it will be assumed that the

firm’s debt is risk-free for all possible values of . In this case rD will be equal to

푟 . The derivative on the right side of equation 2.7 will be equal to zero, and 푟 will

be an increasing linear function of , with a slope coefficient of (푟 – 푟 ) =

(푟 – 푟 ), as can be seen from either equation 2.6 or 2.7.

However, although debt may be virtually default-free for a few firm, this is

not the case in general, a more general scenario is specified with assumption A

and B.

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Assumption A: Investors demand a premium for the risk of a firm’s

securities.

Assumption B: The firm’s debt is risky and its risk increases with the firm’s

leverage.

It follows that (a) 푟 must also increases with leverage; (b) the derivative

term in brackets in the right side of equation 2.7 is positive; and thus (c) the entire

expression ( ) [휎 푟 / 휎 ( )] is positive therefore, it is not clear from inspection of

equation 2.7 that 휎 푟 / 휎 ( ) is positive as proposition ІІ asserts, because the right

side of equation 2.7 is the difference of two expressions, both of which are positive

and the size of either of these expressions for any given level of leverage cannot be

determined.

In the end, the present model structure is insufficient to prove that

proposition ІІ is true. It can be only argued that proposition ІІ has merit because

equity holders, who have only a residual claim to the firm’s assets, bear more risk

than debt holders, who have a priority claim: therefore, 푟 should be greater than 푟

for any given level of leverage.

Moreover, it seems likely that, when leverage increases in risk per dollar of

investment than do debt holders, in which case 푟 must increase at a faster rate with

than does rD, in which case proposition ІІ will be true. However, to address the

issue formally, greater specification of the nature of the firm’s risk and that of its

debt and equity securities, as well as the market’s required compensation for risk in

the form of an expected return premium are required.

Fortunately, as it is visible, the Capital Assets Pricing Model and the Black-

Scholes option pricing model combine to provide such specification (although, too,

are only models).

As a final comment on the M&M model structure, note that the firm’s assets

are fixed, so the total amount of firm risk is constant and must be born in its entirely

the firm’s claimants – debt holders and equity holders – for any level of leverage. By

extension, a change in the firm’s leverage simply involves a redistribution of the

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firm’s total risk among the claimants. If it is also assumed that the market provides

compensation (in the form of expected return premium) that is linearly related to the

risk borne by a given claimant, additional insight into the behavior of 푟 and 푟 as

specific is gained.

For instant, when it is assumed that 푟 > 푟 and that the firm’s debt is risk-

free for all levels of leverage (which implies that debtholders bear none of the firm’s

risk while equityholders bear all of the firm’s risk), it was found that the expected

return on the equity increases linearly with leverage-specifically, at the rate of

푟 – 푟 per unit change in . However, when it is allowed to the risk of the firm’s

debt to be positive and to increase with leverage, the required expected return on the

debt also increases with leverage (i.e., 휎 푟 / 휎 ( ) > 0 in equation 2.7); then it is

found that the required expected return on the firm’s equity increases at a slower rate

with leverage, (푟 – 푟 ) − ( ) [휎 푟 / 휎 ( )] < (푟 – 푟 ). This is logical

because debtholders are bearing an increasing share of the firm’s risk as leverage

increases.

Capital Asset Pricing Model

Modern Portfolio Theory (MPT) involves two basic constructs: the statistical

effects of diversification on the expected return and risk of a portfolio; and the

attitudes of investors toward risk; specifically, it is assumed that investors are averse

to risk, but are sufficiently tolerant of risk to bear it if sufficient compensation (i.e.,

higher expected return), is provided.

MPT assumes that investors are concerned only with the expected return and

standard deviation of their overall portfolio. MPT addresses the task of identifying

the portfolio that maximizes an investor’s expected utility given the investor’s

willingness to trade-off risk and expected return.

Statistics for a Portfolio of Two Securities

To begin a brief review of the statistical effects of diversification on

portfolio’s expected return and risk, consider two securities, A and B. The expected

returns on these securities are denoted as 푟 and 푟 , respectively, and their return

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standard deviation are denoted as 휎 and 휎 , respectively. The correlation between

the returns on securities A and B is denoted as 휌 , where of course, −1 ≤ 휌 ≤

1.

The expected return on a portfolio of securities A and B, denoted as 푟 is:

푟 = 푤 푟 + 푤 푟 (2.8)


Where 푤 and 푤 are the portfolio weights, the proportions of the investor’s

wealth invested in securities A and B, respectively. (푤 + 푤 = 1)

The standard deviation of portfolio, denoted as 휎 , is

휎 = [푤 휎 + 푤 휎 + 2푤 푤 휎 휎 휌 ]ퟏ/ퟐ (2.9)


Statistics for an N-Security Portfolio

For the general case in which the investor’s portfolio contains N

securities, 푟 and 휎 are calculated using Equation 2.10 and 2.11, respectively.

푟 = ∑ 푤 푟 (2.10)


휎 = [∑ ∑ 푤 푤 휎 ] / (2.11)


Where σij = σiσjρ if i ≠ j and σij = σi , if i = j. That is, if i ≠ j, σij is the

covariance between returns on securities i and j, whereas if i = j, variance of security

i is obtained.

In the special case in which the investor places equal amounts of money into

each of N securities, 푟 and 휎 are calculated using Equation 2.12 and 2.13,

respectively.

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푟 = ∑ 푟 (2.12)


휎 = [ ∗ 휎 + 1 − ∗ 휎 ] / (2.13)


Where 휎 is the average variance of the individual securities in the portfolio,

and 휎 is the average of all pairwise covariances. Note that as N → ∞, the first term

in brackets in Equation 2.13 approaches zero, while the second term converges to

휎 . It is in this sense that the variance of a well-diversified portfolio is determined

entirely by covariances and not at all by the variances of the individual securities.

The average covariance of a diversified portfolio is somewhat difficult to

interpret, so the following alternative formula can be offered. In most practical

circumstances, 휎 can be approximated by the product of the average of all pairwise

correlations among the securities, denoted as 휌̅ and 휎 ; that is 휎 ≈ 휌̅ 휎 .

Therefore, as N → ∞,

휎 ≈ 휌̅ 휎/

(2.13a)


Risk Aversion and the Investor’s Optimal Portfolio in the Absence of a Risk-

Free Security

Many securities are available in Indian financial markets today with varying

expected return, standard deviation and correlations with other securities. Moreover,

a virtually infinite number of portfolios can be developed by varying the number of

securities in the portfolio, the specific securities included, and the portfolio weights

applied to each security.

Among all portfolios of risky securities, the choices can be narrowed

considerably by eliminating all portfolios that are dominated. A portfolio is

dominated if another portfolio provides both a higher expected return and lower risk

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(i.e., lower return standard deviation). In other words, a dominated security or

portfolio is relatively inefficient in terms of providing compensation for risk.

After eliminating all dominated portfolios, only efficient portfolios are

remained, which it is represented in Figure 2 in Appendix A, a continuous, concave

curve in 푟 − 휎 space known as the efficient frontier. The figure also shows

indifference curves and optimal portfolios for two investors; Mr. Moreaverse and

Mr. Lessaverse, whose respective tolerances for risk are indicated by their names.

Market Equilibrium: The Capital Market Line (CML)

In the equilibrium derived in the CAPM, investors collectively hold all risky

securities, and all individual investors hold the same portfolio of risky securities, and

all individual investors hold the same portfolio of risky securities. In this market

portfolio, denoted as M, the portfolio weight for each risky security is equal to the

ratio of the total market value of the security to the total market value of all risky

securities. As in the (nonequilibrium) depiction of portfolio choice shown in 3 in

Appendix A, each and every investor chooses a complete portfolio, C, consisting of

weighted investments in the risk-free security and the market portfolio that is

consistent with their risk tolerance. Therefore, the choices available to investors

create a line in 푟 − 휎 space that is formed by the points representing the risk-free

security and M. this line is called the capital market line, or CML:

푟 = 푟 + (푟 − 푟 ) (2.14)


The Security Market Line

The CAPM also specifies the market equilibrium expected return on any

individual security as a function of its relative contribution to the risk of the market

portfolio. For any security, 푟 is a function of the security’s beta, denoted as 훽 and

defined in equation 2.15:

훽 = (2.15)


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Where 휎 is the covariance of returns on security i and the market portfolio,

and 휎 is the variance of returns on the market portfolio.

Formally, the relationship between the equilibrium expected return on any

asset i, 푟 and 훽 is given in equation 2.16:

푟 = 푟 + 훽 (푟 − 푟 ) (2.16)


The Binomial Pricing Model

The Binomial Pricing Model is a simple model both to provide an alternative

proof of M&M Proposition І and to explore firm-specific return relationships that

depend on the firm’s capital structure.

