Relationship between investment opportunities and firm performance according to corporate life cycle: evidence from Tehran Stock Exchange

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1 Applied mathematics in Engineering, Management and Technology 2 (4) 2014: Relationship between investment opportunies and firm performance according to corporate life cycle: evidence from Tehran Stock Exchange Ghodratollah Taleb Nia Professor and the faculty member of Islamic Azad Universy, Science and Research branch Mona Abednazari (corresponding author) student of financial management in Islamic Azad Universy, Science and Research branch ( mona.abednazari@yahoo.com) Fatemeh Dadbeh PhD student of Accounting in Islamic Azad Universy Science and Research branch Abstract: The aim of this paper is to review the relationship between investment opportunies and firm performance according to corporate life cycle. To test the research hypothesis, a sample of 40 companies listed in Tehran Stock Exchange over the period based on panel method was taken. In these models, the presence or absence of effects models (fixed or random) is reviewed and finally the best model is estimated. Inference is based on significant level or p-value, thus likely that any value or significance level of the test is less than 0/05 is rejected at the 95 percent confidence level. The results indicate that the investment opportunies has relationship wh firm performance for firms in decline but has no relationship wh firm performance for firms in growth. Keywords: Investment Opportunies, firm performance, Life Cyle, Return on Assets, Tobins Q 1.Introduction 1.1.Investment Opportunies Rational decision making requires relevant and reliable information. Accounting as an information system for fulfilling needs of various users, especially investors, is a valuable source of information. Thus, is expected that the outcome of accounting information system is of qualy and relevance. Future investment opportunies reflected to investors by means of financial statement ems are important to the users. Investment opportunies constute an important part of firm value (Miller & Modigliani, 1961; Dix & Pindyck, 1994). Investment opportunies are interpreted by market as better future and are reflected in valuation of firms. However, as Hultazen & Watts (2001) point out, empirical research based on accounting valuation to a large extent has ignored growth. Growth potential depends on investment opportunies and life cycle. If earnings are related to change in investment opportunies, then providing evidence of this relationship can be useful in firm valuation. Firms wh investment opportunies are expected to be valued differently in market. It is also argued that in formativeness of investment opportunies is communicated to market through such accounting variables as earnings, operating cash flows and accruals, and thus these variables are of different in formativeness in firms wh various investment opportunies. On the other hand, a firm s age and current stage of life cycle influence s future investment opportunies. 1.2.Firm Performance 29

2 Achieving long-term economic growth requires optimal allocation of resources in the national economy and this issue whout efficient capal markets is not easily possible, in a healthy economy, efficient system plays an essential role in the distribution of resources. Stock exchange market as an official capal market is responsible for directing and supervising financial system. Resource allocation in the stock market, need information to investors to help them make decisions that lead to the peak of their wealth. This information is available for users through accounting system and in the form of financial statements. Furthermore, users by evaluating models can evaluate the performance of different companies. Evaluating models by connecting accounting and financial data and market value do this job. Researchers have presented several theoretical models to explain the value of company's value. Inial models are often based on non-accounting variables and pursued this goal however, because of the difficulties they were gradually outdated and replaced by other models. Measuring the value of company often as a substute for the financial markets is understandable. The value of the company (economic un) as the value of market is calculated by control cost and preferred stock minus cash and cash equipment. Value of company's economic creria reflects the market value of a business. This definion is the claim of all bondholders preferred shareholders and common shareholders of company value. 1.3.Investment Opportunies and Firm Performance Marion Itulchinson and Ferdinand A Gul (2004) reviewed that prior research on the relationship between corporate controls and firm performance is premised on the notion that, in theory, there is direct association between corporate governance and firm performance. However, extensive research has produced mixed and often weak results. In this paper, they pos, as a primary relationship, a negative association between growth and firm performance and then examine whether corporate governance variables moderate this negative relationship. Their results support this notion and show that the role of corporate governance variables in firm performance should be evaluated in the context of the firm's external environment measured in this study in terms of growth opportunies. Claudio Lordere and Urs Waelchi (2009) investigated that over time, firms age and slowly lose their abily to compete, as if they were living organisms: Tobin s Q ratios decline and profs fall. This finding cannot be explained by sample selection, firm-age definion, manager or industry age, and time-varying uncertainty. Corporate aging could occur for two reasons. Consistent wh cementation of organizational rigidies, costs rise, margins thin, growth slows, assets become obsolete, and investment and R&D activies decline as firms get older. Aging also seems to advance the diffusion of rent-seeking behavior: corporate governance worsens and CEO pay goes up. Overall, firms seem to face a serious aging problem. John E. Core, Robert W. Holthausen, David F. Larcker (1999) find that measures of board and ownership structure explain a significant amount of cross-sectional variation in CEO compensation, after controlling for standard economic determinants of pay. Moreover, the signs of the coefficients on the board and ownership structure variables suggest that CEOs earn greater compensation when governance structures are less effective. They also find that the predicted component of compensation arising from these characteristics of board and ownership structure has a statistically significant negative relation wh subsequent firm operating and stock return performance. Overall, our results suggest that firms wh weaker governance structures have greater agency problems; that CEOs at firms wh greater agency problems receive greater compensation; and that firms wh greater agency problems perform worse. 1.4.Measuring Investment Opportunies, Firm Performance and Life Cycle IOS : Variable indicating investment opportunies during the fiscal year which is measured by market to book value of stock. This ratio has been used by Collins & Kothari (1989), Biddle & Seow (1991), Gaver & Gaver (1993), Hrikumar & Harter (1995), and Jones (1997, 2001) to measure investment opportunies. 30

