the relationship between information asymmetry …

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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS

COPY RIGHT © 2012 Institute of Interdisciplinary Business Research

657

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VOL 4, NO 1

THE RELATIONSHIP BETWEEN INFORMATION ASYMMETRY AND

TOBIN'S Q RATIO IN TEHRAN STOCK EXCHANGE

Mahmoud Mousavi Shiri, Narmin Ebrahimi

Department of Management, Economics and Accounting, Payame Noor University, I.R. of Iran

Abstract:

One of the main points during decision making of potential and de facto capitalists to invest in

other companies is to evaluate performance of the companies. This process becomes difficult if

data isn’t distributed equally in market. One of evaluation performance method is Tobin's Q

Ratio. Normally this ratio should be equal 1; it can be more than 1 when there are investment

opportunities for a company, and vice versa.

The aim of this research is to present evidences based on relationship existence between

information asymmetry level and Tobin's Q Ratio in evaluating performance of firms accepted

in Tehran Stock Exchange to find answer for this question: whether value of stock market of

firms decreased and leads to decrease of Tobin's Q Ratio, when there is information

asymmetry? For testing hypothesis experimentally, Pearson correlation coefficient has been

used. So we selected firms accepted in Tehran Stock Exchange and data were analyzed by

EXCEL and SPSS software. Results indicated that there is no significant relationship between

information asymmetry level and Tobin's Q Ratio. Also they indicated that there is significant

relationship between EPS, PEPS and Tobin's Q Ratio.

Keywords: Information asymmetry, Tobin's Q Ratio, Tehran Stock Exchange

1. Introduction: Now a day, in capital markets any participant and potential capitalists need instruments to

predict future, to maximize profits and market.

The main important instruments to adopt correct and better decisions and to obtain expected

and appropriate efficiency are access to information and its realistic and scientific analysis.

Security and exchange organization as a basic part of capital market and index of economic

development, with 3 centuries of history in the world, is an organized and formal market of

investment to buy and sell shares and bonds by special rules. Investment in such market

requires security of people’s capital. Such security contains reliable reliance concerning

decision making about buying and selling shares. If market is efficient, all data has reflection in

stock price. And any new disclosure of information will immediately reform or adjust the stock

price. But if it isn’t efficient, disclosure of information isn’t reflected immediately in stock

price. So individuals, who have better access to information as compared with others, use

information before formal declaration or change the stock price by unusual stock supply

demand. This status is called information asymmetry in which information isn’t distributed in

balance and equal form. Existence of information asymmetry in market causes capitalists

demand higher returns to compensate investment risk. So there will be difference between

suggested price of buying and selling shares. And the more the range of difference, the more

the information asymmetry rate is. And this affair increases unreliability of capitalists about

getting good returns from investment. To increase efficiency and to decrease risk, firms’

performance should be evaluated correctly and scientifically and finally their value should be

determined. So QTobin, as an indicator of market value to book value of any firm, is one of

reflector economic indices of efficiency range and appropriate performance of trade units. In

capital market, value of stock market and shareholders wealth, has direct relationship with

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shareholders returns which is influenced by the distribution of information in the market and

market outcome based on the information from profitability landscape of trade unit. By

increasing non equal range of information distribution in markets creation and intensification of

information asymmetry range between exchange parties is provided and also by increasing risk,

stock value and efficiency are decreased. On this basis, the main issue in current research is

this, whether there is relationship and correlation between QTobin and information asymmetry

or no? And we are looking for an answer of following question. Whether by increasing

information asymmetry, their stock value and QTobin rate is decreased?

2. Literature Review

Important discussion of equal distribution of data in capital markets is an issue which has

involves the accounting and financial theorists mind since 40years ago. And its negative results

on relative decrease of markets efficiency has led to multiple university and professional efforts

to decrease information asymmetry level and to develop transparency of markets by using

certain methods of information disclosure by companies. So that, 3 scientists, Micagel Spense,

George Akerlof, Joseph Stilitz, in 1970 established an attitude as information asymmetry.