Assumptions of Binomial Pricing Model

The assumptions required for the Binomial Pricing Model include all of those

associated with the ideal capital market, plus an additional assumption about the

distribution of the future value of a firm’s assets. With this additional assumption,

discussed next, the model uses arbitrage arguments to determine the values of a

levered firm’s debt and equity securities.

The Distribution of a Firm’s Future Value in the Binomial Pricing Model

The binomial distribution provides the simplest model of risk. Applied to a

firm’s assets, values of the assets are modeled over a single period, which extends

from date 0, the current date, to date T, a future date. The future value of the assets

can take on only two possible values, which are defined relative to the assets’

current value. Denoting the current value of the firm’s assets as V, the future value

of the firm’s assets can take on only one of two possible values, 푉 or 푉 , where

푉 > 푉 and 푉 < 푉 . That is , over the single period involved, the value of the

firm’s assets can either rise to 푉 or fall to 푉 .

Choices of values for 푉 and 푉 define the riskiness of the firm’s assets.

Appropriate values for 푉 and 푉 depend on three factors: (a) the value of V, (b) the

actual riskiness of the value of the firm’s assets that it is attempting to model, and

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(c) the span of time involved in the model’s single period. To address (a), it is

generally assumed that 푉 and 푉 represent proportional “up” and “down” jumps

relative to V. The up jump is denoted as u, where u >1, and the down jump is

denoted as d, where d = 1/u <1. Thus,

푉 = 푢푉 (2.17)

And

푉 = 푑푉 (2.18)

Regarding factors (b) and (c), it is generally wished to model risk as a

function of time, where risk increases with the length of the period. To do so, factors

(b) and (c) simultaneously must be addressed. For instance, to model the riskiness of

the assets of a particular firm, if the length of the period is a year, a particular value

of the risk parameter u would be choosed, whereas if the period is five years,

another larger value of u should be specified Cox, Ross, and Rubinstein (1379)

provided a formula for the parameter u that produces an approximation for the

riskiness of the firm in terms of the per-annum return standard deviation, as if the

returns were normally distributed. The formula is

푢 = 푒 √ (2.19)

Where σ is the per-annum return standard deviation of the firm’s assets, and

T is the length of the model’s period in years. This formula allows us to specify

reasonable values of u.

The Expected Return on the Firm’s Assets

To complete the specification of the binomial distribution of a firm’s assets,

the probabilities of the up and down jumps must be specified. p is denoted as the

probability of an up jump, so the probability of a down jump is (1-p). Consequently,

the expected value of the firm’s assets at date T, 퐸(푉 ) ,is

퐸(푉 ) = 푝 푉 + (1 − 푝)푉 (2.20)


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And the expected return on the firm’s assets is

푟 = 푝 + (1 − 푝)[ ] (2.21)


The Binomial Pricing Model and the Valuation of the Debt and Equity of a

Levered Firm

If the future value of a levered firm’s assets follows the binomial

distribution, the values of the firm’s debt and equity can be determined. It is

assumed that the firm has pure-discount debt consisting of a promise to pay debt

holders the amount X at date T

Case 1: Default-Free Debt

퐷 = ( )

푖푓 푋 < 푉 (2.22)


And the value of the firm’s levered equity is, as before,

퐸 ≡ 푉 − 퐷 (2.23)


The actual payoff on levered equity at date T depends on the value of the

firm’s assets at date T. Denoting the equity payoffs in the up and down states as 퐸

and 퐸 ,

퐸 = 푉 − 푋

And

퐸 = 푉 − 푋

The formula for the expected return on the firm’s levered equity, 푟 , is

푟 = 푝 + (1 − 푝) (2.24)


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Case 2: Default-Risky Debt

If the firm’s debt is default-risky (i.e., 푉 > 푋 > 푉 ), in the up state,

bondholders will receive the promised amount of X, so 퐷 = 푋and equityholders

will receive 퐸 = 푉 − 푋. In the down state, the firm defaults; bondholders receive

퐷 = 푉 < 푋 and equityholders receive nothing 퐸 = 0.

We can value the firm’s equity and debt by creating a risk-free hedge

portfolio with a long position in the levered firm’s assets and a short position in 훿

units of the firm’s levered equity. The value of 훿 must be chosen so that the

portfolio has the same payoff in both the up and down states:

[푉 − 훿퐸 ] = [푉 − 훿퐸 ] (2.25)


Given hedge ratio:

훿 = (2.26)


The cost of this portfolio is 푉 − 훿퐸 where 퐸 is the unknown that we wish

to determine. The portfolio is riskless, so its present value, or cost, must be equal to

the discounted value of the date T payoff, discounting at the risk-free rate. The

expressions on both the left side and the right side of Equation 2.25 represent the

common date T payoff on the portfolio, so we can choose either. We arbitrarily

select the left side expression; the cost of the portfolio must be equal to the present

value of this expression:

푉 − 훿퐸 = ( )

(2.27)


The value of the levered equity is:

퐸 = 푉 − 푉 − 퐸 /(1 + 푟 ) (2.28)


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The Black-Scholes Option Pricing Model (BSOPM)

Fisher Black and Myron Scholes developed a formula to value European

options written non-dividend paying stocks. This model, which is now known as the

Black-Scholes Option Pricing Model (BSOPM), was instrumental in the

development of U.S. option markets, which began trading in the same year in

Chicago.

Their model can be applied to the pricing of (a) the debt and equity of a

levered firm, (b) various options embedded in stock-related securities such as

warrants (c) options embedded in corporate bonds such as call and put provisions (d)

the conversion option in convertible bonds and (e) stock option grants in executive

compensation contracts.

As with the other models it has been already discussed, the BSOPM is

developed under the assumptions of an ideal capital market. Black and Scholes also

assumed that (a) the risk-free interest rate is constant and (b) the future value of the

underlying asset against which the option is written is log-normally distributed, or

equivalently, the instantaneous returns on the underlying asset are normally

distributed with a constant mean (휇) and variance (휎 ) .

The derivation of the BSOPM involves the construction of a risk-free hedge

portfolio involving the underlying asset and the option, as was the case for the

Binomial Pricing Model. For their model, however, Black and Scholes must assume

that risk-free portfolio will be continuously rebalanced. Nevertheless, a risk-free

portfolio can be constructed at each instant of time because instantaneously the

returns on the asset and the option are perfectly correlated. By continually

rebalancing the hedge portfolio so that it remains risk free, Black and Scholes were

able to derive a closed form solution for the price of the option using continuous-

time mathematics. The BSOPM equation for the price, C, of a European call option

is given in equation (2.29)

퐶 = 푉[푁(푑)]− 푒 푋[푁 푑 − 휎√푇 ] (2.29)


67

푑 =√

푉 is the current value of the underlying asset; 푋 is the exercise price of the

option; 휎 is the annual standard deviation of returns on the underlying asset 푇 is the

time to expiration of the option in years, 푟 is the annual risk-free rate, 푁(푑) is the

cumulative standard normal probability density function evaluated at d, and ln (푥) is

the natural log function.

2.2. Modified Modigliani-Miller propositions

Modigliani & Miller (1963) recognized the benefits of personal tax and

introduced a model of capital structure incorporating this. Miller and Modigliani

provide a general specification the effect of interest deductibility on the value of a

firm by (a) using variables to represent the various parameters involved, and (b)

making two simplifying assumptions. The first assumption is that the firm’s debt

consists of a single issue of perpetual debt, which provides an annual cash coupon at

a rate of 푐 = 푟 where 푟 is the required return. The value of the debt is denoted as

D. the second assumption is that the corporate tax rate, 휏 , and the deductibility of

interest, are fixed into perpetuity.

Using the above notion, a firm’s annual tax shield can be expressed as the

product of the tax rate and the annual coupon interest, or

퐴푛푛푢푎푙 푡푎푥 푠ℎ푖푒푙푑 = 휏 푐퐷 (2.30)


It is assumed that both the debt and the tax shield carry into perpetuity, so we

can calculate the present value (PV) of the tax shield using the constant perpetuity

formula, with rD as the discount rate:

푃푉(푡푎푥 푠ℎ푖푒푙푑) = = = 휏 퐷 (2.31)

{source: (Ogden, et al., 2003)}

As a consequence of this tax effect, M&M original І must be modified.

68

푉∗ = 푉 + 푃푉 (푡푎푥 푠ℎ푖푒푙푑) = 푉 + 휏 퐷 (2.32)

{source: (Ogden, et al., 2003)}

Equation 2.32 illustrates the point that, when M&M Proposition І is modified

for corporate taxes, the value of firm is no longer constant across leverage, but

instead increase monotonically with leverage. Thus, it can be concluded from

equation 2.32 that, for management to maximize the market value of the firm, the

firm should be virtually 100 percent debt financed.

Taxes, Arbitrage, and a Firm’s Market Value under Alternative Capital

Structures

If investors can purchase a firm’s unlevered equity at a total price that is less

than the total value of debt and equity after a leverage-increasing recap, they would

realize an immediate riskless arbitrage profit.

