University 18 Lessons Financial Management. Unit 12: Return, Risk and Shareholder Value

Transcription

1 University 18 Lessons Financial Management Unit 12: Return, Risk and Shareholder Value

2 Risk and Return

3 Risk and Return Security analysis is built around the idea that investors are concerned with two principal properties inherent in securities: the return that can be expected from holding a security, and the risk that the return achieved will be less than the return that was expected. We therefore need to distinguish between realised return and expected return. Total return = (Cash payments + Price change over the period)/ Purchase price of the asset Series of Returns: The total return is an acceptable measure of return for a specified period of time. However, we may have to describe a series of returns.

4 Arithmetic Return The arithmetic average or Ā = a / n or the sum of each of the values being considered divided by the total number of values. The arithmetic average is appropriate as a measure of central tendency of a number of returns calculated over a period of time, such as a year. However, when percentage changes in value over time are involved, the arithmetic mean of these changes may be misleading.

5 Geometric Return The geometric average (GA) return measures compound, cumulative returns over multiple periods. It is used in investments to reflect the realised change in wealth over multiple periods. The GA is defined as the nth root of the product resulting from multiplying a series of returns together. G = [(1+R 1 )(1+R 2 )..(1+R n )] 1/n - 1 Where R = total return and n = number of periods However, in this case return relatives are used, i.e. if the return for a period is -15 per cent, then the return relative is 0.85 (1 0.15).

6 Geometric Return Example If a stock started at Rs.50, rose to Rs.100 at the end of Year 1and then dropped to Rs.50 at end of Year 2, then the Geometric Average over two years would be calculated as follows: Return relative, Year 1 = = 2.00 Return relative, Year 2 = = 0.50 G = [(2.0)*(0.5)] 1/2 1 = [1.0] 1/2-1= 0.00

7 Risk in a Traditional Sense Forces that contribute to variations in return price or dividend (interest) constitute elements of risk. Some influences are external to the firm, cannot be controlled, and affect large number of securities. Other influences are internal to the firm and are controllable to a large extent. In investments, those forces that are uncontrollable, external and broad in their effect are called sources of systematic risk. Conversely, controllable, internal factors somewhat peculiar to industries and / or firms are referred as sources of unsystematic risk.

8 Risk in a Traditional Sense Systematic risk refers to that portion of total variability in return caused by factors affecting the prices of all securities. Economic, political and sociological changes are sources of systematic risk. Their effect is to cause prices of nearly all individual common stocks and/or all individual bonds to move together in the same manner. e.g.: Recession It is estimated that on an average, about 50 per cent of the variation in a stock s price can be explained by variation in the market index or systematic risk. Unsystematic risk is the portion of the risk that is unique to a firm or industry. Factors such as management capability, consumer preferences and labour unrest cause variability of returns in a firm. Unsystematic risk factors are largely independent of factors affecting securities markets in general.

9 Systematic Risk: Market Risk Variability in return on most common stocks that is due to basic sweeping changes in investor expectations is referred to as market risk. Market risk is caused by investor reaction to both tangible and intangible events. Tangible events may include events such as political, social or economic. Intangible events are related to market psychology. For example, herd mentality may affect investors which leads to overreaction. Two other factors, interest rate and inflation, are important factors behind market risk and form part of the larger category of systematic or uncontrollable influences.

10 Systematic Risk: Interest Rate Risk Interest rate risk refers to the uncertainty of future market values and of the size of future income, caused by fluctuations in the general level of interest rates. The level of Government borrowings is often a major factor in the rise and fall of interest rates. In addition to the direct, systematic effect on bonds, there are indirect effects on common stocks. First, lower or higher interest rates make the purchase of stocks on margin (using borrowed funds) more or less attractive. Secondly, when interest rates rise or fall, corporate incomes and therefore prices of shares also get affected.

11 Systematic Risk: Purchasing Power Risk Purchasing risk is the uncertainty of the purchasing power of the amounts to be received refers to the impact of inflation or deflation For example, in times of inflation, required rates of return will be adjusted upwards.

12 A Scientific Approach to Predictions A more precise measurement of uncertainty about predictions would be to gauge the extent to which actual return is likely to differ from predicted return that is, the dispersion around the expected return. Security analysts use the probability distribution of return to specify expected return as well as risk. The expected return is the weighted average of the returns. That is if we multiply each return by its associated probability and add the results together, we get a weighted average return.