3 Beta : Measure of systematic risk which is included into the model as a control variable Kumar & Krishnan (2008). Beta is estimated by the slope of market model regression for stock daily return (R ) and market daily return (R mt ) for one year period beginning from the fourth month of the period under investigation. Firm Performance. In this study for evaluate the firm performance, we use ROA and Tobins Q ratio: Tobins q = total debt + (stock price x shares of outstanding)/ book value of assets ROA = Prof to shareholders Total assets Life Cycle. Various models have been used in the accounting and finance lerature to determine corporate life cycle stage. One of the most commonly-used models is suggested by Anthony & Ramesh (1992). They group firms by three variables: sales growth, capal expendures, and firm age. This research uses the three variables to group firms by their life cycle stage. To this end, we follow the methodology suggested by Park & Chen (2006) as following: 1. Sales growth, capal expendure, and firm age are calculated for each firm-year. 2. Industry quintiles are calculated for each of the above variables for each firm-year. The score of each firmyear is assigned from 1 to 5 using the following table. Quintiles Sales Growth (SG) Capal Expendure (CE) Firm age 1st quintile nd quintile rd quintile th quintile th quintile SG t = 1 3. Each firm-year is now assigned a combined score which can be used to classify firm into growth, matury, and decline firms according to the following scheme: a. Growth stage if the score falls between 12 and 15. b. Matury stage if the score falls between 7 and 11. c. Decline stage if the score falls between 3 and 6. Sales growth, capal expendure, and firm age are calculated as following: CE t = (increase decrease in fixed assets during the period firm market value) 100 AGE: The difference between the year in question and the year of foundation of the firm. This study implies that the relationship between investment opportunies and firm performance according to corporate life cycle in firms of Tehran Stock Exchange. 2.Research model and Hypothesis Based on the developments of the lerature, one hypothesis is developed. The hypothesis is stated as follows: H 1 : The relationship between investment opportunies and performance varies significantly across life cycle stages. In this paper for calculated the performance; we use ROA and Tobins Q and we estimate two model This paper is broken into four substantive parts. Following this introductory section, the next section defined Method. This is followed by results. The final section is by way of discussion and conclusion. 31

4 3.Method As is mentioned, the sample is composed of 40 companies listed in Tehran Stock Exchange. The methodology for analyzing data is based on panel modeling. For analyze the hypothesis; we use regression using a panel data. We analyze the hypothesis in two step of life cycle: growth and decline. 4.Results Table 1, hereafter resumes the descriptive statistics of the variables on the whole period ( ): mean, median, maximum, minimum and standard deviation. The performance is measured by Tobin s Q and Return On Assets (ROA). The number of observation is 200. Table 1- Descriptive Statistics Variables N/valid Mean Median Std.Deviation Maximum Minimum TOBIN'S Q /197 1/04 1/47 8/11 ROA /827 3/45 10/46 53/06 LnTOBIN'S Q /056 1/11 0/46 2/31 LnROA /486 1/23 1/20 3/97 IOS /929 2/08 2/58 13/67 Beta /147 2/02 12/68 57/08 5.Normal distribution of the dependent variables Normaly of a regression model remaining is one of the regression assumptions that illustrate the validy of the regression tests. Then using Kolmogrov - Smirnov test normaly of dependent variables distribution is investigated. Because the normaly of dependent variables leads to normaly of remains of model (Difference between the estimated values of the real data) So, is necessary control the dependent variable controlled before the estimate parameters and if this condion was not available take good solution for making them normal (conversion). The null hypothesis and hypothesis 1 in this test is wrten as follow: H H 0 : : 1 Meaningful values for TOBIN'S Q and ROA variables during studied years is less than 0/05 so, null hypothesis is rejected for this variable. Normal distribution of variables in different years is not normal but the values of these variables logarhm in these years is more than 0/05. So their distribution has been normal. Variables Data for the dependent variable follows a normal distribution Data for the dependent variable not follows a normal distribution Number Table 2: Test Kolmogorov Smirnov Normal parameters Most Extreme Differences Mean Std.diviation Absolute Posive Negative 32 Kolmogorov- Smirnov Z Asymp. Sig. (2-taile) TOBIN'S Q 200 1/20 1/47 0/15 0/15-0/09 2/08 0/000 ROA 200 8/83 10/46 0/21 0/21-0/21 3/03 0/000 LnTOBIN 'S Q 200 1/06 0/46 0/16 0/09-0/16 1/08 0/197 LnROA 200 1/49 1/20 0/12 0/12-0/08 0/77 0/592