Such arbitrage profit opportunities will be eliminated in a competitive

market, so the seller should reap the same total proceeds whether he sells the firm by

issuing equity shares or any combination of debt and equity; and these proceeds

should be equal to the maximum market value that can be realized across all

possible capital structures, regardless of the capital structure that the seller presents

to the market. The levered firm’s tax-adjusted WACC would be calculated as

follows:

• Traditional formula:

푟° = 푟 (1− 휏 ) ∗ + 푟°∗

∗ (2.33)


• Correct formula:

푟∗ = 푟 ∗ + 푟∗∗

∗ (2.34)


Where:

69

푟∗ = 푟 + 푟 (2.35)


Indeed many firms have no debt the big question for modified MM

hypothesis is why do firms fail to take greater advantage of the deductibility of

corporate interest to increase the value of their equity?

2.3. Is There an Optimal Capital Structure? (Traditional Trade-off theory)

The Traditional Trade-off theory provides one answer to the question that

why do firms fail to take greater advantage of the deductibility of corporate interest

to increase the value of their equity? According to this theory, as a firm increases

debt relative to equity in its capital structure, expected costs of future financial

distress and bankruptcy also raise, eventually enough to fully offset the benefit of

the tax shield, at the margin. At this point, firm value is maximized, and beyond this

point firm value actually falls.

However, the interest tax shield is an observable factor but the costs of

financial distress are not. Beattie, Goodacre, & Thomson (2006) asserted the

importance of interest tax shield on financing behavior of UK firms.

2.3.1. Costs of Financial Distress

According to Myers, (1984) costs which even with preventing formal

default, can decrease firm value. Such as judicial and executive costs of bankruptcy,

agency costs, moral jeopardy, controlling and contracting costs.

Myers, (1984) stated that the previous researches on costs of financial

distress props two qualitative statements about financing behavior.

A- Firms with higher risk must borrow less rather than firms with lower risk

with same conditions. The definition of risk is variance of the share price of the firm

in market. With increasing in risk of the firm, the probability of default on debt will

be increased. Such default is cause of financial distress; to be on the safer side, firms

must be able to increase debt before interest tax shield is offset by the expected costs

of financial distress.

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B- Firms with more tangible assets and powerful secondary market will

borrow less than firms with intangible assets or growth opportunities. Apart from the

probability of difficulty, the expected costs of future financial distress depend upon

value lost in difficulty. Intangible assets or growth opportunities will lose value

more likely in financial distress. (p. 581).

Myers, (1984) compares the Traditional Trade-off theory with a competing

famous story based on the Pecking Order theory:

Firms rely on internal finance.

They considered target dividend payout ratios relative to investment

opportunities although target dividend ratios are gradually adjusted rather

than changes in the extent of valorous investment opportunities.

Unexpected volatilities in investment opportunity and profitability moreover

adhesive dividend policies mean that cash flow generated internally may be

more or less than needs for valuable investment opportunities.

At the presence of need for external finance, first, firms issue debt as the

safest source of external financing, then probably hybrid securities like

convertible bonds and ultimately equity as a last asylum. There is no a target

debt ratio because there are two types of equity one is retained earnings

(internal) and another one is initial public offering (external). Debt ratio for

each firm indicates its cumulative needs for external source of finance.

De Miguel & Pindado (2001) found an inverse relationship between financial

distress costs and debt, due to the higher premium demanded by debt underwriters.

According to Beattie, et al.(2006) financial distress is important on financing

behavior of UK firms.

The Traditional Trade-off theory proposes that all firms have an optimal

leverage (debt ratio). This theory predicts moderate borrowing by tax-paying firms

(Myers, 2001).Myers (1984) conceptualized that optimal debt ratio of a firm is

generally determined by a trade-off between the benefits and costs of debt, if firm’s

investment plans and assets are held constant. Myers pointed out that the firm is

characterized by balancing the costs of financial distress and the value of interest tax

shields. He also supposed that the firm substitutes equity for debt, or debt for equity,

71

until arriving to maximum value of the firm. Thus the debt-equity trade-off is

illustrated in Figure 1 in the appendix A

The firm's optimal capital structure will require the trade-off between the tax

advantage of debt and different costs of leverage (Bradley, Jarrell, & Kim, 1984).

Bhaduri (2002) presented evidence from India as proxy for less developed countries

(LDCs) that the optimal capital structure choice apart from factors such as growth,

cash flow and size can be influenced by product and factors related to industry. The

results also corroborate the existence of recapitalization costs in obtaining an

optimal capital structure.

According to Booth, et al.(2001) profitable firms have less demand for

external financing. This result does not sit well with the Traditional Trade-off

theory, under which it would be expect that highly profitable firms would use more

debt to lower their tax bill. Fama & French (2002) confirmed predictions shared by

Traditional Trade-off theory, those are as follows

Firms with more profitability and fewer investments are expected to have

greater dividend payouts.

It is expected that the higher the firms’ investment, the smaller market

leverage, which is consistent with the Traditional Trade-off theory and a

complex version of the Pecking Order theory.

Fama & French (2002) found that more profitable firms are less levered that

is contradicting with the Traditional Trade-off theory

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Figure 2.1: The Traditional Trade-off theory of capital structure.

(Source: Myers, 1984, p.577)

According to Drobetz & Fix (2003) the more investment opportunities for

the firm is along with applying the less leverage, which props both the Traditional

Trade-off theory and a complex version of the Pecking Order theory. They also

found that more profitable firms use less leverage that is contradicting the

Traditional Trade-off theory.

Lemmon & Zender (2004) found that, on average, large, profitable, low

leverage firms use internally generated funds to finance their growth and allow their

leverage ratios to drop over an extended period that is not consistent with the

Traditional Trade-off theory. According to Huang & Song (2006) the Traditional

Trade-off theory is better in explaining the feature of capital structure for Chinese

listed companies. Beattie, et al.(2006) discovered that about half of UK firms seek to

maintain a target debt level that is consistent with the Traditional Trade-off theory.

Delcoure (2007) also discovered that tangibility has a positive regression coefficient

and statistically significant with leverage in Central and Eastern European (CEE)

countries. These results are consistent with the Traditional Trade-off and the

Pecking Order theory of capital structure. Frank & Goyal (2009) found empirical

73

evidence consistent with some versions of the Traditional Trade-off theory of capital

structure.

On the existence of optimal capital structure and reducing cost of capital

by optimal capital structure, Ezra Solomon as cited in (Schwartz & Aronson, 1967)

states that

One proof in favor of the Traditional Trade-off theory is that companies in

the different industry classification use debt at the presence of some optimum range

suitable to each classification. Despite significant difference between firms in debt

ratio exist within each classification; the mean of debt by wide industrial

classification tends to pursue a stable pattern over time. (p. 10).

2.3.2. Target Debt Level

Capital structure is a key issue for financial decision makers. Empirical

evidence as well as evidence from surveys indicates that firms look for a target

capital structure. The relationship between leverage ratio of firm and well-defined

firm characteristics generally has been interpreted in favor of one of these two

majors theories of capital structure namely; the Traditional Trade-off and the

Pecking Order theory. The concept of target capital structure plays an important role

in many models of corporate financing. However, empirical evidence on target

leverage has been mixed (Hovakimian, 2004).

It is important to note that this target is not discoverable but it may be

computed from firm’s variables such as debt-to-equity, firm’s size, growth options

and non-debt tax shields etc.(Fama & French, 2002). Marsh, (1982) discovered that

target debt ratios are depended on firm size, risk of bankruptcy, and asset

combination. He also provided evidence that companies choose financing instrument

as if they have target levels of debt in mind. Mayer & Sussman (2004) found

evidence consistence with the Traditional Trade-off theory that firms show a strong

tendency to revert back to their initial leverage.

Kayhan & Titman (2003) found that over long periods of time firms make

financing choices that tend to move them towards their target debt ratios. Titman &

Tsyplakov (2007) also discovered that firms move relatively slowly towards their

74

target debt ratios. The results of Antoniou, Guney, & Paudyal (2008) confirmed that

firms have target leverage ratios.

Hovakimian, Hovakimian, & Tehranian (2004) concluded that the

significance of stock returns in corporate finance literature is unrelated to

target(optimal) leverage and is probably because of Pecking Order–market timing

behavior. They also found that there is no relationship between profitability and

target leverage. To offset the excess leverage due to deadweight losses, firms with

no profitability proceed to issue equity. On the flip side, profitable firms do not seem

to be offsetting the accumulated leverage deficit by issuing debt. Generally they

support the hypothesis that firms have target capital structure.

Hovakimian, et al. (2004) ultimately suggested that the priority of internal

financing and the temptation to time the market by issue equity when the market

price of equity is relatively high admix with the tendency to keep the firm’s debt

ratio close to its target. Hovakimian (2004) suggested that the conflicting results

aroused partially vary across different types of corporate financing transactions

because the importance and the role played by target leverage. He also found that

firms do not initiate equity transactions to offset the accumulated deviation from the

target leverage ratio.

