Australian Journal of Basic and Applied Sciences, 5(12): 1926-1933, 2011 ISSN 1991-8178

The Role of The Economic Value Added Measure and Intellectual Capital In Financial Intermediations Market Value In Stock Exchange (Tse)

1Shokufeh Etebar, 2Roya Darabi

1Sama Technical and Vocational Training College, Islamic Azad University, Karaj Branch, Karaj, . 2Department of Accounting and Management, Islamic Azad University, South Tehran Branch, Tehran, Iran.

Abstract: Firms' values are result in financial capital value and intellectual capital. Despite the importance of intellectual capital, by the principles of accounting but also, intellectual capital used in companies in the financial reporting of Iran are not presented. Goals research is review Evaluation of corporate valuation and study the effect of EVA, residual earning calculated by accounting standards and component of IC in market value of firms. The population of the financial intermediation industry with 25 companies in Iran, About 21 companies in the group Banks, credit institutions and other financial institutions, other financial intermediation, investment and monetary intermediation in Models were tested in the study, the results at the confidence level of 95%, indicate that: There is no significant difference between research models, for the capacities to explain variations in firms' market value, if the proxy variable of intellectual capital is not added. The capacity of residual income calculated by EVA to explain variations in a firm's market value will be significantly greater than residual income calculated by generally accepted accounting principle of Iran to explain variations in a firm's market value if the proxy variable of intellectual capital is added.

Key words: economic value added, intellectual capital, market value of financial intermediations, (TSE).

INTRODUCTION

The participants in capital markets are deeply concerned with the performance and valuation of firms. The development of the knowledge economy coupled with rising globalization, market liberalization and increased competition has pushed many firms to invest in innovation and in value creation activities, such as research and development, manpower training, new technology acquisition or advertisement, etc. in order to sustain their leadership in the market. However, intangible assets that result from these values added investments. Such as brand loyalty, human resources, sales channels, etc, are seldom recognized in balance sheets. Under current Generally Accepted Accounting Principle (GAAP) much of those expenditure are immediately expensed, since their economic benefits are highly uncertain and are difficult to measure. Such accounting procedures cause traditional accounting measurements to deviate from the real economic situation and consequently to reduce the usefulness of the information provided by such financial statements (Lev and Zarowin, 1999; Bradley, 1997). Found that many firms which engage heavily in knowledge- based innovation activities tend to have clear gaps or differences between their book values and their market values. Ohelson (1995) proposed a residual income valuation model, in which the market value of a firm can be determined by its book value, by the discounted value of its expected future abnormal earning and other information. Some accounting items in the financial statements are adjusted to present the firms whole economic value and shareholders value is increased only after its earnings exceed its cost of capital. Roos et al. (1998) argued that a value of firm is determined by its traditional physical capital, its financial capital and its intangible intellectual capital. Lev (2001) suggested that the physical and financial assets of firm can only generate normal Earnings; abnormal earnings are created through the development of intangible assets. Lev stated that if the intellectual capital of knowledge- intensive firms is not properly accounted for in the financial statements, their cost of capital will be over charged and their value systematically undervalued, which will hinder the investment and growth of those firms. In research, the valuation model used or employed will adjust accounting earnings for equivalent equity reserves and for the cost of equity capital. This means that we will, in effect, be using EVA to reflect the economic value of the firm.

Corresponding Author: Shokufeh Etebar, Sama Technical and Vocational Training College, Islamic Azad University, Karaj Branch E-mail: [email protected] 1926 Aust. J. Basic & Appl. Sci., 5(12): 1926-1933, 2011

