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CHAPTER 2
LITERATURE REVIEW
50
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
52
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
54
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)
{source:(Ogden, et al., 2003)
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
55
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)
{source:(Ogden, et al., 2003)
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
56
= (푟 − 푟 )− (2.7)
{source:(Ogden, et al., 2003)
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
58
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
59
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)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
휎 = [∑ ∑ 푤 푤 휎 ] / (2.11)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
휎 = [ ∗ 휎 + 1 − ∗ 휎 ] / (2.13)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
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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)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
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And the expected return on the firm’s assets is
푟 = 푝 + (1 − 푝)[ ] (2.21)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
And the value of the firm’s levered equity is, as before,
퐸 ≡ 푉 − 퐷 (2.23)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
65
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)
{source:(Ogden, et al., 2003)
Given hedge ratio:
훿 = (2.26)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
The value of the levered equity is:
퐸 = 푉 − 푉 − 퐸 /(1 + 푟 ) (2.28)
{source:(Ogden, et al., 2003)
66
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)
{source:(Ogden, et al., 2003)
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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)
{source:(Ogden, et al., 2003)
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)
{source:(Ogden, et al., 2003)
• Correct formula:
푟∗ = 푟 ∗ + 푟∗∗
∗ (2.34)
{source:(Ogden, et al., 2003)
Where:
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푟∗ = 푟 + 푟 (2.35)
{source:(Ogden, et al., 2003)
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,
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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.
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 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
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 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
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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
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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
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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.