2.3.2.1. Target Adjustment Model

Because of random events or other changes, firms may temporarily deviate

from their target capital structure and then only gradually work back to the optimal

one. However, firms may not adjust fully towards target leverage because it might

be less expensive for them even if they come out with that their current debt ratios

are not optimum. Nevertheless, there are some empirical evidence that

macroeconomic factors are affecting on the process and speed of adjustment towards

optimal debt ratio.

De Miguel & Pindado (2001) have developed a target adjustment model to

explain firm characteristics that determine capital structure and how institutional

features affect capital structure. Drobetz & Fix (2003) Used a simple target

adjustment model, they reported evidence that firms adjust to long-term financial

75

targets. As shown by Shyam-Sunder and Myers (1999), this can well be consistent

with a Pecking Order of financing activities.

Leary & Roberts (2005) corroborated that financing behavior is consistent

with the presence of adjustment costs, they discovered that firms dynamically

rebalance their leverages to maintain an optimal range. Their evidence asserts that

the chronic effect of shocks on leverage observed in previous researches is more

probably because of adjustment costs than indifference toward capital structure.

2.3.2.2. Speed of Adjustment towards Target Debt-Ratio

Nivorozhkin (2005) adopted dynamic adjustment model and found that the

large adjustments of leverage tend to be less costly relative to smaller ones,

indicating the presence of fixed costs in changing the capital structure of a firm.

Drobetz & Wanzenried (2006) documented that faster growing firms and those that

are further away from their target capital structure adjust more readily. Their results

also reveal interesting interrelations between the speed of adjustment and famous

variables of business cycle. Particularly, it is observed that the adjustment speed is

more when the spread between current and target debt ratio is more and when

economic perspectives are good.

Taggart, (1977) concluded that movements in the market values of long-term

debt and equity are important determinants of corporate security issues. He also

provides some evidence that timing strategies may speed up or postpone firm’s

adjustment to their targets. According to Jalilvand & Harris, (1984) companies’ size,

interest rate, and levels of market value of firms’ equity affect adjustment speeds to

target debt ratio.

Antoniou, Guney, & Paudyal (2002) used panel data to investigate the

determinants of leverage ratio of firms operating in France, Germany and England .

The estimates reveal that the firms in all three countries adjust their debt ratios to

attain their target capital structure but at different speed, French firms were the

swiftest and the Japanese are the slowest.

According to Nivorozhkin (2005) the speed of leverage adjustment tend to

decrease with an increase in firm size, indicating potential supply-side imperfections

76

from the exposure control of providers of debt financing. Titman & Tsyplakov

(2007) discovered that firms that are subject to financial distress costs as well as

those without conflicts of interest between debt-holders and equity-holders should

adjust more quickly towards their target debt ratios. Despite with controlling for the

traditional determinants of capital structure and firm fixed effects, Huang & Ritter

(2009) found that firms moderately move to target leverage. Half-life of adjustment

for book leverage is 3.7 years. Booth, et al (2001) analyzed ten developing nations

and found that firms having leverage less than their optimal leverage and adjusted

faster towards it, were specified by less growth opportunities, more intangible assets,

less non debt tax shields, more financing slack, less share prices and more deviation

from their target leverage. Conversely, firms having more leverage than their target

leverage and adjusted faster were specified by more growth opportunities, less

intangible assets, more non debt tax shields, less financing slack, more share prices

and more deviations from their target leverage.

Fischer, Heinkel, & Zechner, (1989) developed a model of dynamic capital

structure choice at the presence of adjustment costs. The theory provides the

optimum dynamic adjustment policy that is a function of firm-specific

characteristics. They found that even slight recapitalization costs result in broad

deviations in a firm's leverage over time. In a dynamic setting, the results of

empirical tests relating firms' leverage ranges to firm-specific characteristics that

forcefully prop the theoretical model of relevant capital structure choice.

2.4. Agency Theories of Capital Structure

Long & Malitz (1985) stated that a firm must seek an outside source of

funds, its choice between debt and equity will depend in part on the magnitude of

potential agency costs of debt.

According to Auerbach, (1985) The effects of firm growth rates on the level

of borrowing is inconsistent with the predictions of "agency" models of leverage.

Hovakimian, et al. (2001) found the negative relation between returns on equity in

the past and leverage increasing choices is also in accordance with agency models

where managers are motivated to increase leverage when market value of equity are

low. These results are also confirming this notion that managers are unwilling to

issue equity when their market value of equity is underpriced. According to Titman

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& Tsyplakov (2007) conflict of interest between equity-holders and debt-holders is

less pronounced for firms that are more subject to financial distress costs, since such

firms have a greater incentive to issue equity and pay down debt when they are

doing poorly.

According to Beattie, et al. (2006) agency costs are important determinant of

financing behavior of UK firms. According to Booth, et al. (2001) demand for

external financing in profitable firms is less. This implication supports the notion

that there are agency costs of managerial discretion.

2.4.1. Information Asymmetry

According to Booth, et al. (2001) more profitable firms had lower debt ratio

in 10 developing countries. This finding supports the existence of significant

information asymmetries within developing countries. This result suggests that

external financing is costly and therefore avoided by firms. Beattie, et al. (2006)

asserted that information asymmetry is an important determinant of financing

behavior of UK firms.

2.4.2. Ownership Structure

De Miguel & Pindado (2001) took into account level of ownership

concentration because a high level mitigates the free cash flow problem, and

therefore firms with highly concentrated ownership need to issue less debt.

According to Huang & Song (2006) ownership structure affects leverage.

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2.5. The Pecking Order Theory

Shyam-Sunder & Myers, (1999) tested the Pecking Order for sample of

mature corporations and found that it is an excellent first-order descriptor of

corporate financing behavior.

The Pecking Order theory predicts lower growth firms with high free cash

flow will have relatively low debt ratios (Barclay, et al., 1995). According to the

Pecking Order theory, when internal source of finance is not sufficient to fund

capital expenditures, the firm will issue debt rather than issuing equity. Hence, the

amount of debt in the capital structure of the firm shows the firm’s cumulative

requirement for external funds (Myers, 2001). Kayhan & Titman (2003) found that

financial deficits (the amount of capital raised externally) generally have a positive

effect on changes in debt ratios; however, their results indicate that this effect does

not hold for firms with high market to book ratios.

Booth, et al. (2001) discovered that more profitable have the lower debt

ratio, regardless of definition of debt ratio. This finding is in accordance with the

Pecking Order theory.

Fama & French (2002) confirmed predictions shared by the Pecking Order

theory as follows:

Firms with fewer investments and more profitability pay higher dividend.

Firms with more profitability have less leverage.

Firms which have more investments pay lower long-term dividend and

dividends do not vary to accommodate short-term changes in investment and

earnings is mostly absorbed by debt.

Frank & Goyal (2003) tested the Pecking Order theory of capital structure on

a wide cross-section of publicly traded US companies for 1971 to 1998. Conflicting

with the Pecking Order theory, net issues of equity follow the financing slack more

nearly than do net debt issues. While large firms show some aspects of the Pecking

Order behavior, the proof is not strong to the inclusion of traditional leverage

variables or to the analysis of evidence from the 1990s. They found that financing

slack is less significant in describing net issues of debt over time for firms of all

sizes.

79

Drobetz & Fix (2003) tested several predictions on leverage using data from

a representative sample of Swiss firms. They concluded that the race between the

Traditional Trade-off theory and the Pecking Order theory is undecided; in fact, on

many issues there is no conflict. The shared predictions are confirmed in their tests.

Particularly, firms which have more investment opportunities have less leverage in

their capital structure, which confirms both the Traditional Trade-off theory and a

complex version of the Pecking Order theory. They also found that more profitable

firms use less leverage that is confirming the Traditional Trade-off theory. Drobetz

& Fix (2003) Used a simple Target Adjustment Model, they reported evidence that

firms adjust to long-term financial targets. As shown by Shyam-Sunder and Myers

(1999), this can well be consistent with a pecking order of financing activities.

Mayer & Sussman (2004) found evidence consistent with the Pecking Order theory

that projects are mainly funded with debt, most important in profitable and large

firms. However, they rejected the hypothesis that internal finance plays a major role

in funding investment.

Lemmon & Zender (2004) found that the Pecking Order theory is a good

descriptor of the observed financing behavior of a wide cross-section of firms. Their

finding that, on average, large, profitable, low leverage firms use internally

generated funds to finance their growth and allow their leverage ratios to drop over

an extended period is consistent with the Pecking Order theory. Tong & Green

(2005) provided the results that support tentatively the Pecking Order hypothesis.

Fama & French (2005) rejected the Pecking Order’s central predictions about how

often and under what circumstances firms issue and repurchase equity.