Using experimental researches, they indicated that information asymmetry can lead to increase

of selected range of harmful in market, so relative efficiency of market is decreased. And this

affair is created before transaction.

Riga Kim in 1994, by presenting a method, indicated that some informal people in market such

as shareholders, because of their access to information, are more able than others to evaluate

bettr the equity performance by declaring profit. They think that profit declaration leads to

transaction increase and information asymmetry development. Kyle (1985) Easley and Ohara

(1994) found out that when information asymmetry is increased, transaction volume is

increased too. Diamond Vercechi (1991) found out that when information asymmetry

concerning firm stock is increased, its inherent value is different from stock value of capitalists.

So, actual value will be different from expected value of shareholders. Ormier and Aerts

considered disclosure features about human and society capitals and information asymmetry

between managers and capitalists. Gal and Kay considered relationship between protection law

of firms’ affairs and information asymmetry in financial markets. Results show that firms

information in firms containing more storage protection laws and better performance of law,

have less information asymmetry compared with similar firms. And there is less information

asymmetry in developed markets. In 23rd

of October, 2000 Security and Exchange

Commission, bound institutions and companies to present more clear information and to apply

voluntary disclosure methods of public firms through information disclosure law of market

value. A research by Straster (2002) considered relation between fair disclosure law and

information asymmetry. According to economic theories, increasing amount and quality of

disclosure must decrease the information asymmetry of firms. Results indicate that increasing

available information amount based on law, decreases information asymmetry. Brown

Vehelghist (2004) studied the quality of disclosure influence on information asymmetry.

Results indicated that threr is diverse relation between disclosure quality and information

asymmetry. But there is positive relation between disclosure quality of midterm reports and

information asymmetry. KanaGartnem and Labo (2010) considered the relationship between

quality of managing firms' affairs and information asymmetry in capital market during midterm

profit declaration. Results indicate that a change in suggested price of purchase during profit

declaration has negative relationship with independent board of directors, their activities and

stock percent belonging to employers and board of directors. Also they indicated that changes

depth has positive relation with mentioned factors structure. Durnev and Nain (2007) did a

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research about role of internal trade laws to prevent confidential information business by

considering 2189 firms of 21 countries. They found out that existence of internal serious laws

leads to decrease of confidential information business. But, internal trade limitations have less

efficiency for firms with high representation cost to prevent confidential information business.

Filipse and Gomez (2008) indicated in their research that information asymmetry has main role

in selection of the kind of securities in public and special markets, and also, in selection of

market in which such securities are issued. Results of research indicate the quality of stock

market reaction to different levels of disclosure information accuracy. Totally, quantitative

disclosure of information leads to decrease of stock price fluctuations and increase of firms

Tobin's Q Ratio.

In 2005, Vatanparast considered the accounting information role to decrease information

asymmetry in Tehran exchange. Results indicated that, during studied period, there was

information asymmetry. This affair, before profit declaration period was more as compared

with after declaration period. How do capitalists evaluate firms’ performance in terms of

information asymmetry? There are different approaches to evaluate firms’ performance, such

as: accounting approach, financial, economic, fusion management. Required data is collected

through basic financial statements, reported by relative companies, to evaluate ratios of

accounting and financial management approach. But fusion, economic approaches use not only

basic financial statements’ information but also market information. These approaches are

more appropriate as compared with accounting and financial management approaches, because

possibility of information distortion is low. Fusion approach includes following methods:

Price to profit ratio, market value to book value of each stock and Tobin's Q Ratio. Researchers

have been done as a criterion of performance evaluation about Tobin's Q Ratio application, are

as follow:

In 1969, an economist, Jims Tobin used market value to book value of investment ratio to

evaluate investment projects, so this was known as QTobin index. For the same purpose,

Berger and Sintia (1988) investigated the effect of this criterion and found its usage useful to

evaluate firms' performance in a research called QTobin and importance of firms' performance

discussion. Lange, Stolez and Vaking (1989) in an experimental study used QTobin as an index

for relationship between management performance and resources created from firm

participation in tender. Mack Kanel and Serviz (1990) examined the significance of QTobin to

consider the relationship between kinds of ownership and firms’ value.

