iBusiness, 2013, 5, 6-12
doi:10.4236/ib.2013.51b002 Published Online March 2013 (http://www.s cirp.org/journal/ib)
Copyright © 2013 SciRes. IB
The Effect of Fundamental Risk of Listed Companies on
the Mark et P ricing of Accru als Qualit y
——Base on the Data of Shanghai’s Non-Financial Industry
Zhaoyuan Geng, Zhendong Wang, Tian Song, Tingjun Liu,Wenting Chi, Yue Yu, Lufei Wang,
Tong Zhang, Chaoying He, Minjie Wang, Yiyang Zheng, Yipeng Zhu, Gengen Zhou, Tiantian Li
Department of Applied Economics, Business School of Zhejiang University City College, Hangzhou, China.
Email: gengzy@zucc.edu. cn
Received 2013
ABSTRACT
Motivated by the theoretical results of Yee (2006), with accruals quality, the author of this paper studied enterprises'
earnings quality management, and analyzed the effect of accruals quality on capital cost, which is rising with the in-
crease of basic risks, and ext end ed and a ppl ied to hi s st ud y the t heo ret ical stud y o f Fr anci s, LaFond, Olsson and Schip-
per et al .
Keywords: Cost of Capital; Accr uals Quality; Earni ngs Qua lity; F unda mental Risk
1. Introduction
Yee defined Fundamental Risk as “uncertainty in future
dividend payments” [1]. No studies were found pub-
lished in recent domestic literatures specialized in fun-
damental risk. Quite a few studies are carried out based
on information risk to probe into earnings quality, the
level of earning management and the behavior of mani-
pulating profit. Accrued item quality is known as Ac-
cruals Quality. The conception of accruals was presented
by Healy in 1985. With the conception of accruals in a
narrow sense, he measured controllable accruals, and
using accruals amount to express earnings quality [2]. In
a certain sense, accrual basis of accounting can be re-
garded as a potential balance of cost and efficiency
which between a system of submitting cash flow only
and a system that reveals adequately (Beaver1998) .
Regarding the definition of AQ (AQ, Accruals Quali-
ty), it is the expression of Dechow and Dichv that make
AQ become more and more important in choosing ac-
counting procedure, which clear the conception of AQ as
well.
Whether Accruals Quality can be a risk pricing factor
to explain the excessive rate of return of shares, no final
conclusion has yet been reached on this matter [3]. Stu-
dies about Accruals Quality in Chinese literature mainly
lay there weight on researching from the angles of com-
pany management, motivation of contrast and the beha-
vior of earning management in company during financ-
ing, including IPO of quoted companies, the issue of ad-
ditional stocks and allotment[4] , while few people have
paid attention to asset pricing of Accrual Quality men-
tioned above.
2. Hypothesis and Sample Selection
2.1. Conclusion Hypothesis
Yee studied the relationship between earnings quality
and equity risk premium. Equity risk premium is the
component of cost of capital. Mode Yee is based on in-
formation (including noise) backgrounds in the reports
revealed by venture firms that the inventors rely on.
Earnings quality means an earning evaluation mistake
which is modifiable but unpredictable [5]. Yee re-
searched into Accruals Quality in 2006. The research
results indicates t hat inc o me qua lit y risk ha s no i nfl uence
on co st of cap ital when t here is no f undame ntal ris k, and
the inc re a si ng f u nd a ment al ri s k wil l make i nc o me q ual i ty
risk expend its influence on cost of capita l.
We analyze the research results of Yee and come up
with an experiential research direction: how does the
relationship between earning quality risk and cost of cap-
ital rely on fundamental risk, so I suggest the first con-
clusion hypothesis:
H1: earning quality risk will magnify its influence on
cost of capital, wit h increas in g fundamental risk.
2.2. Hypothesis and Sample Selection
The Effect of Fundamental Risk of Listed Companies on the Market Pricing of Accruals Quality
opyright © 2013 SciRes. IB
7
This article takes balance sheet approach to calculate
business accruals, which leads to the second hypothesis
in this article.
H2: This article is based on the empirical data of
non-financial busi ness in Shan ghai s tock exc hange.