According to Beattie, et al.(2006) 60% of UK firms assert to follow a

financing hierarchy, in accordance with the Pecking Order theory. Delcoure (2007)

also discovered that tangibility has a positive regression coefficient and statistically

significant with leverage in CEE countries. These results are consistent with the

Traditional Trade-off and the Pecking Order theory of capital structure. Delcoure

(2007) found a negative relationship between profitability and leverage that at first

glance supports the Pecking Order theory of capital structure. However, upon taking

another look, the order of external financing choices appears to be different for CEE

companies. The bond market in the majority of CEE countries is still developing.

80

Banks provide short-term liquidity loans rather than long-term financing to

enterprises, so companies have to rely on equity to finance their capital investments.

In addition, shareholders' protection laws are weak. Thus, managers prefer equity to

debt financing because it is not binding, and share capital may appear to be a “free”

source of capital. Managers may perceive retained earnings to be the quickest and

easiest source of financing followed by new equity issuance, bank borrowing, and

possible new debt issuance. Thus, these results collaborates Chen (2004) explanation

of the new Pecking Order hypothesis in corporate capital structure among

developing countries. It appears that countries in transition follow a different

“Pecking Order” in their capital structure decisions— retained earnings, equity, and

debt. Leary & Roberts (2010) found that incentive conflicts, not information

asymmetry, appear to generate pecking order behavior.

2.6. The Traditional Trade-off theory V/S the Pecking Order theory

Drobetz & Fix (2003) tested several predictions on leverage using data from

a representative sample of Swiss firms. They concluded that the race between the

Traditional Trade-off theory and the Pecking Order theory is undecided; in fact, on

many issues there is no conflict. The shared predictions are confirmed in their tests.

Most important, firms which have more investment opportunities have less leverage

in their capital structure, which confirms both the Traditional Trade-off theory and a

complex version of the Pecking Order theory.

Beattie, Goodacre, & Thomson (2006) found that UK firms are not

homogeneous in their policies towards leverage decisions. Almost half of the firms

attempt to keep a target leverage, in accordance with the Traditional Trade-off

theory, but 60% claim to track a hierarchy of financing, confirming the Pecking

Order theory. Delcoure (2007) also discovered that tangibility has a positive

regression coefficient and statistically significant with leverage in CEE countries.

These results are consistent with the Traditional Trade-off and the Pecking Order

theory of capital structure.

2.7. The Market Timing Theory

It is obvious that firms issue equity when their equity market values are high,

rather than book and historical market prices, and repurchase equity when their

81

market prices of equity are low that Baker & Wurgler (2002) confirmed this.

According to Baker & Wurgler (2002) current capital structure is significantly

related to historical market values. Their results propose the theory that capital

structure is the cumulative outcome of past efforts to time the equity market.

Kayhan & Titman (2003) found evidence of a timing effect; however, in

contrast to findings in literatures, this effect disappears quickly. Hovakimian (2004)

asserts that the timing of equity transactions appears to be driven by market

conditions. He pointed out that equity is issued following periods of improvement in

both market and operating performance. He also discovered that Equity is

repurchased following periods when, despite strong operating performance, stock

returns are relatively low. Marsh, (1982), proved that firms are strongly affected by

market conditions and the historical prices of the secutity in choosing between debt

and equity. He also provides evidence that companies choose financing instrument

as if they have target levels of debt in mind.

Dittmar & Thakor (2007) argued that firms maximize the probability of

agreement with investors, otherwise they issue debt. According to them, firms issue

equity when their market values of shares are high. They also predicted that

managers issue equity to fund projects when they believe that investor’s

imaginations about project payoffs are probably consistent with theirs. These results

are in accordance with signaling theory, according to the signaling theory, high-

quality (or undervalued) companies will have higher leverage and make higher

dividend payments than low-quality (overvalued) firms (Barclay, et al., 1995). They

also found strong empirical support for the theory and predicated its incremental

interpretive strength over other security-issuance theories like market timing and

time-varying adverse selection.

According to Frank & Goyal (2008) dependence of financing decisions on

market conditions (‘market timing’) is well-defined in a trade-off model. They

asserted empirically that reduced use of external finance is due to poor market

conditions. This effect is robust especially for firms with low profitability and small

size.

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2.8. Determinants of Leverage

Determinants of leverage are divided into two groups: firm characteristic

variables and policy and decision variables. Managers with choosing better policies

can optimize their firms’ capital structure.

2.8.1. Firm Size

Larger companies might be expected to have higher leverage ratio because

they have lower direct bankruptcy costs (Barclay, et al., 1995). Titman & Wessels,

(1988) discovered that Short-term debt ratios has negative relationship with firm

size, probably indicating that firms with small sizes interface relatively high

transaction costs when issuing long-term financial securities. Barclay, et al., (1995)

found somewhat mixed. According to them firm size coefficient in the pooled

regression was negative and statistically significant (implying that bigger firms have

less leverage), but the coefficient in the fixed-effects regression was positive and

significant (implying the opposite).

Bhaduri (2002) presented evidence, suggests that the optimal capital

structure choice can be affected by firm size. Antoniou, Guney, & Paudyal (2002)

used panel data to investigate the determinants of leverage ratio of firms operating in

France, Germany and England. The results suggest that the leverage ratio is

positively affected by the size of the firm. Lemmon & Zender (2004) found that, on

average, large, profitable, low leverage firms use internally generated funds to

finance their growth and allow their leverage ratios to drop over an extended period

is consistent with the Pecking Order theory.

According to Nivorozhkin (2005) the speed of leverage adjustment tended to

decrease with an increase in firm size, indicating potential supply-side imperfections

from the exposure control of providers of debt financing. Huang & Song (2006);

Antoniou, Guney, & Paudyal (2008) discovered that the leverage ratio is positively

affected by the size of the firm. Frank & Goyal (2008) also found that large firms

use debt more actively while small firms use equity more actively.

According to Frank & Goyal (2009) log of assets has a positive relationship

with market leverage of firm but this result is not reliable for book leverage.

83

Bayrakdaroglu, Ege, & Yazici (2013) discovered that Turkish bigger companies

tend to have higher debt ratios when compared to the small companies.

According to Delcoure (2007) in the sample of companies in CEE countries,

the relationship between the firm size total and short-term debt is positive and

statistically significant, except for the estimation of long-term leverage for the Czech

Republic, Poland, and Slovakia. The estimated size coefficient in the long-term

leverage model for companies in these countries is negative. These negative

relations may be attributed to existence of information asymmetries suggested by

Myers and Majulif (1984) and an underdeveloped state of the bond market in these

transitional economies. Also, laws dealing with financial distress are still

developing, leaving debt holders unprotected in the event of default and forcing

companies to acquire funds through short-term loans. The estimated positive

relationship between firm size and long-term debt for Russian companies is not

surprising. Despite some progress in the transition from banking to a market

economy, high Russian government ownership in enterprises along with government

directing credit programs to preferred sectors with price control in these sectors may

have a significant impact on corporate financing patterns.

2.8.2. Profitability

Titman & Wessels, (1988) found negative relationship between past

profitability and current leverage. Booth, et al.(2001); Fama & French (2002);

Drobetz & Fix (2003); Nivorozhkin (2005); Tong & Green (2005); Huang & Song

(2006); Antoniou, et al. (2008) discovered that the more profitable firm, the lower

the debt ratio that broadly supports the Pecking Order hypothesis over the

Traditional Trade-off hypothesis. Bayrakdaroglu, Ege, & Yazici (2013) also

suggested that profitable Turkish companies prefer less debt.


determinants of leverage ratio of firms operating in France, Germany and England.

The results suggest that profitability has different degrees and directions of influence

on leverage across the sample countries.

Hovakimian, et al.(2004) found that target leverage is not influenced by

profitability. Firms with no profitability issue equity to offset the excess leverage

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due to deadweight losses. On the flip side, profitable firms do not seem to be

offsetting the accumulated leverage deficit by issuing debt. Lemmon & Zender

(2004) found that, on average, large, profitable, low leverage firms use internally

generated funds to finance their growth and allow their leverage ratios to drop over

an extended period that is consistent with the Pecking Order theory.

Delcoure (2007) found a negative relationship between profitability and

leverage that at first glance supports the Pecking Order theory of capital structure.

However, upon taking another look, the order of external financing choices appears

to be different for CEE companies. The bond market in the majority of CEE

countries is still developing. Banks provide short-term liquidity loans rather than

long-term financing to enterprises, so companies have to rely on equity to finance

their capital investments. In addition, shareholders' protection laws are weak. Thus,

managers prefer equity to debt financing because it is not binding, and share capital

may appear to be a “free” source of capital. Managers may perceive retained

earnings to be the quickest and easiest source of financing followed by new equity

issuance, bank borrowing, and possible new debt issuance. Thus, these results

collaborates Chen's (2004) explanation of the new Pecking Order hypothesis in

corporate capital structure among developing countries. It appears that countries in

transition follow a different “Pecking Order” in their capital structure decisions

internal source of finance, equity, and debt.