13 E.g. 1 (Stock A) of Weighted Average Return Return (%) (1) Probability (2) (1) x (2)

14 E.g. 2 (Stock B) of Weighted Average Return Return (%) (1) Probability (2) (1) x (2) In the two examples, the two stocks have identical expected average returns, but the dispersions are different. The spread or dispersion of the probability distribution can be measured by the degree of variation around the expected return.

15 Measures of Dispersion In general, the expected return, variance and standard deviation of outcomes can be shown as: n n R = P i O i, σ 2 = P i (O i R) 2, σ = σ 2 t=1 t=1 R = expected return, σ 2 = variance of expected return, σ = standard deviation of expected return, P = probability, O = outcome, n = total number of different outcomes

16 Return Expected Return (1) E.g.1: Stock A Difference Squared (2) Probability (3) (2) X (3) 7-10 = = = = = = = Variance 2.10 Standard Deviation

17 Return Expected Return (1) E.g.2: Stock B Difference Squared (2) Probability (3) (2) X (3) 9-10 = = = Variance 0.60 Standard Deviation Note: The larger variation about the expected return for Stock A is indicated in its variance relative to Stock B. The variability of return around the expected average is thus a quantitative description of risk. Moreover, this measure of risk is simply a proxy or surrogate for risk because other measures could be used.

18 Modern Portfolio Theory

19 Introduction Modern portfolio theory is in a way the opposite of traditional stock picking. It is the creation of economists, who try to understand the market as a whole, rather than business analysts, who look for what makes each investment opportunity unique. Investments are described statistically, in terms of their expected long-term return rate and their expected short-term volatility. The volatility is equated with "risk", measuring how much worse than average an investment's bad years are likely to be. The goal is to identify the investor s acceptable level of risk tolerance, and then to find a portfolio with the maximum expected return for that level of risk.

20 Types of Investors A risk-averse investor will choose among investments with equal rates of return, the investment with lowest standard deviation. Similarly, if investments have equal risk (standard deviations), the investor would prefer the one with higher return. A risk-neutral investor does not consider risk, and would always prefer investments with higher returns. A risk-seeking investor likes investments with higher risk irrespective of the rates of return. In reality, most (if not all) investors are risk-averse.

21 Portfolio Theory A portfolio is a bundle or a combination of individual assets or securities. Portfolio theory makes two basic assumptions: It is based on the assumption that investors are risk-averse. The second assumption of the portfolio theory is that the returns of assets are normally distributed. A risk-averse investor will prefer a portfolio with the highest expected return for a given level of risk or prefer a portfolio with the lowest level of risk for a given level of expected return.

22 Volatility and Investor s Time Horizon The volatility of an investment is measured by the standard deviation of its rate of return. Usually, if two identical groups of people invested in portfolios consisting of either Stocks or Bonds, the average gain of the Stocks group would be greater than that of the Bonds group, but the Stocks group would have a larger number of investors who actually lost money. Volatility increases the investor s risk of loss of principal, and this risk worsens as an investor s time horizon shrinks. So all other things being equal, an investor would like to minimize volatility in her portfolio.

23 Risk Return Relationship of Different Financial Instruments

24 Averages and Standard Deviations, to (Source: I M Pandey) Securities Arithmetic mean Standard deviation Risk premium * Risk premium # Ordinary shares (RBI Index) Call money market Long-term government bonds Day treasury bills Inflation *Relative to 91-Days T-bills. # Relative to long-term government bonds.

25 Portfolio Diversification If, however, the investor limits herself to low-risk securities, the returns will also be low. So what the investor really wants to do is include some higher growth, higher risk securities in her portfolio, but combine them in a smart way, so that some of their fluctuations cancel each other out. In statistical terms, you're looking for a combined standard deviation that's low, relative to the standard deviations of the individual securities. The result should give the investor a high average rate of return, with less of the harmful fluctuations. The science of risk-efficient portfolios is associated mainly with Harry Markowitz and Bill Sharpe.

26 Portfolio Analysis

27 Portfolio Return The return of a portfolio is equal to the weighted average of the returns of individual assets (or securities) in the portfolio with weights being equal to the proportion of investment value in each asset. n ř p = x i ř i i=1 Where ř p = expected return of the portfolio x i = proportion of funds invested in security i ř i = expected return of security i n = number of securities in the portfolio

28 Portfolio Risk The risk involved in individual securities can be measured by standard deviation or variance. When two securities are combined, we need to consider their interactive risk, or covariance. If the rates of return of two securities move together, we say their interactive risk or covariance, is positive. If rates of return are independent, covariance is zero. Inverse movement results in covariance that is negative.