Considered that Collins and Hriban’s think CFO cal-
culated in balance sheet approach will lead to more noise
and biased results in the mode, the data before 1998 is
ignored. In the meanwhile, enterprises started to carry
out new Accounting Standards for Business Enterprises
after the year of 2006, short-term investments in the
formula for calculating business accruals are replaced b y
trading financial assets. The samples in this article are
strictly constrained in the companies which have com-
plete data during ten years.
3. Determination of Earnings Quality Risk
and Fundamental Risk
3.1. Take Accruals Quality as the Criteria of
Earnings Quality Risk
Yee used the method of Francis and others evaluate
modificatory the mode of Dechow and Dichiev. In De-
chow and Dichiev mode, DD offered a new method to
estimate Accruals Quality, which is the matching degree
between business accruals and the acknowledgement of
cash flow. Accruals Quality is used for determining
working capital of operating cash flow in the past,
present and future, controlling earning variations and the
level of total assets, facto ries, equip ment and other fixed -
assets. Mode evaluated by Yee is as follows:
,0,1, ,12, ,
3,, 14,,
5,, ,
Re
jt tj jtj jt
j jtjjt
jjt jt
TCACFO CFO
CFO v
PPE
φφ φ
φφ
φυ
+
=++
+ +∆
++
(1)
( )
,,jt jt
AQ
συ
=
(2)
(3)
where
,jt
TCA
signifies business accruals;
CFO
signi-
fies cash flow from operating activities;
,
Re
jt
v
signi-
fies variation of sales revenue;
,jt
PPE
signifies varia-
tion of fixed assets;
AQ
signifies Accruals Quality,
which expressed in the standard deviation of residual
error of mode .
3.2. The Crite ria o f Fundamen tal R isk
Yee conceptualized Fundamental Risk as the uncertainty
of unsolved future dividend payments. Since that enter-
prise value was considered as present value of future
expected dividend, the uncertainty of unsolved future
dividend payments accordingly turns into uncertainty of
enterprise value [5]. However, the concept of fundamen-
tal risk is closed to the definition of information risk
from Jiang Lee and Zhang. They defined information risk
as the uncertainty of enterprise value or the degree that
enterprise value can be evaluated by senior investors [4].
The empirical research is the risk substitute in the rele-
vant researches of Jiang, Lee and Zhang. Jiang, Lee and
Zhan g made use of the unc ertai nty of info rmation, led to
four risk substitutes: the age of enterprise; variation of
retur ns; trad e turnove r; average lasting time of cash flo w
in the enterprise. However, I still pre serve market capita-
lization, the age of enterprise, variation of returns and
trade turnover.I make the analysis of principal compo-
nent to combine the four remain substitutes with funda-
mental risk. The first principal component of these four
risk substitutes is combined with market capitalization.
The age of enterprise, variation of returns, trade turnover
are similar to 45 % of to tal sa mple value which is clo se to
the four components. The average of second, third and
fourth component is approximately 18%.
4. The Empirical Research and Results
In the empirical part, this article takes two methods to
test the relationship between Accruals Quality and cost
of capital of non-financial business in Shanghai stock
exchange under different risk levels: asset pricing deter-
mination; take advantage of the ratio of income to price
to determine cost of capital, research into the relationship
between Accruals Quality and cost of capital, then make
further studies on how does fundamental risk influence
the ratio of Accruals Quality to income price. I made
descriptive stat istics of samples b efore starting these t wo
determinations. This article chooses the data of non- in-
ancial quoted companies in A share market from the year
of 1999 to 2009 as samples, which has already excluded
the quoted companies without complete financial data. It
gets 6 840 samples eventual ly.