According to Frank & Goyal (2008) both book equity and the market value

of equity is increased for firms with more profit. They discovered that firms with

high profitability generally borrow and repurchase their stocks, while firms with low

profitability normally decrease their debt and issue equity. Frank and Goyal also

found that poor market conditions result in reduced use of external finance. They

investigated empirically and discovered that the effect is especially strong on small

and low profit firms. However, Frank & Goyal (2009) discovered that profits has a

negative relationship with market leverage of the firm.

2.8.3. Non-Debt Tax Shields

De Miguel & Pindado (2001) discovered an inverse relationship between

non-debt tax shields and debt, which is more significant for Spanish firms because

they have more non-debt tax shields than US firms. According to Huang & Song

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(2006) leverage increases with non-debt tax shields. Delcoure (2007) also found

that there is a strong direct relation between the total, long-term, and short-term

leverage and non-debt tax shield in CEE countries. This result contradicts the

Traditional Trade-off theory that focuses on the substitution between non-debt and

debt tax shields. According to Bayrakdaroglu, et al. (2013) Turkish companies with

high non-debt tax shield may be asserted as willing to have high debt ratios.

However, Titman & Wessels, (1988) found no support for an influence on debt

ratios arising from non-debt tax shields. Sometimes researchers use age of the

company as a proxy for non-debt tax shield. Nivorozhkin (2005) found a positive

effect of the firm’s age on the leverage targets that provides the support for the

hypothesis of the positive effect of reputation in firms’ choice of financing.

Investment tax credit also serves as a proxy for non-debt tax shield. According to the

tax hypothesis there is a negative relationship between investment-tax credit and

leverage. Barclay, et al., (1995) provided little support for negative relationship

between investment-tax credit and leverage ratio.

2.8.4. Investment

Long & Malitz, (1985) concluded that the type of firms’ investments is a

major factor which influences its leverage decisions. De Miguel & Pindado (2001)

discovered a positive relationship between investment and debt which confirms the

concurrency of both decisions. Fama & French (2002) found results confirming

predictions shared by the Traditional Trade-off and the Pecking Order theories of

capital structure, according to them firms with fewer investments and more

profitability have higher dividend payouts. They also discovered that firms which

have more investments have less market leverage, which is confirming the

Traditional Trade-off theory and a complex Pecking Order theory. Fama & French

observed that firms which have more investments pay lower long-term dividend and

dividends do not vary to accommodate short-term changes in investment. According

to prediction of the Pecking Order theory, short-term changes in investments and

earnings are mostly absorbed by debt.

Kayhan & Titman (2003) found that investment expenditures have transitory

effects on corporate debt ratio. Drobetz & Fix (2003) found that firms which have

more investment opportunities issue less debt. This supports both the Traditional

Trade-off theory and a complex version of the Pecking Order theory.

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2.8.5. Collateral Value (Tangibility)

Titman & Wessels, (1988) did not find confirmation for effect of tangible

assets on leverage. Booth, et al. (2001) concluded that though smaller total debt

ratio, firms with more tangible assets have higher long-term debt ratio. According to

Drobetz & Fix (2003); Huang & Song (2006); Frank & Goyal (2009); Antoniou, et

al. (2008) leverage increases with fixed assets and it is closely related to tangibility

of assets. Delcoure (2007) also discovered that tangibility has a positive regression

coefficient and statistically significant with leverage in CEE countries.

Bayrakdaroglu, et al. (2013) discovered that Turkish companies with large

amounts of fixed assets tend to display lower debt ratios. Antoniou, et al. (2002)

used panel data to investigate the determinants of leverage ratio of firms operating in

France, Germany and England. The results suggest that fixed-assets ratio has

different degrees and directions of influence on leverage across the sample

countries.

2.8.6. Repurchases of Stock and Issuing Equity

Hovakimian, Opler, & Titman (2001) investigated the size of the issue and

repurchase transactions separately and proposed that the swing between the actual

and the target debt ratios has a more significant role in the repurchase decision than

in the issuance decision. They proposed that capital structure conditions play a

larger role in the repurchase decision while market conditions play a more important

role in the issuance choice. Their results also suggest that over-levered firms may

choose to cut back their investment expenditures when their stock prices are low.

According to Hovakimian (2004) firms that issue or repurchase equity

generally have low debt ratios. He also found that firms do not initiate equity

transactions to offset the accumulated deviation from the target leverage ratio.

Hovakimian (2004) asserts that equity issuers tend to be under levered prior to the

issue and become even more under levered as a result of the issue. He discovered

that changes in leverage induced by equity issues are relatively transitory and offset

by a post issue upward drift in leverage. As observed by Hovakimian (2004) equity

repurchases, on the other hand, follow periods of increasing leverage deficit but fail

to induce a significant change in leverage.

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Fama & French (2005) found results Contradicting predictions of the

Pecking Order theory, they discovered that equity issues are commonplace. Between

years 1973 and 1982, 54% of their sample companies make net equity issues every

year, increasing to 62% between 1983 and 1992 and 72% between 1993 and 2002.

The fractions of firms making gross equity issues are much higher, 67%, 74%, and

86%. Given that they are so dominant, it is not surprising that equity issues are

commonly done by firms that are not under severity. Firms issue equity more rather

than repurchase it. Approximately 20% of companies retire equity for every year,

and the fractions for companies which repurchase stock are much greater. Moreover,

many of the firms making net repurchases have financing deficits that, in a Pecking

Order world, should make debt capacity valuable. In short, their results reject the

Pecking Order’s central predictions about how often and under what circumstances

firms issue and repurchase equity. between1983 &1992 and 1993 & 2002, the net

equity issues of net issuers among small firms are on average larger than their net

new borrowing. The net equity issues of big firms that are net issuers are about one-

third the size of their net debt issues during 1982-1992, and they are on the order of

net debt issues during 1993-2002. Fama and French asserted that At least since last

ten years of the sample period till now, mergers play a significant role in

demonstrating the significance of equity issues and issues to employees are possibly

main reason in describing both the magnitude and frequency of issues throughout

the sample period.

Müller & Zimmermann (2009) found a larger influence of the equity ratio for

young firms. Equity may be more important for young firms which have to rely on

the original equity investment of their owners since they have not yet accumulated

retained earnings and can rely less on bank financing.

2.8.7. Tax Rate

MacKIE-MASON (1990) confirmed that desirability of debt finance at the

margin varies positively with the effective marginal tax rate. His results were also

consistent with the broader hypothesis that changes in the marginal rate for any firm

should affect financing choices, regardless of the likelihood of tax exhaustion.

According to Delcoure (2007) corporate tax liability positively and significantly

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affects on corporate financing decisions. The typical firm could double tax benefits

by issuing debt until the marginal tax benefit begins to decline(Graham, 2000).

As Barclay, et al., (1995) mentioned in their paper, tax hypothesis has been

defined as follows:

“Firms with same conditions and low growth that interface low financial

distress costs and great free cash flow benefits from heavy debt financing are also

probably to have greater use for interest tax shields than firms with high growth”.

According to Barclay, et al. (1995) The tax hypothesis predicts that

companies with low effective marginal tax rates and high non-debt tax shields (non-

interest tax shield) should have less debt in their capital structure. They also asserts

that the tax hypothesis anticipates a negative coefficient on both the tax-loss carried

forward and investment-tax credit variables in the leverage regressions (Barclay, et

al., 1995).

2.8.8. Tax-Loss Carried Forward

Presumably firms with tax-loss carried forward have the lowest marginal tax

rates, on the other hand, according to tax hypothesis firms with low effective

marginal tax shields should have less debt in their capital structure, hence companies

with tax-loss carried forward have less debt (Barclay, et al., 1995).

Spite the tax hypothesis prediction, Barclay, et al.,(1995) found positive and

significantly significant relationship between tax-loss carried forward and leverage

ratio. However, this result is not consistence with the tax hypothesis theory. In the

opposite side Auerbach, (1985) discovered that the tax loss carried forward has the

negative effect on firm’s borrowing.

2.8.9. Dividend Payout

Fama & French (2002) confirmed predictions shared by the Traditional

Trade-off theory and the Pecking Order theory, firms with more profitability and

fewer investments are expected to have greater dividend payouts. They also

observed that Firms which have more investments pay lower long-term dividend and

dividends do not vary to accommodate short-term changes in investment. According

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to prediction of the Pecking Order theory, short-term changes in investments and

earnings are mostly absorbed by debt.

Tong & Green (2005) found a significant positive correlation between

current leverage and past dividends. This result broadly supports the Pecking Order

hypothesis over the Traditional Trade-off theory. Frank & Goyal (2009) concluded

that firms which pay dividends tend to have lower market leverage.

Dividend Yield

According to Barclay, et al., (1995) changes in leverage ratio and dividend

yield are same trough the time. They also found that companies with high market-to-

book equity ratios had significantly lower leverage and lower dividend yields than

companies with low market-to-book equity ratios.

