iBusiness, 2013, 5, 110-112
http://dx.doi.org/10.4236/ib.2013.53B023 Published Online September 2013 (http://www.scirp.org/journal/ib)
The Relationship between Share Price Gains, Corporate
Performance and Risk
——Empirical Analysis Based on Agriculture, Construction, Finance
Yujuan Zhao
School of Business, Soochow University, Suzhou, Jiangsu Province, China.
Email: Yujuan_zhao@163.com
Received July, 2013
In this paper, we have tested the relationship between the stock returns, corporate performance and investment risks
with the sample of listed companies in the agricultural, construction and financial industries in the A-share stock market.
Descriptive statistical analysis, correlation test and regression analysis indicate that there is no relationship between
stock returns and corporate performance, but there exists a positive correlation between the stock returns and investment
risks in the construction and financial industries.
Keywords: Share Price Gains, Corporate Performance, Investment Risk
1. Introduction
In developed stock markets, share price gains and in-
vestment risk, performance of listed companies should
have more significant positive correlations. Listed com-
panies in different industries have different market
structures, profitability and industry life cycle, so the
share price gains, investment risk and the performance of
listed companies should also have significant differences.
The relationship between share price gains, corporate
performance and investment risks have been studied
abroad. Colin Clubb, Mounir Naffi have analyzed the
relationship between the present and the future book
value and returns on equity (ROE). Their log-linear
model has a high predictive power for the stock returns
of the U.K. listed companies. [1]. Chinese scholars of the
research include: On the listed company's stock yields
standard deviation and return on equity (ROE), they
analyzed the fluctuations in the ratio of the standard de-
viation[2,3], or studied the time series analysis on listed
company's performance and stock price[4,5].
2. Sample Select
Our sample includes 51 listed companies in the agricul-
tural, construction and financial industries. The data in-
clude the ex-right and ex-dividend stock price at the end
of each month, and the financial data in the 36 months
from 2009 to 2011. We have applied statistical and
econometric methods for empirical studies and analyses,
in order to address the following issues:
·Firstly, whether and to what degree there exists cor-
relation between the stock returns and corporate per-
formance and whether there exists industrial differences;
·Secondly, whether there exists correlation between
the stock returns and the risks, whether the risks can ex-
plain the stock returns, and whether there exists industrial
2.1. Industry Selection
We have selected the stocks in the main board for the
study. In select research object, we follow the criteria
“Three Industries Classification Provisions” (www.stats.
gov.cn) published on January 14, 2013. The industries
have primary industry A class (agricultural), secondary
industry E class (construction) and tertiary industry I
class (finance). We also follow the SFC industry classi-
fication to select specific subdivision of industry.
2.2. Conditions of Sample Select
The sampling period ranges from 2009 to 2011. The
sample companies include those listed companies releas-
ing the annual report during the sample period. Flush
software and resset database information are the main
object of analysis. We use complex compound interest to
adjust the stock price data. Sample stocks have been fil-
tered according to the following criteria:
1) Considering that the A-share market and segmenta-
tion of B-share markets, investment and pricing differ-
ences, excluding issued B-shares or H-shares votes a
Copyright © 2013 SciRes. IB
The Relationship between Share Price Gains, Corporate Performance and Risk 111
share listed companies;
2) In view that the shares of newly listed companies do
not release enough data and that comparison is prone to
error, in order to avoid the effects of new shares, we only
select the data of the shares listed before November 31,
3) Because ST company and some other companies
with negative net worth have irregular status, we exclude
ST, *ST and PT unit;
4) To avoid the influence of outliers, we exclude
companies with defect data and missing data
5) In order to maintain stability of the sample company,
removed during the sample period to change the main
business of the company.
Finally, we selected 16 listed companies in the agri-
culture, 22 listed companies in the construction industry
and 13 listed companies in the financial sector.
3. Index Selection
This paper has discussed three main indicators: the com-
pany performance, stock prices earnings and investment
3.1. Company Performance
This paper chose to use the business performance of the
most important indicators—Return of Equity(ROE). Re-
turn on equity is the company's profit after tax divided by
the percentage rate of net assets. The indicators reflect
the level of shareholders ' equity income, measuring the
shareholders into the company's unit capital receive prof-
its, which companies create value for shareholders, to
measure the efficiency of the companies using its own
capital. In theory, the higher the modified index values,
the better the performance of the company will be.
3.2. Share Price Gains
A study on characteristics of months of stock price be-
havior this article proceeds to month stock return. Stock
investors higher yields indicate stock profits gained.
