13 Return, Risk, and the Security Market Line

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13 Return, Risk, and the Security Market Line Prepared by Anne Inglis

Key Concepts and Skills Know how to calculate expected returns and standard deviations for individual securities and portfolios Understand the principle of diversification and the role of correlation Understand systematic and unsystematic risk Understand beta as a measure of risk and the security market line © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Chapter Outline Expected Returns and Variances Portfolios Announcements, Surprises, and Expected Returns Risk: Systematic and Unsystematic Diversification and Portfolio Risk Systematic Risk and Beta The Security Market Line Arbitrage Pricing Theory Summary and Conclusions © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Expected Returns 13.1 LO1 Expected returns are based on the probabilities of possible outcomes In this context, “expected” means average if the process is repeated many times The “expected” return does not even have to be a possible return Use the following example to illustrate the mathematical nature of expected returns: Consider a game where you toss a fair coin: If it is Heads then student A pays student B $1. If it is Tails then student B pays student A $1. Most students will remember from their statistics class that the expected value is $0 (=.5(1) + .5(-1)). That means that if the game is played over and over then each student should expect to break-even. Point out that the expected return of zero is not one of the possible outcomes. However, if the game is only played once, then one student will win $1 and one will lose $1. © 2013 McGraw-Hill Ryerson Limited

Expected Returns – Example 1 LO1 Suppose you have predicted the following returns for stocks C and T in three possible states of nature. What are the expected returns? State Probability C T Boom 0.3 0.15 0.25 Normal 0.5 0.10 0.20 Recession ??? 0.02 0.01 RC = .3(.15) + .5(.10) + .2(.02) = .099 = 9.9% RT = .3(.25) + .5(.20) + .2(.01) = .177 = 17.7% What is the probability of a recession? 0.2 Some students forget that the probabilities have to total to 1.0 or 100%. If the risk-free rate is 6.15%, what is the risk premium? Stock C: 9.99 – 6.15 = 3.84% Stock T: 17.7 – 6.15 = 11.55% © 2013 McGraw-Hill Ryerson Limited

Expected Returns – Example 1 continued LO1 This example can also be done in a spreadsheet Click on the Excel link to see this © 2013 McGraw-Hill Ryerson Limited

Variance and Standard Deviation LO1 Variance and standard deviation still measure the volatility of returns You can use unequal probabilities for the entire range of possibilities Weighted average of squared deviations It’s important to point out that these formulas are for populations, unlike the formulas in chapter 12 that were for samples (dividing by n-1 instead of n). Remind the students that standard deviation is the square root of the variance. © 2013 McGraw-Hill Ryerson Limited

Variance and Standard Deviation – Example 1 LO1 Consider the previous example. What is the variance and standard deviation for each stock? Stock C 2 = .3(.15-.099)2 + .5(.1-.099)2 + .2(.02-.099)2 = .002029  = .045 Stock T 2 = .3(.25-.177)2 + .5(.2-.177)2 + .2(.01-.177)2 = .007441  = .0863 © 2013 McGraw-Hill Ryerson Limited

Variance and Standard Deviation – Example continued LO1 This can also be done in a spreadsheet Click on the Excel icon to see this © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Quick Quiz I LO1 Consider the following information: State Probability ABC, Inc. Boom .25 .15 Normal .50 .08 Slowdown .15 .04 Recession .10 -.03 What is the expected return? What is the variance? What is the standard deviation? E(R) = .25(.15) + .5(.08) + .15(.04) + .1(-.03) = .0805 or 8.05% Variance = .25(.15-.0805)2 + .5(.08-.0805)2 + .15(.04-.0805)2 + .1(-.03-.0805)2 = .002675 Standard Deviation = .051717985 © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Portfolios 13.2 LO1 A portfolio is a collection of assets An asset’s risk and return is important in how it affects the risk and return of the portfolio The risk-return trade-off for a portfolio is measured by the portfolio expected return and standard deviation, just as with individual assets © 2013 McGraw-Hill Ryerson Limited

Example: Portfolio Weights LO1 Suppose you have $15,000 to invest and you have purchased securities in the following amounts. What are your portfolio weights in each security? $2000 of ABC $3000 of DEF $4000 of GHI $6000 of JKL ABC: 2/15 = .133 DEF: 3/15 = .2 GHI: 4/15 = .267 JKL: 6/15 = .4 Show the students that the sum of the weights = 1 © 2013 McGraw-Hill Ryerson Limited

