Study of Relation between Market Efficiency and Stock Efficiency of Accepted Firms in Tehran Stock Exchange for Manufacturing of Basic Metals

Transcription

1 2013, World of Researches Publication ISSN Am. J. Life. Sci. Res. Vol. 1, Issue 4, , 2013 American Journal of Life Science Researches Study of Relation between Market Efficiency and Stock Efficiency of Accepted Firms in Tehran Stock Exchange for Manufacturing of Basic Metals Mohammad Hamed Khan Mohammadi, Hamid Reza Kourdloee and Nasir Hatami Maskoni * Islamic Azad University, Qeshm International Branch, Qeshm, Iran *Corresponding Author: Abstract: Aim of presented study is to discuss relation between market efficiency and stock efficiency of accepted firms in Tehran stock exchange for manufacturing of basic metals during Investors, analysts and stockbrokers can use the results of this study in their financial decisions and the stock returns of each of the companies and finally choosing the most efficient share regarding risks. The results show a significant relationship between discussed independent variable and the dependent variable. Relationship between market efficiency factors and efficiency of firms operating in the manufacturing of basic metals is a direct relationship. Key words: Market Efficiency, Stock Efficiency. INTRODUCTION The most important objectives of businesses, gain profits in the short term and increase economic wealth of owners in the long-term, this will be possible by logical decision making in the investment process, logical decision making has a direct connection with the performance evaluation of business and also assessing performance of businesses needs knowledge of criterions and indexes. There are several criteria for evaluating the performance of economic which regarding to economic concepts they will be divided into two categories: accounting concepts and economic concepts. In accounting criteria, company s performance will be evaluated by accounting data and they belongs to criteria that simple calculation of the criteria and potential investment with regard to the rate of efficiency and cost of capital is estimated, so that computational complexity is so great. In the present paper which is the result of study and research, studies the relationship between market efficiency and stock efficiency of firms operating in the 136

2 Study of Relation between Market Efficiency manufacturing of basic metals. Common models for forecasting stock efficiency include capital asset pricing model, the market model, the arbitrage pricing theory and factor model. Experimental studies that have been conducted in different countries regarding effective factors on stock efficiency show there are many factors that can anticipate stock efficiency more accurately. Some of these variables include market efficiency to firm size, book value to market value ratio, financial leverage and price to profit ratio 1. This study aimed to identify and evaluate variable role of market efficiency on determining stock efficiency of firms operating in the metal industry in the Tehran Stock Exchange. However if much more research in this area will be done accuracy of defined criteria will be greater and therefore accuracy of investment decisions will increase. In case of investigating several variables, the results can be a guide for investors and analysts to consider which variables more and which variables are not of enough significant. Moreover, experimental evidences on future theoretical information about effects of discussed factors on stock efficiency are important 2. Theoretical Basis & Research Background Index of stock prices in financial markets in all over the world, as one of the most important criteria for measuring performance as security are of great importance and attention. Perhaps the most important reason for the widespread interest is that indexes are obtained from aggregate stock price movements of all companies or any classes of companies in the stock market and therefore make it possible to study orientation and size of price movements in the stock market. In fact, development of financial theories and innovation in the last two decades, based on the central role of the market in general, with increasing trend has been accompanied calculating and investigating such indexes. Measuring of the market movements for several reasons is useful and important. Basis for evaluating the performance of professional investment managers; Establish and supervision on investment funds based on index; Measure market efficiency rates in economic studies; Predict the future movements of the market (by technical analysts); An index for the market portfolio of risky assets, when calculating the systematic risk of assets. Hassan ET al. 1 used a multiple model consists of Markov, ANN model and genetic algorithm to forecast market efficiency. This model that was applied to predict stock efficiency proved that multiple models are better than simulation models and act better in anticipating market efficiency. Hamzacebi ET al. 2 compared ARIMA and ANN methods and they concluded that direct predicting of neural network is more applicable in the reality. But it was clear that additional studies are needed before generalizing the results of this study. These baskets showed sectional variations in efficiency and risk. Also the baskets were classified based on size B / E ratio of firm. It turned out that the