3. Research methodology:

3.1. Research hypothesis:

Basic hypothesis:

There is sig relationship between information asymmetry and Tobin's Q Ratio.

Subsidiary hypothesis:

First hypothesis: there is sig relationship between predicted earnings per share (PEPS) and

Tobin's Q Ratio.

Second hypothesis: there sig relationship between earning per share and QTobin.

3.2. Research variables:

Information asymmetry is called non equal distribution of new information in capital markets in

absence of necessary commodity in market.

In current research,

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Tobin's Q Ratio: this ratio is an economic index and is used in accounting to evaluate firms and

their appropriate performance rate, and is as follow:

Tobin's Q Ratio should be 1, and if it is more than 1, indicates growth and investment

opportunities for considering firm. So it is appropriate for investment (since capitalists consider

QTobin of considered firms, before investment). The aim of this research is to consider

relationship between QTobin and information asymmetry in firms, and to answer this question

that what is the relationship between these two and how does it help capitalists in decision

making.

3.3. Time domain of research and sampling method:

Research time domain involves 4 year old information of firms accepted in Tehran Stock

Exchange from 2002-2006.

Statistical community of present research is firms accepted in Tehran Stock Exchange. Firms of

statistical community were selected to determine studied sample. End of their financial year is

29th

of December.

And they were accepted in stock exchange before 2003. And they didn’t change their financial

year during time domain. Their last stock price is accessible and also firms which were active

in investment and financing (financial supply) were deleted from selected samples. There were

N=400 firms in stock exchange in 2002, that 182 firms selected randomly among statistical

community. Sampling method is simple random method. Hypotheses testing results being

generalized to total community, sample amount should be equal to or more than standard

amount and is calculated through this formula:

In this research, we decide to test statistically two quantitative variables by distance scale, so

we will use Pearson and Spearman correlation coefficient test to determine sig relationship

between basic variables and we will apply this test after collecting data and inserting it in

EXCEL and through help of SPSS software. Then achieved outputs will be analyzed.

To provide data of firms accepted in Tehran security and exchange considering research

variables, most of them are achieved in firms’ financial statements and stock price in exchange

market. Different resources have been used such as information system of Rahavard and Tadbir

Pardaz, financial statements of firms and Islamic studies center site of exchange. To process

data, EXCEL and SPSS software has been used.

Considered period is during 2002-2006, and contains all companies listed in Tehran Stock

Exchange, and has following circumstances: 1) They were profitable in 2002-2006.

2) End of their financial year was at the end of December, and there wasn’t any change in

mentioned period.

3) In all considered firms, there is one stock transaction in financial year that their market price is

accessible.

4) Firms that their data are in exchange.

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4. Data Analysis: In scientific researches especially experimental and Field researches, analyzing data collected from

considered community is one of the most important research sections. Although analysis processes are

different to collect data considering the kind of research, research problem, hypotheses nature, kind of

attitude, and used instruments. But this part of research is the main research activity of researcher and

the essential component of every research.

In analysis process, data are refined not only in terms of concept but also experimental aspect. And

different statistical techniques have special role in inferences and generalizations. Researcher considers

his hypotheses using descriptive statistics and doing statistical tests, finally they respond to their first

hypotheses.

5. Results

5.1. Descriptive statistics of research

Descriptive statistics of research are formed by concepts such as frequency table, frequency Histogram,

distribution ratios, size of tend to center, dispersion sizes. Descriptive explanation of data is used to

determine phenomenon status or problem or studied issue or features of studied issue are explained

statistically. So, descriptive statistics of variables and collected data are explained.

5.2. Analyzing statistical distribution of QTobin

The first used ratio of this research is Tobin's Q Ratio. Descriptive statistics were summarized in Table

1.

Table 1. Descriptive statistics of Tobin's Q Ratio

Kurtosis

Skewness

variance

Std. Deviation

Mean

Rang

N

Q2BIN

Std.