4.1. The Asset Pricing Test
1) Sharpes One-way Analys is of Va riance
( )
,,01,,2
3,
*
jt FtmtFti
jt
R RRRAQFactor
AQFactor FRisk
ββ β
βν
−=+−+
++
(4)
Fama-French Three-Factor Model
( )
,,01,,2
34
5,
*
jt FtmtFtt
ti
t jt
R RRRSMB
HML AQFactor
AQFactor FRisk
αα α
αα
αε
−=+−+
++
++
(5)
where
jt Ft
is the additional market profit in
month t;
t
SMB
is the difference in profit between
s mall- scale company and large-scale co mpany in month
t; t
HML is the difference in profit between
The Effect of Fundamental Risk of Listed Companies on the Market Pricing of Accruals Quality
Copyright © 2013 SciRes. IB
8
low-market-share company and high-market-share com-
pany in month t;
i
AQFactor
is rebalance loop of regu-
lating dynamical towards hedge portfolio of monthly
income difference.Since FRisk ranges between 0 to 1,
AQFactor refers to the relationship between accrual
quality and cost of capital in the company with the low-
est FRisk, while AQFactor *FRisk refers to the difference
between accrual quality and cost of capital in the com-
pany with the lowest FRisk and the company with the
highest FRisk. Suppose that the relationship between
accrual quality and cost of capital is based on fundamen-
tal risk, Equation represent the positive correlation coef-
ficients β and α separately as stated in assumption
1.Model Yee indicates that non-systematic risk of earn-
ings quality has no influence on cost of capital as
non-systematic fundamental risk does. Since AQFactor
refers to difference in surplus between high accruals
quality investment combination and low accruals quality
investment combination, and non-systematic risk of ac-
crual quality should have no extra surplus, AQFactor
stands for systematic risk of accrual quality. In fact
FRisk can be hardly divided into systematic and nonsys-
tematic parts and is regarded as non-systematic risk, so
coefficient AQFactor*FRisk tends to 0.
2) Empirical findi ng s
Panel A in Table 1 provide all the coefficients and
specific regression and inspection average t. However,
Gow, Ormazabal and Taylor evaluated the process of
capital pricing and finded that it exaggerates excessively
t test values, the basis of cross section Adjustment of
cluster related to annual regression coefficients. The
consequence of Adjust of the cluster is similar to it. As a
result, most of the relevant inspection values t decrease
and the values t interaction with it increase. Therefore,
data in Panel A is not discussable and we focus on the
resul t in Panel B.
Column”1”, ”2” and ”3” in Table 1 report the testing
results of single factor model, where Column”1” and ”2”
provide the testing results of Fra ncis and others which we
use to compare. In column “2”, AQFactor has a strong
positive correlation with
jt Ft
, while in column
“3” the correlation becomes negative (t = -8.45). Aqfac-
tor*FRisk is also strongly positively correlated with
jt Ft
(t is 39.16). Moreover, with FRisk ranging
from 0 to 1, AQFactor(-0.233) measures the relationship
between AQFactor and the income of a company with
the the lowest fundamental risk, while AQFactor and n
Table 1. C apital pricing test of accru al s quality, future income of stocks, and f undamental risk, 1999 -2009.
Panel A. Fama-Macbeth Regressions by Firm
Predic-ted
Sign
CAPM Fama-French Three-Factor Model
1 2 3 4 5 6
Rm-Rf + 1.066 0.838 0.842 1.012 0.946 0.946
SMB + 0.888 0.509 0.512
HML + 0.218 0.357 0.356
AQfactor + 0.812 -0.199 0.612 -0.439
Aqfactor*FRisk + 1.51 1.52
Adj.R*R 0.114 0.149 0.154 0.158 0.175 0.179
Panel B. Fama-Macbeth Regressions by Year
Predic-ted
Sign
CAPM Fama-French Three-Factor Model
1 2 3 4 5 6
Rm-Rf + 1.027 0.863 0.863 1.189 0.918 0.894
SMB + 0.867 0.55 0.497
HML + 0.436 0.204 0.202
AQfactor + 0.812 -0.223 0.393 -0.473
Aqfactor*FRisk + 1.812 1.814
Adj.R*R 0.082 0.095 0.109 0.098 0.101 0.114
Notes : CAPM is Capital Asse t Pricing Model. The samples include the stock inc omes at least 18 ti mes per month and data from 596 7 compani es from
1999 to 2009. The definitions of var iab les as follow: R M-RF is th e extra return on in vestment of mar ket in vestm ent c ombinati on; SM B is the investmen t
combination income that is hedging with big or small factors of Fama-French. AQfactor is the income of the accural quality investment combination;
FRisk is the first chief factor of the four agencies of which information is uncertain. Panel A reports the averange evalution coefficients and conse-
The Effect of Fundamental Risk of Listed Companies on the Market Pricing of Accruals Quality
opyright © 2013 SciRes. IB
9
quences of regression-anlysin g only owned by 5967 c ompanies , while Panel B provides the average eva lution coefficients an d the conse quence regres-
sion-analysed per 25 year.