3 Khan Mohammadi et al., 2013 regression based on time-series may be sensitive to the ways that baskets have been shaped. To monitor changes in the market value which is related to risk and future efficiency, firm size baskets are useful. Also baskets based on book value to market value ratio have been used to examine how expected efficiency and risk of a bad financial situation or high B / E ratio change during test time. The results show that the ratio of book value to market value only with other variables such as beta has explanatory power for future efficiency. Humpet al. 3 on a research about Macroeconomic variables effect on market efficiency, they studied long-term relationship between industrial production, consumer price index, money supply, short-term prices and long-term interest rates and stock prices in the markets of America and Japan comparatively using Social Analysis. The results indicated a positive relationship between industrial production, consumer price index and short-term interest rates, a negative relationship for the long-term interest rates in the America market. Industrial production in the Japanese market had a smaller positive coefficient compare to America, while the consumer price index coefficient in Japan was higher than in America. In general, the results with the theory that future changes in production efficiency have impact on current cash flows and company s future and they have a positive effect on the market. Kardag 4 reviewed both single-regime Garchmodel and Markov s rotational arch model for Turkish stock market. Then by using different loss functions predicted the fluctuations of the two methods and studied out-of-sample forecasts. The results revealed that these two models predict market moves well. MATERIALS AND METHODS Hypotheses to explain the dual methods in management researches including the use of statistical and non-statistical techniques such as research in operation, this study was non-experimental survey and it is included in the first group. The aim of the research is based on the transactional research. Subject area is reviewing the relationship between market efficiency and stock efficiency of firms operating in the manufacturing of basic metals. In terms of place, area of this research includes confirmed companies in stock exchange that manufacture basic metals. The time period of this study includes a seven-year period from beginning of October 2005 until the end of October This study is based on real data of stock market. In this study, required data are obtained from a direct interpretation of financial statement information by processor resource database and the stock exchange website ( all data for hypothesis testing is collected. In accordance with the requirements of data analysis, multivariate linear regression models were used and for data analysis, Aspasia s software was used. Collecting materials 138

4 Study of Relation between Market Efficiency The data that will be used in this study will be obtained from secondary documentation model (documents review) such as official statistics from the financial statements issued by statistical companies and the information contained in Tehran Stock Exchange, documents and accounting information and reports of firm performance. Methods and materials for data analysis Since the aim of this study was to investigate the influence of independent variables on the dependent variable, therefore, the most appropriate method for analyzing the data using is "multivariate regression". In this research, the following hypothesis will be tested: There is no relationship between market efficiency and stock returns of firms that manufacture basic metals. H 0 = 0 There is a relationship between market efficiency and stock returns of firms that manufacture basic metals. H 1 0 Research variables Study variables included dependent, independent and control variables, the dependent variable is "Stock efficiency of firms in manufacturing basic metals ", and the independent variables are presented. Factors affecting stock returns of companies operating in the manufacturing of basic metals are as follows: 1. Market efficiency Average daily efficiency of stock price index 2. Book value to market daily value ratio Total salaries of shareholders Number of issued ordinary shares Market value of firm 3. Price to income ratio Price per share Latest predicted profit per share 4. Size of firm Market value 5. Financial Leverage Total debts of the firm Total assets of the company Operational definition of variables and their assessments Research variables The model used to study the relationship between market efficiency and stock efficiency of firms operating in manufacturing basic metals: Rit = α + β1t RM + β2t ME + β3t BE/ME + β4t FL + β5t P/E + Dependent variable: Rit