Portfolio Expected Returns LO1 The expected return of a portfolio is the weighted average of the expected returns for each asset in the portfolio You can also find the expected return by finding the portfolio return in each possible state and computing the expected value as we did with individual securities © 2013 McGraw-Hill Ryerson Limited

Example: Expected Portfolio Returns LO1 Consider the portfolio weights computed previously. If the individual stocks have the following expected returns, what is the expected return for the portfolio? ABC: 19.65% DEF: 8.96% GHI: 9.67% JKL: 8.13% E(RP) = .133(19.65) + .2(8.96) + .267(9.67) + .4(8.13) = 10.24% Click the Excel icon for an example © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Portfolio Variance LO1 Compute the portfolio return for each state: RP = w1R1 + w2R2 + … + wmRm Compute the expected portfolio return using the same formula as for an individual asset Compute the portfolio variance and standard deviation using the same formulas as for an individual asset © 2013 McGraw-Hill Ryerson Limited

Example: Portfolio Variance LO1 Consider the following information Invest 60% of your money in Asset A State Probability A B Boom .5 70% 10% Bust .5 -20% 30% What is the expected return and standard deviation for each asset? What is the expected return and standard deviation for the portfolio? If A and B are your only choices, what percent are you investing in Asset B? Asset A: E(RA) = .5(70) + .5(-20) = 25% Variance(A) = .5(70+25)2 + .5(-20-25)2 = 2,025 Std. Dev.(A) = 45% Asset B: E(RB) = .5(10) + .5(30) = 20% Variance(B) = .5(10-20)2 + .5(30-20)2 = 100 Std. Dev.(B) = 10% Portfolio Portfolio return in boom = .6(70) + .4(10) = 46% Portfolio return in bust = .5(-20) + .5(30) = 0% Expected return = .5(46) + .5(0) = 23 or Expected return = .6(25) + .4(20) = 23 Variance of portfolio = .5(46-23)2 + .5(0-23)2 = 529 Standard deviation = 23% Note that the variance is NOT equal to .5(2025) + .5(100) = 1062.5 and Standard deviation is NOT equal to .5(45) + .5(10) = 27.5% © 2013 McGraw-Hill Ryerson Limited

Portfolio Variance Example continued LO1 This can also be done in a spreadsheet Click on the Excel icon to see this © 2013 McGraw-Hill Ryerson Limited

Another Way to Calculate Portfolio Variance LO1 Portfolio variance can also be calculated using the following formula: © 2013 McGraw-Hill Ryerson Limited

Figure 13.1 – Different Correlation Coefficients LO2 © 2013 McGraw-Hill Ryerson Limited

Figure 13.1 – Different Correlation Coefficients LO2 © 2013 McGraw-Hill Ryerson Limited

Figure 13.1 – Different Correlation Coefficients LO2 © 2013 McGraw-Hill Ryerson Limited

Figure 13.2 – Graphs of Possible Relationships Between Two Stocks LO2 © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Diversification LO2 There are benefits to diversification whenever the correlation between two stocks is less than perfect (p < 1.0) If two stocks are perfectly positively correlated, then there is simply a risk-return trade-off between the two securities. © 2013 McGraw-Hill Ryerson Limited

Diversification – Figure 13.4 LO2 © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Terminology LO2 Feasible set (also called the opportunity set) – the curve that comprises all of the possible portfolio combinations Efficient set – the portion of the feasible set that only includes the efficient portfolio (where the maximum return is achieved for a given level of risk, or where the minimum risk is accepted for a given level of return) Minimum Variance Portfolio – the possible portfolio with the least amount of risk © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Quick Quiz II LO1 Consider the following information State Probability X Z Boom .25 15% 10% Normal .60 10% 9% Recession .15 5% 10% What is the expected return and standard deviation for a portfolio with an investment of $6,000 in asset X and $4,000 in asset Z? Portfolio return in Boom: .6(15) + .4(10) = 13% Portfolio return in Normal: .6(10) + .4(9) = 9.6% Portfolio return in Recession: .6(5) + .4(10) = 7% Expected return = .25(13) + .6(9.6) + .15(7) = 10.06% Variance = .25(13-10.06)2 + .6(9.6-10.06)2 + .15(7-10.06)2 = 3.6924 Standard deviation = 1.92% Compare to return on X of 10.5% and standard deviation of 3.12% And return on Z of 9.4% and standard deviation of .48% © 2013 McGraw-Hill Ryerson Limited