2.8.10. Return on Equity (ROE)

Hovakimian, et al.(2001) discovered a negative relationship between past

stock returns and leverage increasing choices, but Hovakimian, Hovakimian, &

Tehranian (2004) asserted that while high stock returns are associated with higher

probability of equity issuance, the likelihood of borrowing is not affected by stock

returns. They concluded that the importance of stock returns in studies of corporate

financing choices is unrelated to target leverage and is likely to be due to Pecking

Order–market timing behavior.

2.8.11. Market-to-Book Equity Ratio

Market-to-book equity ratio is proxy for growth opportunities or investment

opportunities. According to Barclay, et al., (1995) because stock prices should

reflect intangible assets such as growth opportunities but corporate balance sheets do

not, it is reasoned that the larger a company’s growth options relative to its assets in

place the higher on average will be its market value in relation to its book value.

They accordingly used a company’s market-to-book equity ratio as their proxy for

its investment opportunity set.

Barclay, et al., (1995) provided strong support for above argument that

companies with high market-to-book equity ratios had significantly lower leverage

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and lower dividend yields than companies with low market-to-book ratios. They also

discovered that drugs and medical industries have the highest market-to-book ratio

and lowest leverage ratios and dividend yield. Conversely railroad equipment and

lumber industries have the lowest market-to-book equity ratios and dividend yield

and the highest leverage ratios.

The above evidence on leverage ratios, it should be pointed out, is also

consistent with the tax hypothesis in the following sense: The same low-growth

companies that face low financial distress costs and high free cash flow benefits

from heavy debt financing are also likely to have greater use for interest tax shields

than high–growth companies. This evidence is fundamentally inconsistent, however,

with the predictions of the Pecking Order theory which, again, suggests that low-

growth firms with high free cash flow will have relatively low debt ratios.

Hovakimian, et al.(2001) suggested that firm’s financing decision is heavily

depended upon the market value of equity. Firms with great stock price increases are

more probably to issue equity and retire debt than firms with stock price decreases.

This finding is confirming the notion that increases of share price are usually along

with better growth opportunities, which would lower optimal leverage of a firm.

Evidence presented by Bhaduri (2002) suggests that the optimal capital

structure can be influenced by growth. Antoniou, et al. (2002) used panel data to

investigate the determinants of leverage ratio of firms operating in France, Germany

and England. Their findings suggest that the debt ratio has a negative relationship

with market-to-book equity ratio. Kayhan & Titman (2003) found that financial

deficits (the amount of capital raised externally) does not have effect on changes in

debt ratios for firms with high market-to-book equity ratios. Hovakimian, et al.

(2004) found result consistent with the hypothesis that high market-to-book equity

ratio firms have good growth opportunities and, therefore, have low target debt ratio.

According to Chen & Zhao (2006) firms with higher market-to-book equity

ratios face lower debt financing costs and borrow more. Antoniou, et al. (2008)

found that the leverage declines with an increase in growth opportunities. According

to Frank & Goyal (2009) market-to-book equity ratio has a negative relationship

with market leverage of firm but this result is not reliable for book leverage. despite

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the expectations, Bayrakdaroglu, et al. (2013) discovered that the Turkish companies

with high growth opportunities may have high debt ratios.

2.8.12. Interest Rate


determinants of leverage ratio of firms operating in France, Germany and England.

The results suggest that the leverage ratio is conversely related to interest rate.

2.8.13. Share Price Performance

Antoniou, et al. (2002) investigated the determinants of leverage ratio of

French, German and British firms using panel data. The results suggest that the

leverage ratio is inversely related to share price performance in small countries.

Kayhan & Titman (2003) indicated evidence that debt ratio changes,

resulting from stock price changes, do tend to partially persist. They also found that

stock price histories have transitory effects on corporate debt ratio. Antoniou, et al.

(2008) discovered that the leverage declines with an increase in share price

performance.

2.8.14. Volatility of a Firm’s Earnings (Risk)

Drobetz & Fix (2003) found that leverage is closely related to volatility of a

firm’s earnings. According to Huang & Song (2006) leverage in Chinese firms

increases with volatility. However, Titman & Wessels, (1988) found no support for

an effect on debt ratios arising from volatility. On the other hand, Bradley, et

al.(1984) found that firm leverage ratios are related inversely to earnings volatility.

Thus it is visible that results about effect of volatility of firm’s earnings on leverage

are mixed.

Delcoure (2007) did not conclude the estimated relations between earnings

volatility and leverage. The empirical evidence for Czech and Russian enterprises

collaborates the Traditional Trade-off theory. The Russian-listed companies' total

and long-term leverage and Czech firms' long- and short-term leverage are inversely

related to earnings volatility. With positive bankruptcy costs, larger earnings

volatility entails a lower debt / asset ratio. Thus, the negative coefficient on earnings

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volatility suggests the existence of bankruptcy or financial distress costs is higher in

Russia than in other CEE countries. Delcoure (2007) suggested that The observed

differences in the estimated earnings volatility coefficient may be explained by the

fact that, in Russia, the bankruptcy law has been strictly enforced since March 1998.

2.8.15. Equity Market Premium

Antoniou, et al. (2002) investigated the determinants of leverage ratio of

French, German and British firms using panel data. The results suggest that equity

market premium has different degree and direction of influence on leverage across

the sample countries.

2.8.16. Cash Flow

De Miguel & Pindado (2001) discovered the inverse relationship between

cash flow and debt. This result indicates that cash flow is preferred to use of debt as

a source of financing. This preference originates in an attempt to avoid under-

investment when firms face major problems of asymmetric information. However,

in absence of asymmetric information, firms are more concerned with avoiding the

problem of over-investment, where there is a direct relationship between cash flow

and debt, since the latter is used to reduce the managers’ incentive to carry out

investment projects with negative net present value. He also found firms look for a

trade-off between under-investment and over-investment. These results provide

some additional evidence in favor of the Pecking Order and free cash flow theories.

Evidence presented by Bhaduri (2002) suggests that the optimal capital structure

choice can be influenced by cash flow. Kayhan & Titman (2003) found that cash

flows have transitory effects on corporate debt ratio.

2.8.17. Research and Development

Müller & Zimmermann (2009) investigated the significance of equity

finance for the R&D activity of small and medium enterprises. They found that a

higher equity ratio leads to a higher R&D intensity. According to Meuleman & De

Maeseneire (2012) obtaining a R&D subsidy provides a positive signal about SME

quality and results in better access to long-term debt.

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According to Long & Malitz (1985) firms which invest highly on intangible

assets, like R&D; and advertising, have a narrower debt capacity than those

investing on tangible assets. They reasoned that narrower debt capacity is because of

agency costs. Their finding implies on significance of moral hazard problem and

investing and financing decisions are not separable.

2.9. Country and Economic Factors (Institutional Characteristics)

Rajan & Zingales, (1995) discovered that factors recognized by previous

researches as correlated in the cross-section with firm’s leverage in the United

States, are similarly correlated in other countries as well. They also found the United

Kingdom and Germany were relatively less levered rather than previous studies.

De Miguel & Pindado (2001) discovered the greater sensitivity of debt to

fluctuations in cash flow when the public debt ratio is high, indicates that in

countries like Spain, where the bond market is inadequately developed, the

advantage provided by private debt (fewer agency costs of debt) is not as great as

that provided by access to the bond market (fewer financing constraints).

Booth, et al. (2001) investigated on capital structure of firms in 10

developing countries and presented the result that factors affecting on capital

structure choices are same in developed countries, denoting that differences between

capital structure choices of developing and developed countries are because of

particular country and macroeconomic factors. Their findings propose that though

some of the intuitions from modern finance theory are generalized across countries,

lots of them remains to be done to understand the effect of various institutional

characteristics on capital structure choices. They also found that the variables that

are relevant for explaining capital structures in the United States and European

countries are also relevant in developing countries, despite the profound differences

in institutional factors across these developing countries. Their findings also support

existence of significant information asymmetries within developing countries. Their

findings also suggest that external financing is costly for developing countries and

therefore avoided by firms.

Bhaduri (2002) presented evidence from India as proxy for less developed

countries (LDCs) suggests that the optimal capital structure choice can be influenced

94

by factors such as growth, cash flow, size, and product and industry characteristics.

The results are also consistent with the notion that firms in attaining their optimal

leverage incur restructuring costs.

Antoniou, et al. (2002) used panel data to investigate the determinants of

leverage ratio of firms operating in France, Germany and England. These countries

are characterized by different financial systems and traditions that have implications

on how firms decide their capital structure. They modeled the leverage ratio as a

function of firm specific characteristics and market related variables. The results

suggest that the leverage ratio is positively influenced by firm size but inversely

affected by market-to-book equity ratio, term-structure of interest rates and share

price performance in all sample countries. Tangibility, profitability, premium on

stock market and effective tax rates showed various degrees and directions of

affection on debt ratios among the sample countries. The assessments disclose that

the companies in all three countries adjust their leverage to achieve their target

leverage but at different speed, speed of adjustment for French firms was the fastest.