Literature Review: Since (Ball and Brown, 1968; Beaver, 1968) emphases for usefulness accounting information to investors in the capital market. Prior research results generally find accounting earnings are positively related to stock returns. But Lev and Zarowin (1990) found that the usefulness of financial information has been decreasing in the past, the main reason they argue being that financial information cannot fully reflect major changes in a firms operating activities. Lehn and makhija (1996) and Mouritsen1998 asserted where capital is derived from adjusting certain items on the balance sheet to more closely reflect the real cash flows invested. Firm risk and value creation ability of the firm better than the accounting earnings. Chen and dod (1997) investigation, showed that accounting measurements are still in the process of holding companies with the importance and EVA, more information than the operating profits in the evaluation of the firms, does not provide. Donnell et al. (2003) adopted a case study approach to measure how much value firms place on intellectual capital. In the research Huang and Wang (2008), result show residual income based on eva is no better than that based on current GAAP in capacity to explain variations in a firm's market value. And intellectual capital does provide incremental information for the evaluation of stocks. The study jHv H de Wet (2004) found stronger relationship between market value added and cash flow from operations. Result does not to superior to traditional accounting measure (EVA) in driving shareholder value. The EVA of a company is currently acknowledged as a single, most appropriate internal measure of corporate financial performance. Those studies investigate how existing management accounting and financial management techniques can be adjusted to incorporate the EVA Perspective. It also applies these adjusted techniques to a company listed on the JSE securities exchange south Africa. (JHv H de Wet and FJ de Hart, 2010). The purpose of study Chen et al. (2005) is to investigate empirically the relation between the value creation efficiency and firms' market valuation and financial performance. The result extend the understanding of the role of intellectual capital in creating corporate value and building sustainable advantages for companies in emerging economies, where difficult technological advancements may bring different implications for valuation of intellectual capital. Also, JH de Wet and JH Hall (2011) evaluate with combining a variable costing approach with leverage analysis and value analysis opens up new opportunities to investigate the effect of certain decisions on the MVA and the share price of a company with a spreadsheet model to illustrate what the relationship between EVA, MVA and leverage and to determine what impact changes in any variable like sales or costs will have on the wealth of shareholders. Kalyta (2010) investigate impact on measure of firm value in the sample of 3667 public U.S, firm consistent with the prediction, the number of directors-scientists has a positive impact on the firms Q and stock returns in knowledge-intensive sectors. Appointing a scientist to the board raises the stock price in a three- day window around the nomination announcement by 1% and leads to abnormal returns of 2.5% over the 12-month post-event period.

The Relationship Between Intellectual Capital and Economic Value Added: Therefore, the effect of intangible assets (intellectual capital) and economic value added on the market value of firms in various industries including financial intermediation industry, for regard to affect that have EVA and IC on the market value of the organizations. Research in mind, will be necessary with review the role and necessity reporting EVA and IC criteria, that in the traditional reporting in Iran and are not presented in the form of financial statements.

Research Goals: 1. Models to evaluate the company's value, by three factors: Book value, Economic value added, Intellectual capital is determined. 2. The Accuracy of the value calculated by the accounting book value and earnings under accounting standards Iran is measured. 3. Ability or Power residual income calculated by the measure EVA with Ability or Power residual income calculated by accounting standard of Iran, in predicting or explain the difference in market value is compared. 4. Assessing improve the provision of information about intellectual capital reflected in the financial statements by listed companies in Tehran Securities and Exchange Commission 5. Assessing the impact of knowledge management and intellectual capital on firms' value.

1927 Aust. J. Basic & Appl. Sci., 5(12): 1926-1933, 2011

Hypotheses Development: Today, more intangible assets will be considered by investors. Bose (2008) Intellectual capital is appeared an important value driver in today s organizations as business and economy. Evidence shows that the drivers of value creation in modern competitive environments lie in a firms IC rather than its physical and financial capital. It has resulted in an accounting "vacuum" as traditional accounting methods prove unable to quantify knowledge based products and service in the financial statements (Abeysekera, 2000). Although traditional accounting measurement has ignored these products, the market does factor the value of such equity into the market price of the economy. Without intellectual capital information the capital market shows inefficiency and this inefficiency results in an uncertainty premium those investors require in order to convincing them to invest in a business that is difficult in respect of information on its intellectual capital. A direct consequence of this lack of transparency is an increased cost of capital. This leads to lower investment and growth .Continued this theme by noting that absence of intellectual capital information is likely to make stock prices more volatile. Such volatility creates uncertainty that increases the spread in bid versus ask prices (Zaman Khan and Kayeser, 2008). Usefulness of financial statements prepared on the basis of historical cost and the accuracy and value of information in the financial statements of 1996 and 1997 was the challenge facing business units. In fact, traditional reporting can not measure the true value of their companies and to measure the current financial balance and tangible assets are sufficient (Donnell, 2004).