5 In this study we have one hypothesis. In this study we use two variables for firm performance. We analyze data as follow: 6.Panel Analysis Hypothesis For data analysis of the panel analysis (Panel) whout fixed effects, wh fixed effects and wh random effects is used. To determine the effectiveness of model wh fixed or random effects Limer (Chav) test and Houseman test is used. As the table 3 shows, the results of chav test is indicate that the model wh fixed effects is better than pooled model. 7.The results of the hypothesis test (model 1) Table 3: Limer(chav) Test for Hypothesis Effects Test Statistic d.f. Prob. Cross- section F 1/186 (39,156) 0/231 Cross- section Chi- square 51/ /080 After that we used chav test for determined that the model whout fixed effects is appropriate The supposed model to test the first hypotheses is as follow: Ln( Qtobin ) 0 1ios 2beta 3D 4 IOS D D variable in model for corporate in growth is equaled to zero and for corporate in decline is equal to 1. The results of whout effects show that probabily of significant of F is equal This result means that there is a significant model. The coefficient of determination is equal to0/29. The t-statistics for IOS is equal to 0/97 (meaningless), for Beta is equal 0/1 (meaningless), for D is equal to -2/38(meaningful and negative) and for IOS*D is equal to -4/45 (meaningful and negative). The results show in table 4: Table 4: Cross- section whout effects of Hypothesis (model 1) Variables Coefficient t-statistics C 1/223 21/478 IOS 0/013 0/972 Beta 0/000 0/104 D -0/216-2/381 IOS*D -0/089-4/450 Weighted Statistics R-Squared 0/294 Prob(F- statistics) 20/278 Durbin- Watson stat 1/805 The relationship between IOS and Tobins Q for corporate in decline is meaningful but for corporate in growth has no relationship between variables. 8.The results of the model 2 Table 5: Limer(chav) Test for Hypothesis (model 2) Effects Test Statistic d.f. Prob. Cross- section F 1/197 (39,156) 0/222 Cross- section Chi- square 49/ /110 After we used chav test, the results show that the model whout effects is appropriate. 33

6 The supposed model to test the hypothesis is as follow: Ln( ROA ) 0 1ios 2beta 3D 4 IOS D The results of whout fixed effect show that probabily of significant of F is equal This result means that there is a significant model. The coefficient of determination is equal to0/29. The t-statistics for IOS is equal to - 1/06 (meaningless), for Beta is equal 0/1 (meaningless), for D is equal to -9/21(meaningful and negative) and for IOS*D is equal to -2/27 (meaningful and negative). The results show in table 6: Table 6: Cross- section Fixed effects of Hypothesis (model 2) Variables Coefficient t-statistics C 2/434 21/690 IOS -0/028-1/062 Beta 0/000 0/036 D -1/646-9/211 IOS*D -0/089-2/270 Weighted Statistics R-Squared 0/599 Prob(F- statistics) 0/000 Durbin- Watson stat 2/061 The relationship between IOS and ROA for corporate in decline is meaningful but for corporate in growth has no relationship between variables. 9.Discussion and Conclusion In this paper, we sought to measure and to explain investment opportunies in firms of Tehran Stock Exchange on a sample of 40 large firms during 2008 to This paper has examined the relationship between investment opportunies and firm performance according to corporate life cycle. For examined the firm performance, we use return on assets and tobins q. The results in both two model shown that investment opportunies has relationship wh firm performance for firms in decline and has no relationship wh firm performance for firms in growth. The researcher can choose the greater number of companies and use the other method for evaluation of firm performance. Reference Aharony J., H Falk, N Yehuda (2006). Corporate Life Cycle and the Value Relevance of Cash Flow versus Accrual Financial Information. School of Economics and Management Bolzano, Italy,Working Paper; 34. Ahmed, A Accounting earnings and future economic rents: An empirical analysis. Journal of Accounting and Economics 17: Amir, E., and B. Lev Value-relevance of nonfinancial information: The wireless communications industry. Journal of Accounting and Economics 22: Anthony, J. H. and Ramesh, K.(1992). Association between Accounting Performance Measures and Stock Prices: A Test of the Life Cycle Hypothesis, Journal of Accounting and Economics, Vol.15, pp Babajani, J., Bulu, Q., Alizadeh, A, (2011). The relationship between investment opportunies and value relevance of operating cash flow and accruals. Stock Exchange Journal, No 13, Vol. 1. Ball, R. and P. Brown An empirical evaluation of accounting income numbers. Journal of Accounting Research, Volume 6, Issue 2: Barth, M. E., W. H. Beaver, and W. R. Landsman The relevance of value relevance research. Working paper. Journal of Accounting and Economics Conference. 34

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