EVA (Economic Value Added) ve MVA (Market Value Added): İMKB'deki hisse senedi fiyatları üzerine ekonometrik bir analiz
EVA (Economic Value Added) and MVA (Market Value Added): An empirical analysis of stock prices in Istanbul Stock Exchange
- Tez No: 102623
- Danışmanlar: DOÇ.DR. OSMAN GÜRBÜZ
- Tez Türü: Doktora
- Konular: Ekonomi, Economics
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2001
- Dil: Türkçe
- Üniversite: Marmara Üniversitesi
- Enstitü: Bankacılık ve Sigortacılık Enstitüsü
- Ana Bilim Dalı: Bankacılık Ana Bilim Dalı
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 196
Özet
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Özet (Çeviri)
SUMMARY The financial theory suggests that every company's ultimate aim is to maximize the wealth of its shareholders. In the past, this ultimate aim has been either ignored or misunderstood. Traditional accounting based measurement metrics like ROI and EPS are used as the most important performance measures which do not theoretically correlate with the shareholder value creation very well. Currently one of the most popular value based measures is EVA. EVA measures whether the operating profit is enough compared to the total costs of capital employed: EVA = (ROI-WACC)*Capital Employed The idea behind EVA is that shareholders must earn a return that compensates the risk taken. EVA is based on the common accounting based items like interest bearing debt, equity capital and net operating profit. It differs from the traditional measures mainly by including the cost of equity. Mathematically EVA gives exactly the same results in valuations as DCF or NPV which are acknowledged as theoretically best analysis tools from the shareholders perspective. However, it is asserted that NPV and DCF do not suit in performance evaluation because they are based exclusively on cash flows. EVA is a measure which tells what have happened to the wealth of shareholders. According to EVA supporters, earning a return greater than the cost of capital increases the value of a company, and earning less decreases its value. It is helpful to understand the basic ways in which EVA can be improved. Increasing EVA falls always into one of the following three categories: 1. Rate of return increases with the existing capital base. 2. Additional capital is invested in business earning more than the cost of capital. 1893. Capital is withdrawn or liquidated from businesses that fail to earn return greater than the cost of capital. The first category means improvement of operating efficiency or increasing of revenues. The second category means completely same as accepting only NPV-positive investments. The third category, withdrawing capital, is probably not so widely understood and applied as the previous ones. It is however also very important to realize that shareholder value can also be increased if capital is withdrawn from businesses earning less than the cost of capital. These categories and ways to improve EVA are certainly not new ways to improve the wealth of shareholders. In addition, advantages of EVA can be stated as folows: 1. EVA is closely related to NPV. It is closest to corporate finance theory that argues that the value of the firm will increase if you take positive NPV projects. 2. It avoids the problems associated with percentage spreads - between ROE and Cost of Equity and ROC and Cost of Capital. These approaches may lead firms with high ROE and ROC to turn away good projects to avoid lowering their percentage spreads. 3. It makes top managers responsible for a measure that they have more control over rather than market price per share that they feel they cannot control as well. 4. It is influenced by all of the decisions that managers have to make within a firm - the investment decisions and dividend decisions affect the return on capital. 190If the total market value of a company is more than the amount of capital invested in it, the company has managed to create shareholder value. If the case is opposite, the company has destroyed shareholder value. The difference between the company's market and book value is called MVA and this can be represented as follows: Market Value Added = Market Value of Equity - Book Value of Equity Market Value Added = Present Value of All Future EVA Market value added is equal to present value of all future EVA. According to the theory, if a company increases EVA, it increases its market value added, or in other words increases the difference between company's value and the amount of capital invested in it. The relationship with EVA and MVA has its implications on valuation. By arranging the formulas above, a new definition of the value