Main Hypothesis: Whether the accounting information derived from EVA is more relevant than that derived from accounting earnings by GAAP of Iran? Therefore are proposed below Hypothesizes for basis Huang and Wang (2008) research.

Sub Hypothesis: H1: There is no significant difference between the capacities to explain variations in firms market value of residual income calculated by EVA or by generally accepted accounting principle of Iran accounting earnings. H2: The capacity of residual income calculated by generally accepted accounting principle of Iran to explain variations in a firm's market value will be significantly greater if the proxy variable of intellectual capital is added. Economic value added, is performance evaluation criteria that will attempt to correctly calculate the cost of capital. Intellectual capital is still in its place as the intangible assets of firms value is not. H3: The capacity of residual income calculated by EVA to explain variations in a firm's market value will be significantly greater if the proxy variable of intellectual capital is added.

Sample and Data: Given the importance of financial intermediation industry in the economic activity of active companies in Tehran Securities and Exchange Commission and with contemplate a different financial structure of the industry than other industries, also existence of the EVA measure in the research model, which is essential for shareholders in assessing investing rate of return. So elect this industry is appropriate as research population. The Statistical Pupulation in in this study includes the accepted companies in Tehran Stock Exchange in the period of 2003 to 2010. With selected by purposive sampling method, sample below, 21 companies were selected from 28 companies that are active in the financial intermediation industry. 1. Group bank and credit institutions (bank of new economy, Persian, kar afarin, sina) 2. other financial intermediation (rayan , Iran leasing, ghadir car leasing, industry and mining leasing) 3. Investments (Damavand future Investments, bahman Investments, boali Investments, Iran industrial development Investments, Investments in national development, sepah Investments, industry Investments, industry and mining Investments, Iran behshar industry group Investments, Iran national Investments, niro Investments, melat Investments) 4. monetary intermediation (melat bank).

Restrict of availability of sample and data companies: Completed due to lake of databases and related sites Tehran stock exchange, access to the financial statements ansar bank, commerce bank and , Iran saderat bank in Tehran stock exchange has been accepted, not available

Research Design: Measurement of the dependent and independent variables research: EVA as a performance evaluation measure which defines performance as being net operating profit after taxes less the cost of capital of both equity and debt employed to produce those profits. The formula is as follows:

1928 Aust. J. Basic & Appl. Sci., 5(12): 1926-1933, 2011

EVA = (Return on Invested Capital – Cost of Capital)*Invested Capital = (Return on Invested Capital – Cost of Capital)*(Stockholders equity – interest –bearing debt- equivalent equity reserve) Definition and the expected sign of the Variables research of their relation with firm value are given in table1.

Table 1: Measurement of the Research variables. Research variable Code Definition Availability name in Iran Market value of the equity per Pt Market value of the stock per share at the end of t term available share (dependent variable) Book Value per share BVt Book Value of the equity per share at t term available Accounting residual earning per EPSRt Accounting residual earning per share for t term EPSRt= available share EPS t – (Book value of the equity per share at the beginning of t term *shareholders essential rate of return) EVA per share EVA t The Economic value added per share for t term available Operating revenue per staff REPt Net operating revenue/the quantity of staff for t term available (Human capital) Marketing expenses per share SPt The Marketing expenses/number of share of stock of stock available (customer capital) of weighted average in outside for t term Growth of operating revenue RGt operating revenue for t term- operating revenue for t-1 available (customer capital) term)/operating revenue for t-1 term( Research and Develop RDPt The research and development expenditure of the operating Available not expenditure ratio (Innovative expense and manufacturing expense/Net operating revenue capital) for t term Administrative expenses per MEt Administrative expenses for t term/ the quantity of staff for available staff (procedure capital) t term Stable degree of organization OSt The years of firm since beginning at the end of t term available (procedure capital)

Methodology: This study is an correlation and regression research. In terms of purpose, this study is applied research that its results can be useful for extensive range of users including stockholders, analysis and Tehran Stock Exchange and standard setters and intensive range of users including managements, accountants for the provide financial statements. Companies' information collected through the Stock Exchange official website and then data analyzed by the software SPSS 16.