Aqfactor * FRisk measures the relationship betwee AQ-
Factor and the income of a company with the highest
fundamental risk.The testing results of Fama-French
Three-Factor Model are displayed in Column”4”, ”5”
and ”6”, where Column”4” and ”5” reports the testing
results of Francis and others, and the Column “6” reflects
the interacted model of AQFactor and RiskScore. Being
(-9.63) in Column”5”, AQFactor changes to (-9.35). Aq-
factor * FRisk is positively correlated with
and e xtremel y notab le(3 9.18 ). In this re gressio n anal ysis,
we can find that when AQFactor decreases, both SMB
and HML decreases from 0.867 to 0.550 and from 0.436
to 0.204. This means FRisk has little influence on SMB
and HML.
If AQ has a strong influence on profit when FRisk is
very high instead of low, we can predict boldly that Aq-
factor*FRisk and AQFactor are both positively corre-
lated with
jt Ft
. To study whether the hypothesis
talked about above, is connected some unusual changes
or AQFactor and nonspecific econometrics affecting
factors of index variables, we evaluate the regression of
every value of FRisk in the model except the Aqfac-
tor*FRisk. Figure 1. sho ws th e re gr ession of 10 points of
AQFactor. In this figure, AQFactor increase only when
FRisk increases, and the lowest value is below 0. More-
over, Figure 1 suggests that the relationship between
AQFactor and FRisk are nonlinear.
4.2. Regression test: Estimation of Cost of
Capital by Using Earning-Price Ratio
The study of Core, Guay and Verdi suggests that the re-
sult of asset pricing test by using factor model is able to
prove the difference in the same period among the earn-
ings, and those earnings are related with the factors in the
models[6].However, this relation between earings and
factors cannot guarantee a premium return. And in order
to be scientifically rigorous, another test will be used to
evaluate the relationship between AQ and cost of capital.
In 1992, Alford has proved that industrial matching is
benefit for controlling the difference between risk and
growth, this means IndEP is able to control other deci-
sive factors of earning-price ratio. In order to study how
fundamental risk influences the relationship between
earning-price ratio and accruals quality, we make regres-
sion o f IndE P of gro wth, AQ, FRi sk and AQ*F Risk. Re-
sults are displayed in Table 2.
There are three variables including Growth, AQ and
FRisk in Column“1”, “2” and “3” of Table 2. factor
growth is significant-1.89, which indicates that IndE P
relaying on dependent variable is effective in controlling
differences of growth. As is shown in the results of re-
search by Francis, factor AQ is positively correlated with
he cost of capital, and significant differences-3.66can
Figure 1 . FRisk Decile and AQfacto r.
Table 2. regression estimation of relationship between ac-
cruals quali ty an d cost of capit alt es ti ng wi th I ndEP and
betwee n fundame ntal risk an d cost of capital .
Predicted
Sign 1 2 3 4
Growth - -0.0044 -0.0041 -0.0029 -0.0025
AQ + 0.008 0.0015 0.011 0.0036
FRis k + 0.0197 0.0126
Risk1 + 0.0034 0.0041
Risk2 + 0.0149 0.0074
AQ*FRis k + 0.0157
AQ*FRis k1 + -0.0018
AQ*FRis k2 + 0.0166
R*R 0.017 0.019 0.015 0.016
Notes: Risk1 and R isk2 a re the fir st two imp orta nt ind ex of ten ris k index es.