5 Khan Mohammadi et al., 2013 Stock efficiency of firms in the manufacturing of basic metals Stock returns of firm are obtained by the formula: R it = [(D it + P it )(1+ +β] (P it 1 + C ) P it + C Rit = efficiency rate of company share in period t Pit = Company's share price at end of period Pit -1 = Share price at the beginning of period Diet = Ownership interests of the company s share in period t α = Percentage of capital increase from receivables and cash β = Percent increase in capital reserves C = Paid nominal amount of capital increases from cash and receivables Independent variable Market efficiency: RM In this study, Tehran Stock Exchange Index has been used as the market efficiency. RM = stock index at the begining of period stock index at the end of period stock index at the begining of period Control variables Size of company: ME In this study, because the inflationary will affect total assets of the company, and the book value of total assets has a considerable difference with their market values, in order to measure the size of company, market value is used. In this study, we refer to total stock market size of the company as size of company which is obtained from number of shares on the last price (P) and the total number of shares issued for each company in each of the years 2005 to 2011, as regards to size of company which is much larger than that of the other variables, we take logarithms. Book value per share: BE Book value of shares is net assets of the company. Company's net assets are the difference between assets and debts of the company. Book value per share indicates that how much is the capitals per share based on book prices for shareholders. In other words, the book value per share represents the amount of capital used in the firm based on book amounts; book value per share is calculated as follows: book value per share = Book value to market value ratio: BE/ME total salaries of sharholders number of issued common shares 140

6 Study of Relation between Market Efficiency The book value to stock market value ratio as one of the four control variables is calculated as follows. At first, the market value of the Company's common stock is determined using the latest balance sheet data, then market value by multiplying the latest price of common shares to number of issued stocks will be determined, to homogenize these variables, book value and the market value of a company is calculated. Then the book value of salaries of shareholders is divided by its market value. book value to market value = book value od common share of company market value of company Financial Leverage: FL For company s financial leverage following formula is used: TD: total debts of company i in year t TA: total assets of company i in year t This formula is the capital index and indicates that how much debt is used to finance a company's assets. Price to earnings ratio: P/E This ratio which is also named as a profitability coefficient, obtained by dividing the share price by its earnings and in fact shows the relationship between the stock prices of a company with its profit, in this research, earnings per share is last projected earnings per share after tax deduction. Statistical population The statistical population consists of a number of desirable elements that have at least one characteristic trait. Characteristic trait is a trait that is shared among all elements of the statistical population and distinct the population from other communities. According to the above explanation, statistical population in this study is all companies operating in the manufacturing of basic metals from to that it was their first attempt to offer their stocks in conditions as: 1. Before 2005 were accepted in Tehran Stock Exchange and they were out of stock boards until the end of Between 2005 until the end of 2011 their stock to be traded at least once per year. 3. Book value of shareholders salaries was not negative in Due to the above requirements of the companies who were operating in manufacturing of basic metals, 17 companies were selected. SEPANTA Calcimine Kasha Amirkabir Steel

7 Khan Mohammadi et al., 2013 Rolling and Production of Steel Parts Pipe & Machine Making Ferrosilicon Sepahan Industrial Group Iran Aluminum National Led and Zinc Mineral Processing Aluminum Rod SADID Industrial Taka Investment Calumet Navard Aluminum Sadid Pipe and Equipment Shahid Bahonar Copper Industries Used statistical methods In this study, at first a statistical sample of the statistical population from listed companies in Tehran Stock Exchange under the terms of the attributes that were listed in the community sample, was selected and then in order to assumptions calculations and to test them SPSS software was used. Statistical methods used in this study are regression descriptive statistics, correlation, F-test, (F.TEST) T-test (T.TEST) and Durbin and Watson test. Approximate size of sample Using a systematic approach used in determining the statistical population, the entire statistical population is as research sample, in other words, members of statistical population and research sample are the same and therefore the total size includes 17 companies listed in Tehran Stock Exchange for companies that have met the above conditions. Research hypothesis The aim of this study was to study the relationship between market efficiency and stock returns in companies that manufacture basic metals and are listed on the Tehran Stock Exchange. This goal is accomplished by testing the following hypothesis. There is a relationship between market efficiency and stock returns of firms that manufacture basic metals. Research questions The main research question that arises is as follows: What is the relationship between market efficiency and stock returns of firms that manufacture basic metals? RESULTS Descriptive statistics The first step in analyzing data is calculating descriptive statistics of the data used in this study, the data that is used in the estimation have been selected from 142