Error

Statistic

Std.

Error

Statistic

Statistic

Statistic

Std.

Error

Statistic

Statistic

Statistic

.358

.358

.358

.358

8.25 12.58

46.98

121.74

.180

.180

.180

.180

2.736 3.155

5.728

10.194

2.054E7 1.582E7

9354990.582

3.428E7

4532.2 3978.

3058.5

5854.8

335.9 294.8

226.7

433.9

3400.25 2906.71

1930.69

2268.01

25299.05 27700.13

31001.21

73346.59

182 182

182

182 182

Q2BIN8I81 Q2BIN8I82

Q2BIN8I83

Q2BIN8I84 Valid N

As observed in above table, Tobin's Q Ratio has been achieved for 182 considered firms in this research

during 2002-2005. The maximum changes range of this ratio has been 73346 in 2005 and the minimum

change range has been 25299 in 2002. On the other hand, all skewness coefficient amounts were

positive and right distribution of this ratio as compared with normal distribution. Furthermore, statistical

distribution of QTobin for all firms in 4years is positive in terms of kurtosis coefficient. So it indicates

the longer distribution as compared with normal distribution. Other statistics can be extracted from

above table such as Median, variance, Tobin's Q Ratio for considered firms.

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5.3. Analyzing statistical distribution of information asymmetry

Descriptive statistic of information asymmetry for considered firm has been summarized in Table 2.

Table 2. Descriptive statistic of information asymmetry for considered firm

kurtosis

Skewness

variance

Std.

deviation

Mean

Rang

N

INFORM.

Std.

Error

statistic Std.

Error

statistic statistic Statistic Std.

Error

statistic statistic statistic

.358

.358

.358

.358

10.817

17.344

148.117

135.482

.180

.180

.180

.180

-2.802

-3.394

-11.717

-10.929

3.264

2.487

40.090

13.700

1.80

1.57

6.33

3.70

.13391

.11689

.46933

.27436

-.3896

-.1496

-.7853

-.3957

14.23

13.70

85.94

48.06

182

182

182

182

182

Inform81

Inform 82

Inform 83

Inform 84

Valid N

Calculated statistics for information asymmetry during 2002-2005 was suggested that, the maximum

changes range of information asymmetry was 86 in 2004. This statistic reaches its minimum range i.e.

13/7 in 2003. Considering variance amount, we can say that maximum and minimum distribution range

of information asymmetry were for 2004 and 2003 respectively. On the other hand, unlike the Tobin's Q

Ratio, skewness coefficient of data concerning information asymmetry are negative, which indicates

that statistical distribution of information asymmetry is in left direction as compared with normal

distribution. This distribution considering positive kurtosis coefficient during 4 years study, contains

longer distribution.

5.4. Analyzing statistical distribution of Predicted earnings per share (PEPS) and earnings per share

(EPS)

Statistics concerning these two variables have been summarized in Table 3.

Table 3. Descriptive statistics of PEPS and EPS

Kurtosis

Skewness

Variance

Std.

Deviation

Mean

Rang

N

PEPS

EPS

Std.

Error

statistic

Std.

Error

statistic

statistic

statistic

statistic

statistic

statistic

.181

.181

15.376

8.665

.091

.091

2.734

1.053

351054.247

813948.431

592.49831

902.197

700.1297

648.27

6703.00

11737

728

728

728

PEPS

EPS

Valid N

Changes range, median, std deviation, variance, skewness coefficient and kurtosis coefficient

are main statistics which have been achieved for PEPS and EPS. These 2 variables have been

calculated for 128 firms during 4 years study (According to this, we have 728 data). Being

positive the two coefficients of skewness and kurtosis suggests right skew and longer kurtosis

of these data statistical distribution as compared with normal distribution.

5.5. Statistical distribution of other data

Statistics concerning the collected data of this research have been summarized in Table 4 such

as total assets, total debts, capital and market value for considered firms during 4 years.