This table provides average annual evaluating coefficient of independent
variab les, which or igina ted from IndEP . T test values is st and ard err or based
on annual coefficient evaluation.
t be found. This also corresponds with the negative cor-
relation between AQ and cost of capital. Before the re-
gression estimation, the value of AQ is decimal fraction
within the range from 0 to 1. FRisk is also positively
correlated with the cost, and there are also significant
differences-3.79. Consequently, the value of FRisk,
0.0197, reflects the differences between the cost of capi-
tal of 1.97 per cent of enterp rises with the hi ghest AQ and
those of 1.97 percent of enterprises with the lowest AQ.
Although both AQ and FRiskt equals 3.66 and 3.79
separatelyhave significant differences, the value of
FRisk is more than twice the value of AQ 1.79% VS
0.80%, which indic ates that FRisk is an important i ndex
when determining cost of capital.Row “2” of TABLE
shows the testing results when AQ*FRisk is added to
regression estimation, where AQ and FRisk are allowed
The Effect of Fundamental Risk of Listed Companies on the Market Pricing of Accruals Quality
Copyright © 2013 SciRes. IB
10
to be different. Under this circumstance, both AQ and
FRisk decrease causing by this change. However, FRisk
still has significant differe ncest-3.01, while AQ does
nott-0.51.AQ*FRisk p ositively corr e la te d with cost of
capital and the value is about 10 percent -1.75. T he
summation of AQ and AQ*FRisk signifies the value of
the differences of cost of capital. This demonstrates that
risk o f ea rni ngs q ual ity will have lar ger i nflue nce o n cost
of capital with the increase of FRisk.These factors in-
cludi n g t he a ge of e nte rp r ise , va ri ati o ns in r et ur n, vo lu me
of trade consisting of FRisk may related to AQ. In fact,
the relationship between FRisk and AQ is significant.
The thesis that FRisk has no signi ficant releva nce to AQ
will be confir med in the next sec tion.
4.3. The Methods of Fundamental Risk Test
1) FRisk test: FRisk test corresponds with the Yee's
fundamental risk test in concept. Moreover, return wave
and the volume of trade is market dependent variable
affected by accruals quality. Accordingly, we use the
other 10 dependent variables based on Francis, LaFond,
Olsso n and Sc hippe r, incl udin g two o pera ting ris k inde x:
cash flow and standard deviation of sales volume. Hribar
and Nichols find that these two operating index are con-
nected with the accruals quality obtained from accruals
quality model r e sidual error .
2) Fundamental risk disintegrated by component analy-
sis
We analyse two risks by using component analysis to
reduce risk variable(as showed in Table 2). The first
principal component of 10 proxy variables of fundamen-
tal risk are Size Sd(CFO) and Opcycle, and the second
are SD(sales volume)leverage ratio and Negearm[7].
Simil ar to fund a me nt al ri s k, t he t wo compo ne nts a re b ot h
decimal fractions ranging from 0 to 1. Consequently,
fundamental risks ar e Risk1 and Risk2 in Table 2.
To study the sensibility of the testing results to funda-
menta l risk, we make the regr ession o f IndEP of gro wth,
AQ, Risk1, Risk2, AQ* FRisk1 and AQ* FRisk2. The
Column”3” in Table 2 displays independent variable:
growth, AQ, Risk1 and Risk2. As mentioned before, AQ
conforms the principles that accruals quality is negative
correlated with cost of capital. Cost of capital is substi-
tute of Risk1 and Risk2 in fundamental risk. What is
funny is that Risk1 has no significant differences(-0.91),
while Risk2 is si gnificantly positively correlated0.0149,
-6.82. This means Risk1 refers to nonsystematic risk
which is not market-priced, and Risk2 refers to the sys-
tematic fundamental risk which is market-priced.
In Column”4” of Table 2, regression analysis of AQ*
FRis k1 a nd AQ* F Ris k2 i s ca rri ed o ut, a llo wing t hat AQ
is different from Risk1 and Risk2. This change leads to
decrease of AQ and Risk2 and increase of Risk1. Al-
though Risk1 still has significant differences(-2.93), AQ
has no significant differences(-0.52). Interacted coeffi-
cient AQ*FRisk2 is positively correlated with cost of
capital and has significant differences(-4.66). Moreover,
in this regression analysis, Risk1 and AQ*FRisk1 pos-
sess no significa nt differences.