Empirical Model: The firm valuation model in this research is as fallows:

Model 1: Pt = a0 + a1 BVt + a2 Xt + Et Xt = Accounting residual earning per share or EVA per share

Model 2: Pt = a0 + a1 BVt + a2 Xt + a3 REPt + a4 SPt + a5 RGt + a6 RDPt + a7 MEt + a8 OSt + ET Model 2, including the proxy variables of intellectual capital that added with Model 1

Regression Result: Result Analysis for one-Sample One- Kolmogorov-Smirnov Test One-Kolmogorov-Smirnov Test: Zero hypothesis: market value of the equity per share is normal. Polar hypothesis: Market value of the equity per share is not normal. Kolmogrov-smirnoff test analysis results, in the level of 21 companies shows that Significance greater than 5% is obtained And, therefore, Polar hypothesis, which states that the market value equity per share are not normal, Is rejected and Zero hypothesis based on the market value of the equity per share is normal, will be accepted. Summary results of the test statistic, with 21 sample companies, are presented in Table 2. So the test results Kolmogrov- Smirnoff regression models research, are reliable and have the required validity for the performance testing the multiple linear regression and regression analysis using analysis of variance.

Result Analysis for Model 1: The estimated variance inflator Factor (VIF) of each variable in regression model 1 and model 2 was between 1/001 and 6/752. Indicate in that, there is no serious collinearity among the research variables in this regression models. Result analysis for model 2 Comparing the results shown in table 3 and table 6, it can be concluded that, from 21 tested firms for first model, independent variables in the first regression model for 10 firms, explanation ability or predictive power have a market value of the company. The results showed that, for the first hypothesis test and the 95% confidence level Model 1, there is no significant difference between the

1929 Aust. J. Basic & Appl. Sci., 5(12): 1926-1933, 2011 capacities to explain variations in firms' market value of residual income calculated by EVA or by generally accepted accounting principle of Iran accounting earnings, for market value of financial intermediation firms. In other words, there is no difference between the capacities to explain model 1 for explanation market value tested firms, in this research. Explanatory power of the first model Variable based on Eva 47/61% and 47/61 % is also based on the variable epsr.

Table 2: Result for one-sample One- Kolmogorov-Smirnov Test. Kolmogorov- Asymp. Sig. Name of firm Mean Std. Deviation Smirnov Z (2-tailed) bank of new economy 3,774.3 2,058.8 .948 .330 Iran leasing 2,693.5 1,739.6 .692 .724 ghadir car leasing 2,363.3 2,388.9 .957 .319 industry and mining leasing 1,976.3 577.6 .718 .682 rayan saipa leasing 3,652.6 4,039.1 1.941 .338 Persian bank 2,563.7 1,266.3 .641 .806 kar afarin bank 4,830.6 3,299.6 .938 .343 melat bank 1,933.7 1,593.7 7.048 .631 sina bank 1,769.6 745.8 .600 .864 boali Investments 1,143.7 787.4 1.006 .264 melat Investments 891.2 616.5 7.764 .603 niro Investments 1,227.0 519.7 .676 .751 bahman Investments 1,568.2 1,029.0 1.187 .120 Damavand future Investments 1,389.0 854.0 .865 .443 Iran behshar industry group Investments 1,681.1 1,164.3 .641 .805 Iran industrial development Investments 1,127.2 411.7 .445 .989 sepah Investments 1,474.6 818.3 .870 .436 insurance industry Investments 1,239.3 644.6 .763 .605 Iran national Investments 2,199.5 2,328.1 .952 .325 industry and mining Investments 1,724.5 1,390.1 .724 .670 2,580.7 2,272.4 .682 .740