of company is established: Market Value of Equity = Book Value of Equity + Present Value of All Future EVA This valuation formula of EVA is always equivalent to DCF and NPV if the necessary adjustments are made before EVA is calculated. This relationship between EVA and MVA has been studied in recent years in many studies with many methods - and with different results. However, every study has different results which shows the degree of correlation may change according to the method used to calculate EVA. The distortions in EVA probably affect the correlation between EVA and share prices. This might also be one reason why EVA does not correlate with share prices in every study so much better than other accounting based measures like ROI and EPS. 191Conceptually, EVA is superior to accounting profits as a measure of value creation because it recognizes the cost of capital and, hence, the riskiness of a firm's operations. The main shortcoming with ROA is that maximizing rate of return does not necessarily maximize the return to shareholders. As a relative measure and without the risk component ROI fails to reflect the performance of the operations correctly. Therefore, capital can be misallocated on the basis of ROI. The difference between EVA and ROI is actually exactly the same as it is with NPV and ERR. Maximizing rate of return percentage does not matter. What matters is the absolute amount of shareholders' wealth added. EVA and NPV go hand in hand as also ROI and IRR do. There is no reason to abandon ROI and IRR. They are very good and illustrative measures that tell us about the rate of returns. IRR can always be used along with NPV in investment calculations and ROI can always be used along with EVA in company performance. IRR and ROI provide us additional information. Likewise, ROE suffers from the same shortcomings as ROI. Risk component is not included and hence there is no comparison. The level of ROE does not tell the owners if company is creating shareholders wealth or destroying it. With ROE this shortcoming is however much more severe than with ROI, because simply increasing leverage can increase ROE. EPS can be raised simply by investing more capital in business. If the additional capital is equity, then the EPS will rise if the rate of return of the invested capital is just positive. If the additional capital is debt, then the EPS will rise if the rate of return of the invested capital is just above the cost of debt. EPS and earnings can be increased simply by pouring more money into business even though the return on that money would be entirely unacceptable from the viewpoint of owners. There has been a debate for and against EVA in academic and management literature. However, there are currently very few articles dealing objectively with EVA's strengths and weaknesses as a management tool. %'v 192In the first part of this study, the relationship between EVA, MVA, and MV and the relationship of these measures with the traditional measures of performance is analyzed. The results are summarized below: I) In one of the studies, which is similar with that of Stewart's, done by using the data for 143 stocks traded in ISE between 1993 and 1998, the correlation coefficient between EVA and MVA is found to be positive but low. H) In another study, which is modified to make it more similar to Stewart's study, done by using the data for 109 stocks traded in ISE between 1993 and 1998, the change in the values of EVA, MV and MVA from 1993 to 1998 is calculated. This time, the correlation coefficient between EVA and MVA is found to be 47% and the correlation coefficient between EVA and MV is found to be 49%. IH) Using the data for 109 stocks traded in ISE between 1993 and 1998, a regression analysis is conducted by taking EVA as an independent variable and MV and MVA as dependent variables respectively. In this study, which is similar with that of Uyemura, Kantor and Pettit's, the explanatory powers of the models are found to be low. IV) The correlation coefficients between EVA, MVA and MV during 1993 and 1998 are found to be high. This shows there is a positive correlation between these measures. V) To test the model, (MVA = The present value of all future EVA), for the stocks traded in ISE between 1993 and 1998, correlation coefficients of EVA, MVA and MV are calculated. The highest correlation coefficient is found to be between MV 1993 and the discounted values of EVA 1993 to EVA 1996. Therefore, this model can easily be said to be supported for the stocks in ISE. a) To test the model, (MV = BV + The present value of all future EVA), for the stocks traded in ISE between 1993 and 1998, a regression analysis is conducted where the discounted values of EVA 1993-EVA 1996 is used as independent variables, and MVA 1993 and MV 1993 are used as dependent variables. 