5. Other Regression Estimation: Implicit
Cost of Capital
The result of the study by Easton and Monahan, Guay,
Kothari and S hu, suggested that the co st of capital calc u-
lated by earning-price ratio has weak relationship with
the Yield T o Maturity(YT M). In this section, we method
to estimate cost of capital will be adopted to study the
sensibility of the testing results in Section . In this
method, several indexes of implicit cost of capital will
rise and thus diminish the measurement errors. Referring
to the research method of Dhaliwal, Heitzman and Li,
cost of capital will be calculated using discount rate im-
plied within different applying methods of Residual Re-
turns Value Model.
5.1. Four Value Models
1) Gebhardt, Lee and Swaminathan Model
Gebhardt, Lee and Swaminathan Model is used to es-
timate Enterp rise Value:
( )
( )
11 11
1
12 11
11
1
1
t gls
t tti
tgls
tgls t
gls gls
FROE r
PB B
r
FROEr B
rr
+
+−
=
+
+
= ++
++
(6)
where
gls
r
: cost of capital; B: amo unt at t he be ginn ing o f
year;
FROE
: earnings forecasts
2) Claus and Thomas Model
( )
( )
( )
511
1
4
5
1
( )1
( )1
tict ti
t tti
tct
s ct
ct ct
FEPSr B
PB B
r
FEPSr Bg
rg r
++− +−
=
= ++
−+
+−+
(7)
where ct
r: cost of capital;
S
FEPS
: earnings forec asts o f
per share in the first two years, or forecasts of long-term
growth ra tes in the foll owing t hree years .
3) Gode and Mohanranm Model
Gode and Mohanranm Model which based on Earn-
ings Growth Model by Ohlson and Juettner-Nauroth
Model is as follows:
( )
( )
120.03
t
gm f
t
FEPS
rA Agr
P
+
=++− (8)
The Effect of Fundamental Risk of Listed Companies on the Market Pricing of Accruals Quality
opyright © 2013 SciRes. IB
11
( )
( )
12
21
1
0.50.03 0.5
t
ft
tt
t
DPS
A randg
P
FEPS FEPS
FEPS
+
++
+


= −+



=
(9)
Easton Model DPSt is the dividend per share during
period t. Assu me that DPSt equals to DP S0, and the de fi-
nitions of the other variables are the same as that men-
tioned above. Thus, Easton Model that separated from
Earnings Growth Model is as follows: where the defini-
tions of variables are the same as that mentioned above.
2 11
2
tpeg tt
t
peg
FEPSr DPSFEPS
Pr
+ ++
+−
=
(10)
5.2. Analy sis of Resul ts
In the calculation, each of fou r averages of cost of capital
is evaluate, thus we gain a single cost of capital estimate:
AvgCOC[13]. Compared with the results of regression
estimation of IndEP, AvgCOC requires more precise data,
so the sample size should be diminished from 6840 to
5967.
The estimating results based o n AvgCOC ar e as shown
in Table 3, where the data in Row “4” are the same as
those in Row “4” of Table 2.T here are three independent
variables in Row “1” of Table 3: Growth, Accruals
Quality (AQ) and Fundamental Risk (Frisk). According
to Table 3, AQ is posit ively co rrelated with the cost, a nd
significant dif ferences (-6.93) can be found between four
models. This also corresponds with the negative correla-
tion between AQ and cost. The value, 0.0115, reflects the
difference between the costs of capital of 1.15 percent of
enter p ri ses wit h the highe st A Q a nd tho se of 1 . 15 p e rc ent
of enterprises with the lowest AQ. This value is farther
higher than 0.008 in Table 2. Moreover, Frisk is posi-
tively correlated with the cost and there is also significant
differences (-13.40) between four models. The value of
Frisk is 0.0392, which is more higher than 0.0197 in Ta-
ble 2. In Row “2” of Table 3, a related variable
AQ* Fris kis added, , where AQ and Frisk are allowed
to be different. As a result shown in Row “2”, decrease
can be found in both AQ and Frisk causing by this
Table 3. Regression Analysis of the relationship between
cost of stock (estimated by implicit cost of average capital)
and Accruals Quality and Fundamental risk.