8 Study of Relation between Market Efficiency exchange information on a series of 17 companies participating in the construction industry of basic metals. Table 1 lists the companies used in this study. SEPANTA Rolling and Production of Steel Parts Pipe & Machine Making Ferrosilicon Sepahan Industrial Group Table 1. List of reviewed companies Calcimine Kashan Amirkabir Steel Iran Aluminum SADID Industrial National Lead and Zinc Mineral Processing Aluminum Rod Taka Investment Alumtek Navard Aluminum Sadid Pipe and Equipment Shahid Bahonar Copper Industries Characteristics of collected data which includes market efficiency, firm size, book value to market value ratio, financial leverage, and earnings-price ratio are presented in table 2. Descriptive statistics are presented for the sample of 17 companies and in the 7-year period. Description Market Efficiency Size Logarithm Book Value to Market Value Financial Leverage Price to Earnings Stock Efficiency Table 2. Descriptive statistics of research variables Minimum Maximum Median Mean SD Model estimation As mentioned earlier in this study, the aim of this study is to evaluate and test the hypothesis. This hypothesis is as follows: Hypothesis: There is a relationship between market efficiency and stock returns of firms that manufacture basic metals. To test the hypotheses and check each of them, multiple regressions is used. The following regression equation is estimated using multivariate regression: R = α +β RM + β ME + β BE/ME + β FL + β P/E + In this model, an independent variable, market efficiency, and 4 control variables, firm size, book value to market value ratio, financial leverage and priceto-earnings ratio is used. The dependent variable is firm performance which is estimated using multivariate regression model, the regression equation.

9 Khan Mohammadi et al., 2013 Research independent variables Correlation test To investigate the relationship between the independent and dependent variable, correlation analysis is used. In this analysis, the correlation relationships between the independent and dependent variables are discussed and reviewed. The purpose of the test is to find correlations between independent variables and diagnosis of significant variables. Among the various methods for calculating the correlation coefficient between the two variables, moment correlation (Pearson) has less error and the most commonly it is used. In this study, Pearson correlation coefficient between the dependent variable and each of the independent variables were calculated for the entire period, the results are indicated in Table 3. In table (3) research variable correlation regarding to entire data based on years of company is displayed. Given correlation coefficients indicate higher correlation between size of the company and company stock efficiency. There is also a significant correlation between financial leverage and book value to market value ratio. According to the above table, results show that market efficiency in entire period has a direct relation with the efficiency of stock market, it means, the increase (decrease) in market efficiency increase (decrease) stock efficiency. Table 3. Pearson Correlation coefficient Variables Company Stock Efficiency Market Efficiency Firm Size Book value to market Value Ratio Price to Earnings Ratio Financial Leverage Stock Efficiency Market Efficiency Firm Size Book value to market Value Ratio Price to Earnings Ratio / Financial Leverage / Hypothesis test results of research After Correlation test to determine the mathematical relationship between each of research independent variables with model dependent variable, value model using multiple regression procedure is done, in this section hypothesis has been tested. Hypothesis testing results 144

10 Study of Relation between Market Efficiency R = α + β1 RM + β2 ME + β3 BE/ME + β4 FL + β5 P/E + Table 4. Test results concerning the relationship between stock market efficiency of firms engaged in manufacturing of basic metals Variable name Coefficient Standard Error T-statistics Probability Constant value Market efficiency Size of company Book value to market value Financial Leverage Price to Earnings Correlation coefficient R 0.475a Coefficient of determination R Adjusted coefficient of determination Durbin- Watson statistic Standard error of regression Statistics F Probability of statistic F The results show that between market efficiency and stock returns of company there is relationship (positive) Regarding to variable coefficient , it is indicate that there is a direct correlation between the market efficiency variables and the dependent variable. If a unit is added to the stock returns, market efficiency will increase up to units. Adjusted coefficient of determination in this study is This tells us that the independent variables in the model explain 191% of the variability in the dependent variable. Based on statistic test t of Student, market efficiency has a significant effect on stock returns. In estimating the multivariate regression model, in addition to the coefficient significance test, the overall regression model significance is tested by statistic F. where in this model F= (P=0.000) presents significance of overall regression in level 99%. The coefficient of determination R 2 = shows that in stock returns can be explained by the independent variables mentioned in the study, other changes are affected by other factors. P value for the beta coefficient of the market efficiency is This value is significant at the 10% significance level. So we cannot accept the null hypothesis. In other words, we can argue that there is a significant positive relationship between market return and stock efficiency of companies operating in the manufacturing of basic metals.