Table 3: Regression model 1 with Economic value added per share criteria. Name of firm Constant (a0) Beta Beta (Xt) sig Adjusted R2 vif (BV) Is EVA (F test) bank of new economy .465 . 412 -.856 0.432 -.736 1.051 Iran leasing 67.51 0.854 .060 040 .577 1.136 ghadir car leasing -11.85 1.004 .018 .000 .971 2.437 industry and mining leasing 8. 56 .517 -.242 .027 .767 1.112 rayan saipa leasing 13.77 .936 -.119 .001 .927 1.069 Persian bank 34.92 .384 -.010 .668 -.191 1.045 kar afarin bank 51.62 .178 -.317 .634 -.167 1.107 melat bank 34.87 .901 -.115 .001 .903 1.338 sina bank 66.31 .342 -.160 .590 -.133 1.234 boali Investments -19.85 .491 -.090 .452 -.019 1.071 melat Investments -50.27 .855 .000 .005 .877 2.483 niro Investments 22.10 -.140 -.612 .431 .001 1.656 bahman Investments -67.82 .963 -.063 .000 .987 1.331 Damavand future Investments 45.61 555. -.194 .466 -.031 1.171 Iran behshar industry group 16.60 .064 -.216 .084 -.314 1.159 Investments Iran industrial development 10.25 .064 -.310 .074 -.243 1.107 Investments sepah Investments 17.06 .016 -.466 .053 -.089 1.081 insurance industry Investments 46.07 -.800 .031 .652 1.069 Iran national Investments -33.00 .968 .037 .003 .897 1.505 industry and mining Investments -79.05 .676 -.538 .687 -.205 3.294 tejarat bank 45.28 -.127 -.662 .312 .122 1.305

Result Analysis for Model2: Determination coefficients of the second model, is bigger than the first model, indicating that is :In the second model by adding variables components of intellectual capital to the model of the first, The explanatory power of the second regression model is improved in comparison with the first regression model. Explanatory power of the second model with the EVA variables is 85/71 % (18 financial intermediations firms of 21 firms Explanatory power of the second model with the EPSR variables is 66/7 % (4 financial intermediations firms of 21 firms. As Explanatory power of EVA variable is more than Explanatory power of EPSR variable, for market value of firms. (* in the second rows are vif of variables in table 4 and table 5). (1.000 = are missing data in columns of various coefficients Beta)

1930 Aust. J. Basic & Appl. Sci., 5(12): 1926-1933, 2011

Table 4: Regression model1 with accounting residual earning per share criteria. Name of firm constant(a0) Beta BV) Beta(Xt)Is PSR sig AdjustedR2(Ftest) vif bank of new economy 39.83 0.235 -.323 0.056 -.112 1.104 Iran leasing 22.00 .530 -.440 .019 .714 1.909 ghadir car leasing -10.53 .951 .097 000. .982 1.192 industry and mining leasing -36.72 .910 .329 327. .105 12.930 rayan saipa leasing 12.05 .948 -.039 001 .910 1.293 Persian bank -34.34 .392 -.123 .639 -.170 1.003 kar afarin bank 51.23 -.173 .947 .025 .679 1.290 melat bank 59.54 .989 .089 .001 .899 1.121 sina bank -17.49 1.133 -.823 .370 .059 4.282 boali Investments -20.14 .492 -.063 .459 -.025 1.147 melat Investments -21.57 .898 .238 .008 .853 1.001 niro Investments 61.267 .344 -.788 .042 .640 1.016 bahman Investments -89.29 1.028 .049 .000 .985 2.008 Damavand future Investments 45.31 .474 .067 .511 -.070 1.009 Iran behshar industry group 16.41 -.732 .656 .000 .100 1.056 Investments Iran industrial development -47.78 .290 -.520 .441 -.009 1.066 Investments sepah Investments -18.52 .185 -.273 .782 -.269 1.023 insurance industry Investments 97.24 -.630 .607 .211 .249 1.184 Iran national Investments -24.10 .827 -.188 .002 .884 1.683 industry and mining Investments -51.87 .562 -.666 .299 .137 1.338 tejarat bank 25.07 .108 -.272 .760 -.254 1.108