Predicted
Sign 1 2 3 4
Growth - -0.0284 -0.0282 -0.0231 -0.0231
AQ + 0.0115 0.0071 0.0085 0.0038
FRis k + 0.0392 0.0332
Risk1 + 0.0231 0.022
Risk2 + 0.0264 0.0232
AQ*FRis k + 0.0133
AQ*FRis k1 + 0.0026
AQ*FRis k2 + 0.0081
R*R 0.167 0.171 0.147 0.151
change.In Row “3” and “4”, Frisk is used to replace the
other index of fundamental risk: Risk1 and Risk2. As a
result in Row “3”, Risk1 and Risk2 are systematic fun-
damental risks that are market-priced, opposed to the
resul ts in Table 2.
6. Conclusion
In this article, two sets of tests have been taken to study
the effect of Fundamental Risk on the Market Pricing of
Accruals Quality: Firstly, using asset-pricing determina-
tion to estimate the relationship between prese nt wo rt h o f
income and Accruals Quality. Secondly, using price-
income ratio to estimate cost of capital, meanwhile stud-
ying the fundamental risk’s influence on the relationship
between Accruals Quality and price-income ratio. Tests
suggests that, there is no internal connecting link be-
tween Accruals Quality and cost of capital which is cal-
culated by the present worth of income of low- funda-
mental-risk enterprises. Ho wev er, the interaction be-
tween Accruals Quality and fundamental risk connects
closely with cost of capital. And when this interaction
exists, the main influence from Accruals Quality will
disappear. In the final result, we can conclude that, as
fundamental risk rises, Accruals Quality’s influence on
cost of capital is enhanced, but this influence on cost of
capital of any enterprises will never exceed that of
low-fundamental-risk enterprises. In fact, our results do
not correspond with that of Yee about whether the ri s k o f
Earnings Quality is systematic or not. Yee found that
cost of capital i s related with s ystematic risk of E arnings
Quality but not with nonsystematic risk of Earnings
Quality.But in this study, it is the total risk of Earnings
Quality that we focus on, and we do not divide the total
risk i nto t wo sep arate d pa rts, so the fur ther stud y may b e
a huge challenge. Finally, however, we can conclude in
this study that fundamental risk actually affects the rela-
tionship between Earnings Quality and cost of capital.
And this suggests that total risk of Earnings Quality at
least has systematic parts within it. Because if all risk of
capital were not systematic, no relationship will be dis-
covered between Earnings Quality and cost of capital,
nor will any changes take place as fundamental risk
change.
REFERENCES
[1] Yee, K. K. Earnings Quality and the Equity Risk Premium:
The Effect of Fundamental Risk of Listed Companies on the Market Pricing of Accruals Quality
Copyright © 2013 SciRes. IB
12
A Benchmark Model.Contemporary, Accounting Re-
sea r c h, 2006, 23 (Fa ll ): 83 3877.
[2] Healy P M. The Effect of Bonus Schemes on Accounting
Decisions [J]. Journal of Accounting and Economics,
1985, 7, ( 1-3):85-107.
[3] Francis J, La Fond R, Olsson P, Schipper K. The Market
Pricing of Accruals Quality [J]. Journal of Accounting
and Economics, 2005, 39(2):295-327.
[4] Nichols C. Fundamental or Information Risk. An Analysis
of the Earnings Quality Factor [R]. Ithaca: Cornell Uni-
versity, 2006.
[5] Hribar, P., and D. C. Nichols. The Use of Unsigned Earn-
ings Quality Measures in Tests of Earnin gs Management.
Journal of Accounting Research, 2007, 45 (December):
10171053.
[6] Core J E, Guay W R, Verdi R S. Is Accruals Quality a
Priced Risk Factor? [J]. Journal of Accounting and Eco-
nomics, 2008, 46, (1):2-22.