Expected versus Unexpected Returns 13.3 LO2 Realized returns are generally not equal to expected returns There is the expected component and the unexpected component At any point in time, the unexpected return can be either positive or negative Over time, the average of the unexpected component is zero © 2013 McGraw-Hill Ryerson Limited

Announcements and News LO2 Announcements and news contain both an expected component and a surprise component It is the surprise component that affects a stock’s price and therefore its return This is very obvious when we watch how stock prices move when an unexpected announcement is made or earnings are different than anticipated © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Efficient Markets LO2 Efficient markets are a result of investors trading on the unexpected portion of announcements The easier it is to trade on surprises, the more efficient markets should be Efficient markets involve random price changes because we cannot predict surprises © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Systematic Risk 13.4 LO3 Risk factors that affect a large number of assets Also known as non-diversifiable risk or market risk Includes such things as changes in GDP, inflation, interest rates, etc. © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Unsystematic Risk LO3 Risk factors that affect a limited number of assets Also known as unique risk and asset-specific risk Includes such things as labor strikes, shortages, etc. © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Returns LO3 Total Return = expected return + unexpected return Unexpected return = systematic portion + unsystematic portion Therefore, total return can be expressed as follows: Total Return = expected return + systematic portion + unsystematic portion © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Diversification 13.5 LO2 Portfolio diversification is the investment in several different asset classes or sectors Diversification is not just holding a lot of assets For example, if you own 50 internet stocks, you are not diversified However, if you own 50 stocks that span 20 different industries, then you are diversified © 2013 McGraw-Hill Ryerson Limited

Table 13.8 – Portfolio Diversification LO2 © 2013 McGraw-Hill Ryerson Limited

The Principle of Diversification LO2 & LO3 Diversification can substantially reduce the variability of returns without an equivalent reduction in expected returns This reduction in risk arises because worse than expected returns from one asset are offset by better than expected returns from another However, there is a minimum level of risk that cannot be diversified away and that is the systematic portion © 2013 McGraw-Hill Ryerson Limited

Figure 13.6 – Portfolio Diversification LO2 & LO3 © 2013 McGraw-Hill Ryerson Limited

Diversifiable (Unsystematic) Risk LO3 The risk that can be eliminated by combining assets into a portfolio Synonymous with unsystematic, unique or asset-specific risk If we hold only one asset, or assets in the same industry, then we are exposing ourselves to risk that we could diversify away The market will not compensate investors for assuming unnecessary risk © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Total Risk LO3 Total risk = systematic risk + unsystematic risk The standard deviation of returns is a measure of total risk For well diversified portfolios, unsystematic risk is very small Consequently, the total risk for a diversified portfolio is essentially equivalent to the systematic risk © 2013 McGraw-Hill Ryerson Limited

Systematic Risk Principle 13.6 LO3 There is a reward for bearing risk There is not a reward for bearing risk unnecessarily The expected return on a risky asset depends only on that asset’s systematic risk since unsystematic risk can be diversified away © 2013 McGraw-Hill Ryerson Limited

Measuring Systematic Risk LO3 How do we measure systematic risk? We use the beta coefficient to measure systematic risk What does beta tell us? A beta of 1 implies the asset has the same systematic risk as the overall market A beta < 1 implies the asset has less systematic risk than the overall market A beta > 1 implies the asset has more systematic risk than the overall market © 2013 McGraw-Hill Ryerson Limited

Figure 13.7 – High and Low Betas © 2013 McGraw-Hill Ryerson Limited

Table 13.10 – Beta Coefficients for Selected Companies LO3 © 2013 McGraw-Hill Ryerson Limited

Total versus Systematic Risk LO3 Consider the following information: Standard Deviation Beta Security C 20% 1.25 Security K 30% 0.95 Which security has more total risk? Which security has more systematic risk? Which security should have the higher expected return? Security K has the higher total risk Security C has the higher systematic risk Security C should have the higher expected return © 2013 McGraw-Hill Ryerson Limited

Example: Portfolio Betas LO3 Consider the previous example with the following four securities Security Weight Beta ABC .133 3.69 DEF .2 0.64 GHI .267 1.64 JKL .4 1.79 What is the portfolio beta? .133(3.69) + .2(.64) + .267(1.64) + .4(1.79) = 1.773 Which security has the highest systematic risk? ABC Which security has the lowest systematic risk? DEF Is the systematic risk of the portfolio more or less than the market? MORE © 2013 McGraw-Hill Ryerson Limited