193R2's are found to be 76% and 66% respectively. Therefore, this model also can easily be said to be supported for the stocks in ISE. VI) In a study done by using 83 stocks traded in ISE between 1993 and 1998, the correlation coefficients between EVA, MVA and MV and traditional performance measures (NI, EPS, ROA and ROE) are calculated. The correlation coefficients of NI is 74% with MV and 69% with MVA. This study is similar to that of Uyemura, Kantor and Pettit's who found EVA has the highest correlation coefficients with traditional performance measures. However, coefficients of EVA and other traditional measures with MV and MVA are found to be lower than those of NTs. VE) Using the data for 83 stocks traded in ISE between 1993 and 1998, a regression analysis is conducted by taking performance measures as independent variables and MV and MVA as dependent variables respectively. In this study, explanatory powers of EVA (27% and 26%) and other traditional measures with MV and MVA are found to be lower than those of NTs (55% and 47%). VIE) A regression analysis is conducted by taking EVA 1997, MV 1997 and NI 1997 as independent variables and MV 1998 as a dependent variable. R is found to be 87% and this shows there is a statistical relationship between EVA 1997, MV 1997, NI 1997 and MV 1998. K) Using the data for 83 stocks traded in ISE between 1993 and 1998, a regression analysis is conducted by taking EVA(t-i), MVA(t-i), MV(t.i) and NI (t.i) values as independent variables and MV(t) as a dependent variable. R2 is found to be 83% and this shows a prediction for next period's MV done by taking current period's MVA and NI values can be accurate. This means even the weak-form efficiency of ISE is questionable because a model using current period's MVA and NI can be significantly explanatory for predicting next period's MV. The studies summarized above shows that for most of the stocks traded in ISE, EVA has a strong statistical relationship with MVA and MV. However, Nljias stronger relationship with MVA and MV than EVA. £i 194, '>“*>In the second part of this study, the performance of the sectors in ISE is analyzed: X) The 24 sectors in ISE is analyzed by using average capital, EVA and MVA for the years 1993-1998. MVA/Capital, MVA/EVA and EVA/Capital ratios are calculated for performance evaluation. a) According to sectoral performance analysis for the period 1993- 1998, stationary, utility and petrolium product sectors are found to be successful. On the other hand, iron&steel, glass and textile sectors are found to be unsucccesful. According to weighted performance analysis, stationary is the most whereas iron&steel sector is the least successful sector for the period 1993-1998. b) According to sectoral performance analysis for 1998, retail, stationary, petrolium product and consumer durables sectors are found to be successful. On the other hand, iron&steel, utility, textile, glass and ceramic sectors are found to be unsucccesful. XI) In a study, which is modified to be more similar to Stewart's study, done by using the data for 24 sectors in ISE between 1993 and 1998, the change in the values of EVA, average capital and MVA from 1993 to 1998 is calculated. This time, the correlation coefficient between EVA and MVA is found to be high and positive whereas the correlation coefficients between average capital and EVA and MV are found to be negative. Therefore, for the sectors analyzed, the change in EVA and MVA is positively correlated but for every increase in average capital, causes a decrease in EVA and MVA. This shows that the sectors may not be investing their capital efficiently and/or there is a diseconomies of scale problem. XO) Using the data for 109 stocks traded in ISE between 1993 and 1998, a multiple ratio analysis is conducted for EVA, MVA, and MV to understand which company increased its EVA, MVA, and MV most from 1993 to 1998. According to these analysis, Banvit, Vestel and Migros has the highest whereas Okan Tekstil, Izmir Demir Celik and Aksu iplik has the lowest multiples. ”-'1 ;/? 195XIII) Using the data for 186 stocks traded in ISE between 1993 and 1999, a productivity of paid-in capital and equity analysis is conducted. EV A/Equity and EV A/Paid-in Capital ratios are calculated. As a result, the most successful companies are found to be Koniteks, EGS Dis Ticaret and Çukurova Elektrik whereas the most unsuccessful companies are found to be Gima, Arat Tekstil and BayrakliBoya. ?SHSKSSS 196
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