29 Portfolio Risk Mathematically, covariance is defined as 1 N cov xy = --- [R x Ř x ][R y Ř y ] N Where the probabilities are equal and cov xy = covariance between x and y R x = return on security x R y = return on security y Ř x = expected return to security x Ř y = expected return to security y N = number of observations

30 Calculation of Covariance Year Rx Deviation Rx - Řx Ry Deviation Ry - Řy Product of Deviations Řx = 56/4 =14 Cov xy = -42/4 = Řy= 48/4 = 12-42

31 Portfolio Risk: Two-Asset Case The portfolio variance or standard deviation depends on the co-movement of returns on two assets. Covariance of returns on two assets measures their co-movement. The formula for calculating covariance of returns of the two securities X and Y is as follows: Covariance XY = Standard deviation X * Standard deviation Y * Correlation XY The variance of two-security portfolio is given by the following equation: w w 2w w Co var p x x y y x y xy w w 2w w Cor x x y y x y x y xy

32 Portfolio Risk The coefficient of correlation is another measure designed to indicate the similarity or dissimilarity in the behaviour of two variables. We define r xy = cov xy / σ x σ y, where: r xy = coefficient of correlation between x and y cov xy = covariance between x and y σ x = standard deviation of x σ x = standard deviation of y The coefficient of correlation is, essentially, the covariance taken not as an absolute value but relative to the standard deviations of the individual securities (variables). It indicates, in effect, how much x and y vary together as a proportion of their combined individual variations, measured by σ x σ y.

33 Portfolio Example: 2 asset case Let us make the following assumptions: We have two securities P (expected return 15%, standard deviation 50%) and Q (expected return 20%, standard deviation 30%), and correlation coefficient of -0.60, i.e. negative correlation. We decide to allocate 40% of the funds in P and 60% in Q. The expected return of the portfolio is (0.40 x 15) + (0.60 x 20) = 18%. The variance of the portfolio = σ p2 = (0.40) 2 (50) 2 + (0.60) 2 (30) 2 + 2(0.40)(0.60)(-0.60)(50)(30) = = 292 The standard deviation of the portfolio = σ p = 292 = 17.09

34 Reduction of Portfolio Risk through Diversification

35 Portfolio Standard Deviation Correlation Coefficients Portfolio Standard Deviations Diversification reduces risk in all cases except when the securities are perfectly positively correlated. As correlation coefficient declines the portfolio standard deviation also declines

36 Portfolio Risk Depends on Correlation between Assets When correlation coefficient of returns on individual securities is perfectly positive (i.e., cor = 1.0), then there is no advantage of diversification. The weighted standard deviation of returns on individual securities is equal to the standard deviation of the portfolio. We may therefore conclude that diversification always reduces risk provided the correlation coefficient is less than 1.

37 Portfolios with more than two securities As the number of securities added to a portfolio increases, the standard deviation of the portfolio becomes smaller and smaller. Theoretically, an investor can make the portfolio risk arbitrarily small by including a large number of securities with negative or zero correlation in the portfolio. However, in reality, typically securities show some positive correlation, that is above zero but less than the perfectly positive value (+1). As a result, diversification results in some reduction in total portfolio risk but not in complete elimination of risk. Moreover, the benefits of diversification is exhausted quite rapidly. Most of the reduction in portfolio standard deviation occurs by the time the portfolio size increases to 25 to 30 securities. By combining securities into a portfolio, unsystematic risk specific to different securities is cancelled out, but market related risk or systematic risk remains.

38 Diversification of risk Risk (Portfolio standard deviation) Unsystematic or diversifiable risk) Systematic risk No. of securities held in the portfolio

39 Portfolio Selection

40 Portfolio Diversification and the Efficient Frontier Suppose we have data for a collection of securities (like the S & P 500 stocks, for example), and we graph the return rates and standard deviations for these securities, and for all portfolios we can get by allocating among them. Markowitz showed that we get a region bounded by an upward-sloping curve, which he called the efficient frontier. It's clear that for any given value of standard deviation, we would like to choose a portfolio that gives us the greatest possible rate of return; so you always want a portfolio that lies up along the efficient frontier, rather than lower down, in the interior of the region. This is the first important property of the efficient frontier: it's where the best portfolios are. The second important property of the efficient frontier is that it's curved, not straight.