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Table 4. Descriptive statistics of other collected data

Kurtosis

Skewness

Variance

Std.

Deviation

Mean

Rang

N

Title

Std.

Error

Statistic

Std.

Error

Statistic

Statistic

Statistic

Std.

Error

Statistic

Statistic

Statistic

.181

.181

.181

.181

133.045

160.728

54.125

25.447

.091

.091

.091

.091

10.526

11.785

6.621

4.709

1.387E13

9.076E12

3.274E11

7.234E18

3723756.206

3012629.813

572200.742

2.690E9

138011.587

111655.490

21207.170

9.968E7

958326.27

686850.50

204600.23

1.08E9

56591551

4732518

6997000

231122100

00

728

728

728

728

728

Total

Asset

Total Debt

Capital

Market Value

Valid

N

5.6. Statistical testing of research hypotheses

In this part, research hypotheses are teased by using statistical analysis and SPSS software.

5.6.1. Basic hypothesis testing

Basic hypothesis testing of research is that, there is sig relationship between information asymmetry

level and Tobin's Q Ratio. In another word:

H0: There is not sig relationship between information asymmetry level and Tobin's Q Ratio

H1: There is sig relationship between information asymmetry level and Tobin's Q Ratio

Since, 2 variables of information asymmetry level and Tobin's Q Ratio are quantitative; correlation

coefficient testing should be used to consider their sig relationship. Summary of results are observed in

table 5.

Table 5. Test results of research basic hypothesis

According to above output, H0 hypothesis is confirmed, if sig amount is more than 0/05. So we can

claim that there is sig relationship between information asymmetry level and Tobin's Q Ratio. In on the

other hand, low correlation rate is indicator of no sig relationship between 2 variables.

In another words, research basic hypothesis (H1) is rejected (failed).

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5.6.2. Testing first subsidiary hypothesis of research

First subsidiary hypothesis of research is defined as follow:

There is sig relationship between predicted earnings per share (PEPS) and Tobin's Q Ratio.

In another words, zero hypotheses and research hypothesis are defined as follow:

H0: There is not sig relationship between predicted earnings per share (PEPS) and Tobin's Q

Ratio

H1: There is sig relationship between predicted earnings per share (PEPS) and Tobin's Q Ratio

Since both variables of predicted profit of each stock (PEPS) and Tobin's Q Ratio are

quantitative, correlation testing should be used to test this hypothesis after testing through SPSS

software, its output is in Tables 6 and 7..

Table 6. Results of second hypothesis testing by using Pearson correlation coefficient

Table 7. Results of second hypothesis testing by using Spearman correlation coefficient

Result of testing contains 2 above mentioned outputs. First one (table 6-4) indicates Pearson

coefficient, sig and data number. According to this output, since sig amount is less than 0/05. H0

hypothesis is rejected. And there is sig relationship between 2 variables. Correlation coefficient

of 728 data is 0/318.Second one indicates Spearman correlation coefficient, sig and data

number. Results of Spearman method are similar to results of Pearson method, but with a

difference that correlation coefficient of this method is 0/418. It is clear that both correlation

coefficients are sig at the 0/01 error level. So, first hypothesis is accepted. In another words, it

can be accepted that there is sig relationship between predicted profit of each stock (PEPS) and

Tobin's Q Ratio.

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5.6.3. Testing second subsidiary hypothesis of research

Second subsidiary hypothesis of research is defined as follow:

There is sig relationship between actual profit of each stock (EPS) and Tobin's Q Ratio.

In another words, zero and research hypothesis are defined as follow:

H0: There is sig relationship between earning per share (EPS) and Tobin's Q Ratio

H1: There is sig relationship between earning per share (EPS) and Tobin's Q Ratio

Since, both variables of earning per share (EPS) and Tobin's Q Ratio are quantitative with

distance ranges; correlation testing is used to test this hypothesis. After testing by using SPSS

software, its output is in Tables 8 and 9.