3.3. Investment Risks
Risk is measured by deviation of the rate of return on
saving. Risk is the uncertainty about profits, so we
measure the risks as the absolute value of the difference
between the month-end closing price of each stock and
the closing price the industries.
4. Regression Process
According to descriptive statistical analysis, the average
revenue in the construction industry has amounted to
2.75%, the highest in the three sampling industry. Agri-
cultural stocks months yield is slightly lower than the
construction industry. Finance stock returns are 1.25%,
far below the stock months yield in agriculture and con-
struction, basically only one half of the saving rate in the
construction industry. From profit risks, profits in the
construction industry are 7.26%, lower than agricultural
8.28%. Saving yields the lowest 4.76%, also have the
lowest profit value-at-risk in the financial industry, but
the value is relative to the yields a higher risk. Judging
from the ROE, finance has the value of maximum, 9.48%,
agriculture has 4.11% and construction has 5.11%, re-
spectively, the difference between the two is only 1%, far
less than the financial industry ROE. We can conclude
that ROE of the financial industry are significantly
higher than the other two sectors, indicating generally
better performance of the financial sector.
In this article, risk and performance are explanatory
variable, for regression analysis of stock returns. Regres-
sion models are:
R=α1+β1σ+υ1 (1)
R=α2+β2ROE+υ2 (2)
R, σ, ROE, respectively for the month stock return,
risk and profit return on equity;
α1 and α2 are for intercept, β1 and β2 are for regression
coefficients; υ1 and υ2 are for errors. For the entire com-
pany, we take the risk and performance of the company
as explanatory variables for regression analysis of stock
returns. (1) (2) can have all three respectively by a for-
mula of regression equation:
R=0.030159-0 .107312 σ (3)
1.674024 -0.786377
R=0.054489-0.908144ROE (4)
0.998175 -0.629839
R=-0.122864+2.071953σ (5)
-2.834386 *** 3.701295***
R=0.019575+0.154728ROE (6)
0.559989 0.2 65277
R=-0.131175+3.017579σ (7)
-3.592490 ** 4.363768***
R=0.004501+0.084075ROE (8)
Copyright © 2013 SciRes. IB
The Relationship between Share Price Gains, Corporate Performance and Risk
Copyright © 2013 SciRes. IB
0.084193 0.160409
(**at a confidence level of 95% significant, *** at a
confidence level of 99% significant)
The above results indicate the following points:
1) For all industries, with ROE as explanatory vari-
ables on stock returns, the regression coefficients are not
significant in t-test.
2) Relationship between investment risk and stock re-
turns for agricultural companies’ regression is not sig-
nificant. For the construction industry, at 99% confidence
level, investment risk and stock returns are linearly cor-
related. Growth of investment risk by 1% would increase
earnings 2.071953%. Financial risk on stock return on
investment is significant at 99% confidence level, which
indicates that with increasing investment risk, stock re-
turns will increase.
5. Conclusions
The above empirical research on company's performance,
investment risk and stock return can come to the follow-
ing conclusions:
1) In the stock market in China, the relationship be-
tween share price gains, investment risk and return on
equity in the agricultural and the construction industries
are closer, the value of share price gains and investment
risk are much lower in comparison, but return on equity
of the financial sector is far higher than the two indus-
tries. Primary and secondary industries in the Chinese
stock market have a strong convergence of the listed
company, tertiary industry's share price gains and in-
vestment risk but do not match its return on equity. In-
vestors have underestimated as represented by the finan-
cial industry's profitability of listed companies of the
tertiary industry, and it’s better to invest in the compa-
nies in the primary and secondary industries.
2) On the construction and the financial sector, share
price gains show strong correlation with investment risk.
We can consider the proceeds of its share price gains in
the construction industry and the financial sector in part
as the premium of risk.
3) Listed company's share price gains are out of its
performance of listed companies relying on the sub-
ject—ROE. This suggests that China's stock markets are
strongly speculative. In developed stock markets, inves-
tors fully obtain enterprise value on the basis of relevant
information to invest in listed companies. In pursuit of
maximization of investment wealth, the investors are
driven by their preference for the good performance of
listed companies. The investors offer high for companies
with good performance, and company can only bid low
with their poor performance. The process makes capital
cost difference, enables the optimization of resources
allocation of stock market. In a large number of empiri-
cal studies, the mature markets have indicated that most
of the listed companies have a good performance and
high stock price. China’s stock market is an emerging
market and still in its transition phase. The system and
the market participant in China are not so mature as those
in the developed markets. The intermediary organizations
are quite weak so the information release is inefficient.
The market structures and market rules are still inade-
quate, so the market has long been characterized by fre-
quent, intense market volatility.
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