Table 5: Regression model 1 with Economic value added per share criteria and proxy Variable of Intellectual capital. BetXt Adjust Beta Beta Beta Beta Beta Name of firm Beta (a0) Is Beta OSt sig ed R2 BVt RPEt SPt RGt MEt EVA (F test) bank of new economy 12.11 .174 1.576 2.899 -.42 .525 .621 -3.580 .000 1.000 8.029* 1.712 1.255 2.602 6.299 6.299 3.342 Iran leasing 28.30 1.114 .067 -.522 -.56 -.78 .047 .214 .000 1.000 3.070 1.105 2.647 3.147 5.409 4.538 6.575 ghadir car leasing 10.31 .893 -.286 .147 .132 -.199 -.043 -.115 .000 1.000 1.560 1.918 4.994 3.790 3.760 1.912 2.818 industry and mining 18.908 .965 -.060 -.033 -.039 -.197 .014 -.154 .000 1.000 leasing 3.570 4.973 1.726 1.790 3.525 1.791 1.260 rayan saipa leasing 11.515 .370 .345 .171 .165 -.181 1.285 -1.859 .000 1.000 1.542 4.283 1.252 2.084 3.266 2.353 2.220 Persian bank -57.400 .970 -.135 -.656 .066 .026 -.191 .950 .004 .998 3.966 1.153 6.220 3.295 5.615 1.229 1.341 kar afarin bank -19.475 1.584 -.665 .426 .142 2.001 .805 2.106 .012 .576 1.536 1.032 3.502 1.782 2.967 3.821 2.743 melat bank -198.2 -1.34 1.224 3.581 1.271 2.924 -2.35 -1.294 .011 .923 1 6.752 3.185 3.013 1.358 4.784 2.705 4.153 sina bank -308.922 .806 .049 -.331 -.202 -.135 .128 1.000 .043 .996 2.220 3.163 2.416 1.242 3.663 2.629 boali Investments -51.063 1.159 -.693 .955 -.696 1.069 1.873 .104 .234 .057 1.642 2.015 2.379 4.097 1.978 1.942 2.034 melat Investments -51. 123 1.159 -.693 .955 -.696 1.069 1.873 .104 .340 .065 1.642 2.015 2.379 4.097 1.978 1.942 2.034 niro Investments 654.867 -.389 .078 -.210 -.128 -.187 -.600 -.908 .000 1.000 4.907 4.489 1.487 4.446 2.083 1.404 0.953 bahman Investments -11.993 .443 .159 -.007 -.376 .974 -.358 .456 028. .564 1.525 2.834 6.590 1.880 2.602 1.653 5.935 Damavand future -230.0 .851 -.046 -.072 .027 .063 -.195 .154 .000 1.000 Investments 4 1.932 1.740 4.529 4.136 4.786 1.885 2.167 Iran behshar industry 405.490 -.307 .347 -.104 1.000 1.330 .316 .263 .259 .863 group Investments 0.066 4.743 8.144 5.513 0.553 .034 Iran industrial -455.79 3.478 -2.96 3.998 3.015 .799 -4.46 5.749 .000 1.000 development 1.067 4.655 0.918 1.647 2.720 1.472 4.761 Investments sepah Investments 280.591 1.461 -.701 3.097 -2.11 .611 8.377 -9.714 .000 1.000 6.233 1.711 2.168 1.537 1.608 1.849 2.608 insurance industry 574.755 -.234 -.210 -.046 .809 -.004 .186 -.776 .000 1.000 Investments 1.548 1.729 6.118 3.816 1.852 6.323 4.425 Iran national 7943.9 -.329 -.457 -.254 -.191 .343 -.239 -.735 .000 1.000 Investments 1.196 1.420 2.265 0.686 2.665 2.330 7.985 industry and mining -120.6 1.066 -.065 -.352 -.132 -.080 -.109 -.236 .000 1.000 Investments 1.113 2.259 2.043 3.520 3.941 2.218 1.754 4.990 tejarat bank -7.1821 .860 -2.08 .090 -.270 .710 -2.58 2.981 .804 -.823 .213 4.677 5.562 6.289 2.713 1.904 2.687