41 Efficient Frontier This is the key to how diversification lets the investor improve her reward-to-risk ratio. To see why, imagine a 50/50 allocation between just two securities. Assuming that the year-to-year performance of these two securities is not perfectly in sync -- then the standard deviation of the 50/50 allocation will be less than the average of the standard deviations of the two securities separately. Graphically, this stretches the possible allocations to the left of the straight line joining the two securities. In statistical terms, this effect is due to lack of covariance. The smaller the covariance between the two securities -- the more out of sync they are -- the smaller the standard deviation of a portfolio that combines them. The ultimate would be to find two securities with negative covariance (very out of sync: the best years of one happen during the worst years of the other, and vice versa).

42 Average Rate of Return Example of Two-Security Case Standard Deviation

43 Investment Opportunity Set: The N-Asset Case We have the opportunity to use a large number of shares quoted in say the BSE and NSE. We could construct a large number of portfolios combining these shares in different proportions. However, depending on the risk profile of the investor, she will choose a risk-return mix which suits her. An efficient portfolio is one which has the highest expected return for a given level of risk. The efficient frontier is the frontier formed by the set of efficient portfolios. All portfolios on the efficient frontier are efficient portfolios. All other portfolios which lie outside the efficient frontier are inefficient portfolios.

44 Investment Opportunity Set: The N- Asset Case An efficient portfolio is one that has the highest expected returns for a given level of risk. The efficient frontier is the frontier formed by the set of efficient portfolios. All other portfolios, which lie outside the efficient frontier, are inefficient portfolios. Return P B C x x x A x D Q x x x R Risk,

45 Optimum Portfolio In general an optimum portfolio has either (i) more return than any other portfolio with the same risk, or (ii) less risk than any other portfolio with the same return. If we plot the standard deviation of the portfolio (x axis) against the return of the portfolio (y axis), for various combinations of portfolio risk and return with varying weights of the securities in the portfolio, we can arrive at an optimum portfolio efficiency locus. This efficiency locus is also called the efficient frontier. Hence an investor can choose between portfolios that provide the highest return for a given level of risk or the lowest risk for a given level of return. However, the Markowitz model is extremely demanding in its data needs and computational requirements. In the real world of investments, security analysts follow individual stocks and often do not track correlation between stocks.

46 Combining Risk-Free Asset and Risky Asset

47 Combining a Risk-Free Asset and a Risky Asset One approach to constructing a portfolio opportunity set is to have a mix of risky and risk-free securities. Let us assume that the risk free security f has an expected return of 5 per cent and a risky security j has an expected return of 15 per cent and a standard deviation of 6 per cent. The weights assumed are 50 per cent each. Portfolio return R P = wr j + (1-w)R f = 0.5 x (1-0.5) x 0.05 = = 0.10 or 10% Portfolio standard deviation σ P = wσ j = 0.5 x 0.06 = 0.03 or 3% Note: The risk free security has zero standard deviation, and the covariance between the risky and risk free security is also zero.

48 Risk-return Analysis for a Portfolio of a Risky Asset and a Risk-free Asset Risky security Weights (%) Risk-free security Expected return R P (%) Standard deviation σ P (%) Note: It will be seen that it is possible for the investor to borrow at the riskfree rate and invest in the risky security.

49 Mix of one Risk-free Asset and one Risky Asset We can graphically illustrate the risk-return relationship for various combinations of a risk-free security and a risky security, and the resulting opportunity set. Point B represents 100% investment in the risky security expected to yield 15% return and 6% standard deviation. The investor can also borrow at the risk free rate and invest in the risky security. The portfolio opportunity set is a straight line. This is because the correlation and covariance of any asset with a risk-free asset are zero, so that any combination of an asset or portfolio with the risk-free asset generates a linear return and risk function. The dominant line is the one that is tangent to the efficient frontier. This dominant line is the capital market line (CML), and all investors should target points along this line depending upon risk preferences.