11 Khan Mohammadi et al., 2013 Since Durbin- Watson statistic is near two (1.89), it shows that there is no problem of autocorrelation. Entering the control variables indicates that only firm size variable has positive and significant effect on firm performance. As you can see in Table 4, coefficients and t-statistics of variable for company size is and that indicate the significant and positive relationship between firm size and stock return of sample companies. In other words, the larger the size of the company, stock returns of it will be more. The variable coefficients of book value to market value and t-statistic indicates a negative relationship between this ratio and stock returns that regards to significant level of this variable, this relationship is significant at the 95 percent of confidence level. As you can see based on the company's financial leverage variable, there is a negative relationship between financial leverage and stock returns, but this relationship is not statistically significant, this means that financial leverage has no effect on stock returns. Meanwhile, the variable E / P as financial leverage shows a negative relationship, but this relationship is not statistically significant. DISCUSSION Since the aim of this study was to study the influence of independent variables on the dependent variable in period between years 84 to 90 over 17 companies that are listed in Tehran Stock Exchange for the manufacturing of basic metals, so regression analysis was used to test the hypotheses; before examining the relationship between dependent and independent variables it was necessary to ensure that distribution of the data is normal. The results of the Kolmogorov - Smirnov (KS) test represents the normal distribution 5. Then, using multiple regressions, variables were examined; as a result hypothesis of the relationship between market efficiency and stock efficiency of companies engaged in manufacturing of basic metals were tested. Test results are given in Table 4. In order to test the above hypothesis, the t test was used. Therefore, t table (critical values) with 99% reliability, when 0.01 = α (the probability of error 1%) it will be compared with the test statistic t, the critical value of the test with error level of 0.01 is Since the test statistic 0.01 is not in the critical region and its value is greater than the critical value, the research hypothesis is confirmed. Overall, the results of the regression analysis revealed that the relationship between market efficiency and company efficiency in 99 percent level, is a significant relation and there is a relationship between these two variables which among the control variables, only firm size is positively and significantly related to stock efficiency and the ratio of book value to market value have significant and negative correlation with stock efficiency and two other control variables, the financial leverage and ratio of book value to market value have no significant relationship with stock 146

12 Study of Relation between Market Efficiency efficiency. Thus the efficiency of market is of factors that affect the efficiency of the company and based on figure 4, it has a direct relationship with stock efficiency of company. Study restrictions Like other studies, this study had some limitations that make the general inability of the results difficult, some of the restrictions include: 1. Limited period of investigation 2. Lack of reviewing other financial relations 3. Indiscriminate increase of prices in the whole year of research, followed by rise of stock efficiency, results may be affected by changes in economic conditions Suggestions based on research results Investors, analysts and other stakeholders are recommended to pay more attention to the Stock Exchange General Index of Securities and consider it into their decision-making models. As the results show, an increase in market efficiency, stock efficiency increases. Due to the impact market efficiency, understanding the factors that influence market efficiency and models to predict the movement of total stock market index help in buying and selling shares of companies engaged in manufacturing of basic metals (One of the most efficient industry in the Tehran Stock Exchange), investors need to pay close attention to this issue. In other words, investors should keep in mind the fact that when investing in stocks consider components and factors affecting the efficiency of the market as a direct impact on stock efficiency. Since changes in these factors, stock efficiency will also have direct changes. Suggestions for future researches 1. Review the relationship between stock efficiency and market yields using another model. 2. The impact of market efficiency, stock efficiency in other industries. 3. In this study to test the hypothesis, the data for the period from 90 to 84 is used; it is suggested, in a similar study using data from different time periods. 4. It is suggested to calculate market efficiency, in addition to total index of stock exchange from other criteria, such as price indexes and total cash efficiency and also the index of 50 companies that are more active, to be used. 5. In this study, the market efficiency is calculated as annual efficiency; consequently, stock efficiency is calculated on a yearly basis. For a more detailed review the monthly market efficiency and monthly stock efficiency are used. REFERENCES

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