1931 Aust. J. Basic & Appl. Sci., 5(12): 1926-1933, 2011

Table 6: Regression model 1 with accounting residual earning per share criteria and proxy Variable of Intellectual capital. Name of firm Beta (a0) Beta Beta Beta Beta Beta Beta Beta sig Adjust BVt Xt RPEt SPt RGt MEt OSt ed R2 is F test Epsr bank of new economy 67.23 .960 -5.66 8.699 14.384 -.432 -10.7 -6.641 .000 1.000 5.069* 1.720 1.136 4.858 2.154 2.931 4.149 Iran leasing 34.38 1.054 -.165 -.413 -.468 -.855 -.019 .146 .000 1.000 2.851 1.013 1.450 2.239 2.675 1.393 1.680 ghadir car leasing 11.515 .965 -.060 -.033 -.039 -.197 .014 -.154 .000 1.000 3.570 4.973 1.726 1.790 3.525 1.791 1.260 industry and mining 28.81 1.510 1.107 -.300 .593 -.024 .713 -.911 .020 .987 leasing 4.378 4.085 1.612 1.620 5.900 3.095 2.549 rayan saipa leasing 19.750 .164 .431 1.890 1.946 -2.68 .313 -2.327 .042 .788 1.28 3.029 2.541 1.213 2.498 5.932 3.506 Persian bank 57.958 -.470 -.641 -1.58 .199 1.748 .133 1.438 .050 .294 1.052 1.770 1.485 2.920 1.224 1.961 3.253 kar afarin bank -19.271 -1.34 1.224 3.581 1.271 2.924 -2.35 -1.294 .011 .923 6.752 8.185 3.013 1.358 4.784 2.705 4.153 melat bank -544.90 -.237 1.198 .857 .172 .105 -.849 .181 .123 023. 5.944 2.846 1.269 3.333 2.604 1.316 5.006 sina bank 22.3696 .802 .160 -.313 1.000 -.168 -.050 -.024 .040 .995 2.275 3.678 3.066 2.798 5.276 4.873 boali Investments 27.422 -4.33 5.879 1.131 5.465 -7.87 3.196 -2.845 .000 1.000 1.264 1.169 2.498 2.216 3.689 1.978 3.793 melat Investments 300.194 1.795 -1.17 -.240 1.688 -2.62 2.540 -5.875 .756 .023 3.945 0.791 1.762 1.136 1.671 2.481 1.633 niro Investments 599.110 -.338 -.017 -.162 -.112 -.175 -.583 -.805 .000 1.000 0.757 2.405 7.854 2.955 1.767 5.820 2.271 bahman Investments -939.88 .350 .207 372 -.245 .843 -.240 .409 .953 .002 2.306 3.726 3.494 2.955 1.568 2.832 5.044 Damavand future .124 090 .277 -.399 .002 -.089 .378 -.417 .223 .876 .056 Investments 3.020 1.380 3.508 1.234 0.181 1.045 1.904 Iran behshar industry 136.289 -.580 .005 .780 1.000 .677 .141 .112 .264 .857 group Investments 1.315 4.350 0.777 1.904 3.849 1.368

Iran industrial -9.120 .769 2.483 -.241 2.382 -.571 1.681 -.239 .000 1.000 development .461 1.871 6.207 6.405 5.357 1.685 1.967 0.534 Investments sepah Investments -153.7 .002 -1.30 .025 1.110 .113 .319 1.000 882 .502 2 2.343 1.049 3.590 1.884 3.285 2.185 insurance industry 40465 -1.99 3.208 1.410 -2.19 .645 -3.04 -2.354 .000 1.000 Investments 1.490 4.122 3.851 3.033 1.916 3.398 1.363 Iran national 40.465 -1.99 3.208 1.410 -2.19 .645 -3.04 -2.354 .000 1.000 Investments 1.490 4.122 9.851 3.033 1.916 3.398 1.363 industry and mining 34.1896 -.159 .419 -.258 -.134 -.166 1.586 -2.533 .000 1.000 Investments 6.620 6.730 1.037 5.485 1.474 1.852 2.537 tejarat bank 76.7390 -1.26 -2.21 -12.3 -2.05 2.796 12.81 -2.170 .000 1.000 2.258 1.305 1.058 2.729 2.465 4.300 1.468

Discussion and Conclusions: Hypothesis testing and statistical analysis can be stated: According to the results of the first hypothesis test and table 3 and 4, the first research hypothesis was accepted. According to the results of the second hypothesis test and table 5 and 6.The second research hypothesis is rejected and the third hypothesis that claimed: The capacity of residual income calculated by EVA to explain variations in a firm's market value will be significantly greater if the proxy variable of intellectual capital is added. Accepted. Therefore, the capacity of residual income calculated by generally accepted accounting principle of Iran to explain variations in a firm's market value would be significantly lower than the capacity of residual income calculated by EVA if the proxy variable of intellectual capital is added in the second regression model, in financial intermediations firms accepted in Tehran stock exchange. For economic growth and development companies, Overcome weaknesses in the traditional financial reporting system (i.e., focusing on financial instruments) will lead to related decisions about economic and increases the accuracy of business decisions, it is recommended, the research will test models for different industries. And the need to economic variables, including measure the economic value added (EVA) in the financial reporting in Iran, are critical.

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