50 Expected Return Risk-return relationship for portfolio of one risky asset and one risk free asset A B 5 R f Risk-free asset Standard Deviation

51 The Sharpe Ratio Earlier we saw that the efficient frontier is where the most risk-efficient portfolios are, for a given collection of securities. The Sharpe Ratio helps us find the best possible proportion of these securities to use, in a portfolio that can also contain a risk-free security. The definition of the Sharpe Ratio is: S(x) = ( r x - R f ) / StdDev(x), where x is some investment, r x is the average annual rate of return of x R f is the best available rate of return of a "risk-free" security StdDev(x) is the standard deviation of r x The Sharpe Ratio is a direct measure of reward-to-risk. To see how it helps us in creating a portfolio, consider the diagram of the efficient frontier again, this time with the risk-free asset drawn in.

52 Capital Market Line We have in a market situation a large number of investors holding portfolios consisting of a risk-free security and multiple risky securities. However, out of these available portfolios an efficient portfolio is one that has the highest expected returns for a given level of risk. The efficient frontier is the frontier formed by the set of efficient portfolios. All other portfolios, which lie outside the efficient frontier are inefficient portfolios. Capital allocation lines denote feasible portfolios consisting of a risk-free security and a portfolio of risky securities. The capital market line (CML) is the capital allocation line which is at a tangent to the efficient frontier. Thus the point X is the optimum risky portfolio, which can be combined with the risk-free asset. The slope of CML is the Sharpe Ratio.

53 Capital Market Line

54 Calculation of Risk The total risk of an investment consists of two components: diversifiable and non diversifiable. Diversifiable, or unsystematic risk, represents the portion of an investment s risk that can be eliminated by holding enough stocks. Nondiversifiable, or systematic risk, is external to an industry and/or business, and is attributed to broad forces such as inflation, war or political events. Such forces impact all investments and are therefore not unique to a given instrument. Total risk = Diversifiable risk + Nondiversifiable risk Studies have shown that by carefully selecting as few as fifteen securities for a portfolio, diversifiable risk can almost be eliminated.

55 Capital Asset Pricing Model The CAPM is a centre piece of modern financial theory, as it gives Treasury Managers and other financial professionals a meaningful and manageable way of thinking about the required return on a risky investment. The model is attractive because it specifies two kinds of risks; those which you can diversify away and those which you cannot i.e. market risk. Market risk is measured by beta, which is a measure of the extent to which a particular investment is affected by a change in the aggregate value of all assets in the economy. As these risks are not diversifiable, the required rate of return on an asset increases with its beta.

56 The Concept of Beta Beta measures nondiversifiable risk. Beta shows how the price of a security responds to market forces. In effect, the more responsive the price of a security is to changes in the market, the higher will be its beta. Beta is calculated by relating the returns on a security with the returns for the market. Market return is measured by the average return of a large sample of stocks, such as BSE Index. The beta for the overall market is equal to 1.00 and other betas are viewed in relation to this value. Betas can be positive or negative.

57 Capital Asset Pricing Model Using beta as the measure of nondiversifiable risk, the CAPM is used to define the required return on a security according to the following equation: R t = R f + β s (R m R f ) where R t = the return required on the investment R f = the return that can be earned on a risk free investment (say Treasury Bill) R m = the average return on all securities (e.g. BSE Stock Index) β s = the security s beta (systematic) risk To illustrate, say a security s beta is 1.5, risk free return is 10% and expected return on the market portfolio is 18%, then the required rate of return of the security is (18-10) = 22%

58 Assumptions of CAPM (A) Perfect Capital Market: All investors have the same information about securities:- There are no restrictions on investments (buying and selling) Securities are completely divisible There are no transaction costs There are no taxes Competitive market means no single investor can affect market price significantly (B) Investors preferences: Investors are risk averse:- Investors have homogenous expectations regarding the expected returns, variances and correlation of returns among all securities. Investors seek to maximise the expected utility of their portfolios over a single period planning horizon.

59 Capital Asset Pricing Model Example Assume a security with a beta of 1.4 is being considered at a time when the risk free rate is 6 per cent and the market return is expected to be 14 per cent. Substituting these data into the CAPM equation, we get R t = 6% + [1.4 x (14% - 6%)] = 6% + [1.4 x 8%] = 6% % = 17.2% If say market return is -14% (falling market), then R t = 6% + [1.4 x (-14% - 6%)] = -22%.