Therefore, the capital structure choice of a company is not merely the output of its

own specifications, but also the result of environment and customs in which it

operates.

According to Drobetz & Fix (2003) debt ratio of firms operating in

switzeland is relatively low. This is an exciting observation, given that typically

continental European companies tend to have high leverage. They concluded that

leverage in Switzerland is similar to what has been previously reported by Rajan and

Zingales (1995) for Germany, but somewhat lower than in Anglo-American

countries. One important reason is that Swiss firms hold large cash positions. They

also observe that leverage has been slightly decreasing during the last decade.

Chen (2004) expanded a primary study to discover the determinants of

capital structure of Chinese-listed firms using firm-level panel data. The results

indicate the transitional nature of the Chinese corporate environment. They

suggested that some of the intuitions from modern finance theory of capital structure

are generalized to China in that determined firm-specific factors that are pertaining

to describing capital structure in developed economies are also related to China.

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Nevertheless, neither the Traditional Trade-off nor the Pecking Order theory

derived from the western countries provides satisfactory description for the capital

structure choices of firms operating in China. The capital structure choice of

Chinese companies show a ‘‘new Pecking Order’’—retained earnings, equity issue,

and long-term borrowing. This is because the essential macroeconomic factors of

western countries are not at work in China. Banking sector as same as firm

characteristics in China is factor affecting firm’s capital structure choices.

According to Nivorozhkin (2005), leverage of companies in countries with

transition economics was lower than EU countries but average levels of

indebtedness of companies in advanced transition economies of Estonia, Poland and

Czech Republic was close to those observed in several EU countries. They also

observed a significant convergence in the average level of firm’s leverage across EU

accession countries. The average leverage of companies in the higher leverage

countries declined, while the average leverage of companies in the lower leverage

countries appreciated. Nivorozhkin asserted that the determinants of target leverage

in the cross-section of companies also differ amongst countries. Only two variables

had a same effect on target capital structure for all countries namely; the age and

profitability of firm.

Tong & Green (2005) tested the Pecking Order and Traditional Trade-off

hypotheses of corporate financing choices using a cross-section of the largest

Chinese listed companies. They show that a traditional model of corporate capital

structure can explain the financing behavior of Chinese companies. Their results

support the Pecking Order theory of capital structure.

Huang & Song (2006) found that leverage in companies operating in China

is Different from other countries, they discovered that the higher the volatility the

higher the leverage and firms borrow long-term much lower. The Traditional Trade-

off model rather than the Pecking Order hypothesis seems better in explaining the

features of capital structure for Chinese listed companies.

According to Beattie, et al. (2006) cross-country institutional differences

have a significant impact on financial decisions. The results of Delcoure (2007)

suggest that there is a difference in capital structure choices for companies in

96

Central and Eastern Europe (CEE) countries and developed countries. Firms in CEE

countries tend to rely more heavily on short-term than long-term debt in their capital

structure than is typical in companies in developed markets. They also found that

some of the western capital structure theories are transparent. The Pecking Order,

Traditional Trade-off and Agency theories partially explain to corporate capital

structure choices in the CEE countries.

According to investigation of Delcoure on firm-specific factors that

determine financial leverage of transition economy companies fails to produce

robust results. The empirical evidence demonstrates the presence of the “modified

Pecking Order” theory in explaining capital structure choices for firms in CEE

countries—retained earnings, equity, bank and possibly debt market. Delcoure found

the differences and financial limitations of banking systems, disagreement in

legitimate systems controlling companies' operations, protection rights for

stockholders and debt-holders, perfection of stock markets and debt markets; and

corporate governance system of enlisted companies are the factors that affect firms'

capital structure choices.

According to Delcoure (2007) lowest business risk countries, Poland and

Slovakia, have the highest debt ratio. At the same time, tangibility of firm's assets is

similar across countries at about 60%, with Russia an outlier at 72%. Furthermore,

long-term debt to asset ratio (0.16 for Czech Republic, 0.18 for Slovakia, 0.21 for

Poland, and 0.25 for Russia) suggests that companies in these countries are mainly

equity capital financed. Banks supply mostly short-term working capital financing

rather than funds for long-term investments. The main reason for the lack of long-

term debt may be the domestic bond markets in these countries are still developing.

The Russian bond market appears to be more advanced in its development than

those of other transition countries. Overall, companies in transition economies are

financed with high cost equity due to inefficient corporate governance, an

underdeveloped bond market, and an incomplete institutional structure and legal

system governing the banking industry. Also, poor corporate governance and lack of

shareholders protection laws supports the extensive use of “non-binding” equity

financing that allows managers to engage in asset-stripping behavior. Short-term

financing, with its lower default risk, enables creditors to monitor managers more

97

effectively. This preponderance of short-term financing decreases the explanatory

power of traditional capital structure theories in explaining capital structure choices

by companies in CEE countries.

According to Delcoure (2007) in the sample of companies in CEE countries,

the relationship between the firm size total and short-term debt is positive and

statistically significant, except for the estimation of long-term leverage for the Czech

Republic, Poland, and Slovakia. The estimated size coefficient in the long-term

leverage model for companies in these countries is negative. These negative

relationships may be attributed to existence of information asymmetries suggested

by Myers & Majluf (1984) and an underdeveloped state of the bond market in these

transitional economies. Also, laws dealing with financial distress are still

developing, leaving debt holders unprotected in the event of default and forcing

companies to acquire funds through short-term loans. The estimated positive

relationship between firm size and long-term debt for Russian companies is not

surprising. Despite some progress in the transition from banking to a market

economy, high Russian government ownership in enterprises along with government

directing credit programs to preferred sectors with price control in these sectors may

have a significant impact on corporate financing patterns.

Delcoure (2007) found that tangibility has a positive regression coefficient

and statistically significant with leverage in CEE countries. It found a negative

relationship between earnings volatility and leverage in Russia and Czech Republic.

This result suggests the existence of bankruptcy or financial distress costs. Russian

bankruptcy law has been strictly enforced since March 1998. Contrary to the

Russian Federation, creditors' rights in the Czech Republic are poorly protected.

This affects banks' willingness to provide long-term loans and creates difficulties in

collecting existing ones. The Members of the Czech Parliament are calling for

bankruptcy law to be closer to the US Chapter Eleven provisions for out-of-court

settlements to encourage resuscitation of troubled firms. Another problem that

Czech corporate bankruptcy law faces is that most Czech judges lack experience

with bankruptcy proceeding, causing a 3 to 4 years backlog in the bankruptcy courts.

Furthermore, the relatively small secondary market would not help the liquidation of

seized assets. Another finding is that corporate tax liability positive estimated

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coefficient and statistically significant for all countries in the sample. It becomes

visible that in the CEE countries, the corporate tax rate affects firms' financing

choices.

Antoniou, et al. (2008) investigated how firms operating in capital market

oriented economies (the United Kingdom and the United States) and bank oriented

economies (France, Germany and Japan) determine their capital structure. They

discovered that tangibility of assets and firm size has positive relationship with the

leverage ratio, but the leverage ratio decreases with appreciate in firm profitability,

growth opportunities and share price performance. They also found that the leverage

ratio is also influenced by the market conditions in which the firm operates. They

asserted that the degree and effectiveness of these determinants are dependent on the

country’s juridical and financial customs. Their results also confirm that firms have

target debt ratios, French companies were swiftest and Japanese firms were slowest

in adjusting their leverage towards their target leverage. Generally they discovered

that a firm’s capital structure is heavily affected by its macroeconomic and

institutional environment, tax systems, corporate governance, the borrower-lender

relationship, exposure to capital markets, and the level of investor protection in the

country in which the firm operates.

Huang & Ritter (2009) investigated on capital structure of publicly traded

firms operating in United States of America and found that a much greater fraction

of their financing slack is fund with external equity when the cost of equity is low.

According to Aggarwal & Kyaw (2010) multinational companies have significantly

lower debt ratio than domestic companies and such leverage clearly and

significantly decreases with the degree of multi-nationality. In addition, compared to

domestic firms, multinational firms seem to pay higher dividends.

Bayrakdaroglu, et al.(2013) analyzed the determinants of capital structure in

supporting the capital structure theories in the emerging market of turkey. They

concluded that Turkish companies do not have target debt ratio. They can suggest

that Turkish companies follow a hierarchical company structure. More specifically,

they claimed that the Traditional Trade-off theory is less successful than the Pecking

Order hypothesis in explaining the capital structure of the Turkish firms. Hence,

firms operating in Turkey are tracking the Pecking Order hypothesis in their

financing behaviors.

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CHAPTER 2 LITERATURE REVIEWshodhganga.inflibnet.ac.in/bitstream/10603/72419/8/chapter 2.pdf · developed under assumptions that characterize an ideal capital market (also called a