Beta and the Risk Premium 13.7 LO3 Remember that the risk premium = expected return – risk-free rate The higher the beta, the greater the risk premium should be Can we define the relationship between the risk premium and beta so that we can estimate the expected return? YES! © 2013 McGraw-Hill Ryerson Limited

Figure 13.8A – Portfolio Expected Returns and Betas LO4 Rf Based on the example in the book. Point out that there is a linear relationship between beta and expected return. Ask if the students remember the form of the equation for a line. Y = aX + b E(R) = slope (Beta) + y-intercept The y-intercept is = the risk-free rate, so all we need is the slope © 2013 McGraw-Hill Ryerson Limited

Reward-to-Risk Ratio: Definition and Example LO4 The reward-to-risk ratio is the slope of the line illustrated in the previous example Slope = (E(RA) – Rf) / (A – 0) Reward-to-risk ratio for previous example = (20 – 8) / (1.6 – 0) = 7.5 What if an asset has a reward-to-risk ratio of 8 (implying that the asset plots above the line)? What if an asset has a reward-to-risk ratio of 7 (implying that the asset plots below the line)? Ask students if they remember how to compute the slope of a line: rise / run If the reward-to-risk ratio = 8, then investors will want to buy the asset. This will drive the price up and the return down (remember time value of money and valuation). When should trading stop? When the reward-to-risk ratio reaches 7.5. If the reward-to-risk ratio = 7, then investors will want to sell the asset. This will drive the price down and the return up. When should trading stop? When the reward-to-risk ratio reaches 7.5. © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Market Equilibrium LO4 In equilibrium, all assets and portfolios must have the same reward-to-risk ratio and they all must equal the reward-to-risk ratio for the market © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Security Market Line LO4 The security market line (SML) is the representation of market equilibrium The slope of the SML is the reward-to-risk ratio: (E(RM) – Rf) / M But since the beta for the market is ALWAYS equal to one, the slope can be rewritten Slope = E(RM) – Rf = market risk premium Based on the discussion earlier, we now have all the components of the line: E(R) = [E(RM) – Rf] + Rf © 2013 McGraw-Hill Ryerson Limited

Figure 13.11 – Security Market Line LO4 © 2013 McGraw-Hill Ryerson Limited

The Capital Asset Pricing Model (CAPM) LO4 The capital asset pricing model defines the relationship between risk and return E(RA) = Rf + A(E(RM) – Rf) If we know an asset’s systematic risk, we can use the CAPM to determine its expected return This is true whether we are talking about financial assets or physical assets © 2013 McGraw-Hill Ryerson Limited

Factors Affecting Expected Return LO4 Pure time value of money – measured by the risk-free rate Reward for bearing systematic risk – measured by the market risk premium Amount of systematic risk – measured by beta Mention to student that they need to pay attention to how questions are phrased. Are you being given the expected market return E(Rm) or the market risk premium (E(Rm) – Rf)? © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Example - CAPM LO4 Consider the betas for each of the assets given earlier. If the risk-free rate is 4.5% and the market risk premium is 8.5%, what is the expected return for each? Security Beta Expected Return ABC 3.69 4.5 + 3.69(8.5) = 35.865% DEF .64 4.5 + .64(8.5) = 9.940% GHI 1.64 4.5 + 1.64(8.5) = 18.440% JKL 1.79 4.5 + 1.79(8.5) = 19.715% © 2013 McGraw-Hill Ryerson Limited

Arbitrage Pricing Theory (APT) 13.8 LO1 Similar to the CAPM, the APT can handle multiple factors that the CAPM ignores Unexpected return is related to several market factors © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Quick Quiz What is the difference between systematic and unsystematic risk? What type of risk is relevant for determining the expected return? What is the SML? What is the CAPM? What is the APT? Consider an asset with a beta of 1.2, a risk-free rate of 5% and a market return of 13%. What is the reward-to-risk ratio in equilibrium? What is the expected return on the asset? Reward-to-risk ratio = 13 – 5 = 8% Expected return = 5 + 1.2(8) = 14.6% © 2013 McGraw-Hill Ryerson Limited

© 2013 McGraw-Hill Ryerson Limited Summary 13.9 There is a reward for bearing risk Total risk has two parts: systematic risk and unsystematic risk Unsystematic risk can be eliminated through diversification Systematic risk cannot be eliminated and is rewarded with a risk premium Systematic risk is measured by the beta The equation for the SML is the CAPM, and it determines the equilibrium required return for a given level of risk © 2013 McGraw-Hill Ryerson Limited