60 The Security Market Line When the CAPM is depicted graphically, it is called the Security Market Line (SML). Plotting SML, we find that it is a straight line. It tells us that the required return an investor should earn in the market place for different levels of beta. The CAPM can be plotted using the above equation. In the earlier example, make beta zero and the required return is 6 per cent. Using various levels of beta, we end up with the combination of risk (beta) and required return. If beta is 1, then reqd. return = 6% + [1.00(14-6)%] = 14%. If beta is 0.50, then reqd. return = 6%+ [0.50(14-6)%] =10%. If beta is 2.00, then reqd. return = 6% + [2.00(14-6)%] = 22%

61 Security Market Line Required Return (%) Risk Beta

62 CML vs. SML What is the difference between CML and SML? The CML represents the risk premiums of efficient portfolios as a function of portfolio standard deviation. The SML, on the other hand, depicts individual security risk premium as a function of security risk. The individual security risk is measured by the security s beta. Beta reflects the contribution of the security to the portfolio risk. If a security s return is perfectly positively correlated with the return on the market portfolio, then CML totally coincides with SML with the same slope.

63 The Concept of EVA

64 The Definition of EVA Economic Value Added (EVA) is a measure of economic profit. It measures the profitability of a company after taking into account the cost of all capital including equity. Concept introduced by Stern Stewart & Co. This concept states that in order for a firm to earn genuine profits, not only must these profits be sufficient to cover the firm s operating costs, but they must also cover the cost of capital. Only when these conditions are fulfilled, can the business claim to have earned a profit. It is the post-tax return on capital employed (adjusted for the tax shield on debt) minus the cost of capital employed. It is those companies which earn higher returns than cost of capital, that create value. Those companies which earn lower returns than cost of capital are destroyers of shareholder value.

65 Calculation of EVA EVA = NOPAT c* x Capital EVA = Capital (r-c*) c*= cost of capital Capital = economic book value of the capital employed in the firm r = return on capital = NOPAT/ Capital

66 Example of EVA Calculation Balance Sheet as on P&L Statement for the Year Ended Liabilities Assets Net sales: 400 Equity 200 Debt 200 Total 400 Fixed assets 320 Net current assets 80 Total 400 The company s NOPAT is: PBIT (1-tax rate) = 60 (1-0.3) = Rs. 42 million Cost of goods sold 340 PBIT 60 Interest 20 PBT 40 Tax (30%) 12 PAT 28 Given a capital of Rs.400 million, the company s return on capital is 42/400 = 10.5%

67 Components of EVA Cost of Capital: Providers of capital (shareholders and lenders) want to be suitably compensated for investing capital in the firm. The weighted average cost of capital = (Cost of equity) (Proportion of equity in the capital employed) + (Cost of preference capital) (Proportion of preference capital in the capital employed) + (Pre-tax cost of debt)(1-tax rate) (Proportion of debt in the capital employed)

68 Economic Value Added (EVA) vs Market Value Added (MVA) EVA is perceived as a powerful tool as it is a performance measure that is linked most directly, both theoretically and empirically, to a measure called Market Value Added (MVA). MVA is the difference between the market value of an enterprise and the capital contributed by shareholders and lenders. The ultimate objective of every firm should be to produce as much MVA as possible. No matter what goods or services they produce, all companies share one thing in common: they all are or should be in the business of creating wealth.

69 EVA vs MVA From the perspective of modern financial theory, MVA is nothing more or less than the net present value, or NPV, of a company. If we think of a company as an agglomeration of investment projects, MVA is the stock market s estimate of the aggregate net present value of all of them both those already in place and those the investors anticipate will be undertaken in the future. One way that managers can evaluate on whether their own share is over or under-valued is to make their own estimate of the aggregate NPV of the company and compare it with the company s MVA. If the MVA is significantly lower, then the managers should ask themselves why the market s judgement differs from their own-because they have inside information, or because they have failed to communicate the company strategy effectively, or because the market is being more objective.

70 EVA vs MVA MVA itself is not much use as a guide to day-to-day decision-making or long-term planning. Firstly changes in the overall level of the stock market can overwhelm the contribution of management actions in the short run. Secondly, MVA can be calculated only if a company is publicly traded and has a market price. Thirdly, even for public companies, MVA can be calculated only at the consolidated level; there is no MVA for a division, business unit, subsidiary, or product line. As there is no clear way to manage directly for increases in MVA. As a result, managers have to focus on some internal measure of performance that is closely linked to the external MVA verdict and that s where EVA becomes important.

71 EVA vs MVA With EVA managers would finally have a current period performance measure tied directly to the value of the firm. Algebraically, MVA = the present value of future EVA Hence, the way to manage for a higher share price for greater shareholder wealth is to manage for increases in EVA.