Table 8. Results of second hypothesis testing using Pearson correlation coefficient

Table 9. Results of second hypothesis testing using Spearman correlation coefficient

Result of testing is 2 above mentioned tables. First one indicates that Pearson correlation

coefficient, sig and data number. According to this output, since sig amount is less than 0.05, H0

hypothesis is rejected. And there is sig relationship between EPS and Tobin's Q Ratio.

Correlation coefficient of 728 data is 0.254. Second one indicates Spearman correlation

coefficient, sig and data number. Results of spearman method are similar to Pearson method but

with a difference that correlation coefficient of this method is 0.54. It is clear that both of

Pearson and Spearman are sig at 0.001 error level. According to this, second subsidiary

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hypothesis is accepted, in another words, it is accepted that there is sig relationship between

earning per share and QTobin ratio.

5.7. Other statistical findings

In addition to statistical description of research data and statistical testing of correlation

between main variables of research can be considered. Since main research variables include

Tobin's Q Ratio, information asymmetry, predicted earnings per share and actual profit of firms'

stock, correlation analysis can be done for Tobin's Q Ratio and information asymmetry during 4

years study. Table 10 indicates correlation coefficients between Tobin's Q Ratios of 2002-2005.

And Table 11 indicates correlation coefficients of information asymmetry of 2003-2005.

Table 10. Analyzing correlation of Tobin's Q Ratio for considered firms

As it is observed in above mentioned output, all correlation coefficient of Tobin's Q Ratio of

considered firm during 4 years is positive (direct correlation). All coefficients are sig at 0/01

and 0/05 error level except correlations of 2002-2005. The strongest correlation is 0/856 for

2004 and 2005 and the weakest correlation is 0/115 for 2002-2005.

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Table 11. Analyzing information asymmetry correlation for considered firms

Above output indicates correlation analysis of information asymmetry of considered firm

during 4 years study. It is clear that information asymmetry correlation is diverse during 2002-

2004 and 2002-2005, and it is positive and direct during 2002-2003, 2003-2004, 2003-2005. On

the other hand, correlation coefficient is sig at 0/01 error level in 2002 and 2003 and 2004 and

2005. The strongest correlation is 0/93 in 2004 and 2005. The weakest one is 0/044 in 2002 and

2005.

5. Conclusion

Present research considers existence or non existence of relationship between information

asymmetry and Tobin's Q Ratio. Testing the hypothesis is done using Pearson correlation

coefficient. And confirming results is done using Spearman correlation coefficient. In

hypothesis testing, basic hypothesis wasn’t confirmed, i.e. there wasn’t sig relationship between

changes of information asymmetry level, Tobin's Q Ratio. Following results can justify reason

of non existence of relationship:

1) Book value of firm is one of the sufficient criteria to calculate QTobin in Iran. This criterion

has not observed sig relationship in domestic done researches, book value with stock price. On

the other hand, ignoring inflation factor can dominate amount of calculated book value which

has had more and sig effects in Iran.

2) Information asymmetry rate is quantitative and it cannot be evaluated through calculating

changes of predicted and actual profit. So to access to certain criterion of evaluating

information asymmetry, more researches are required.

Subsidiary hypothesis is confirmed by statistical tests. There is sig relationship between

predicted profit (PEPS), actual profit (EPS) and Tobin's Q Ratio.

One of the evaluation methods of firms’ performance is through capitalists. From the point of

view of capitalists, a firm which has more actual and regular profit in a year, has better

performance, so stock price of such firm will be increased and directly leads to increase of

Tobin's Q Ratio.

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If there is little difference between predicted and actual profit, it is indicated that there is no

existence of information asymmetry or equal distribution of information. So capitalist is relaxed

in transaction of stock which leads to stock boom and increase of its price in market.

Increasing EPS →increasing stock price →increasing Tobin's Q Ratio

Decreasing information asymmetry →increasing stock price →increasing

QTobin

At the end, it should be mentioned that other important factors such as economic status,

changing profit division policy, kind of industry, inflation rate, are effective for market

efficiency and effective stock price. And mentioned factors should be considered.

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