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Risk and Return To risk or not to risk, that is the question… Standard deviation and normal distribution normal distribution is completely defined by its mean and standard deviation the probability of abnormally high or low returns depends on the standard deviation Std Devs. from mean -3 -2 -1 0 1 2 3 Cumulative probability 0.1% 2.3 15.9 50.0 84.1 97.7 99.9 Markowitz Portfolio Theory Price changes vs. Normal distribution IBM - Daily % change 1986-2006 Proportion of Days 6 5 4 3 2 1 0 -6 -5 -5 -4 -3 -2 -1 -1 0 1 2 2 3 Daily % Change 4 5 5 6 Calculating mean (or expected) return Probability Return Probability x return .20 -10% -2% .50 +10 5 .30 +30 9 Total 12% Mean or expected return Calculating variance and standard deviation Probability Return .20 -10% .50 .30 Deviation from mean return Probability x squared deviation -22% 96.8 +10 -2 2.0 +30 +18 97.2 Total 196.0 Variance Standard deviation = square root of variance = 14% Calculating variance and standard deviation of Merck returns from past monthly data Month 1 2 3 4 5 6 Total Return Deviation from mean return 5.4% 1.7 - 3.6 13.6 - 3.5 3.2 2.6% - 1.1 - 6.4 10.8 - 6.3 0.4 16.8 Mean: 16.8/6 = 2.8% Variance: 205.4/6 = 34.237 Std dev: Sq root of 34.237 = 5.851% per month Annualised std dev: 5.9 x square root (12) = 20.3% Squared deviation 6.76 1.21 40.96 116.64 39.69 0.16 205.42 Mean and standard deviation mean measures average (or expected return) standard deviation (or variance) measures the spread or variability of returns risk averse investors prefer high mean & low standard deviation 20 15 expected return better 10 5 0 5 10 15 standard deviation 20 Expected portfolio return Portfolio proportion (x) Expected return (r) Proportion x return (xr) Merck .40 10% 4% McDonald .60 15 9 Total 1.00 13% Expected portfolio return Calculating covariance and correlation Prob. Return on: A B .15 .05 .45 .05 .25 .05 -10% -10 +10 +10 +30 +30 Mean Std dev +12 +14 -10% +10 +10 +30 +30 -10 Deviation from mean return: A B -22% -22 -2 -2 +18 +18 +12 +14 Probability x product of deviations -22% -2 -2 +18 +18 -22 + 72.6 + 2.2 + 1.8 - 1.8 + 81.0 - 19.8 Total 136 Covariance Correlation coefficient = covariance (sd A) x (sd B) = 136 14 x 14 = .6944 Calculating covariance and correlation between Merck and McDonald from past monthly data Month 1 2 3 4 5 6 Total Mean Return: Merck McD 5.4% 1.7 - 3.6 13.6 - 3.5 3.2 10.7% - 8.4 1.6 10.2 4.4 - 7.8 16.8 2.8 10.7 1.78 Covariance: 106.1/6 = 17.7 Std dev Merck: 5.9% Std dev McD: 7.7% Corr. co-effic: Cov/(sdMe . sdMcD ) = 17.7/(5.9 x 7.7) = .39 Deviation from mean: Merck McD 2.6% - 1.1 - 6.4 10.8 - 6.3 0.4 8.9% -10.2 - 0.2 8.4 2.6 - 9.6 Product of deviations 23.2 11.2 1.2 90.9 -16.5 - 3.8 106.1 Effect of changing correlations: Portfolio of Merck & McDonald 15 100% McD Expected return % 14 13 corr = .4 corr = 1 12 corr = -1 11 10 100% Merck 9 8 0 1 2 3 4 Std dev % 5 6 7 8 Mean & standard deviation: Portfolio of Merck & McDonald 15 Expected return % 14 100% McD 13 40% Merck 12 11 10 100% Merck 9 8 4 4.5 5 5.5 6 Std dev % 6.5 7 7.5 8 The set of portfolios Expected return A B x x x x x x x x x x x x x x x x x x x x x x Standard deviation The set of portfolios between A and B are efficient portfolios Adding a riskless asset to the efficient frontier tangency portfolio riskless rate Portfolio composition with a riskless asset Regardless of the investor's attitude to risk, he should split his portfolio between the tangency portfolio and the riskless asset. - the tangency portfolio provides the maximum reward per unit of risk - the riskless asset adjusts the level of risk Two basic ideas about risk and return 1. Investors require compensation for risk 2. They care only about a stock's contribution to portfolio risk Capital asset pricing model Expected return Expected market return Risk free rate 0 .5 r = rf + 1.0 (rm - rf ) Beta Capital asset pricing model - example If Treasury bill rate = 5.6% Bristol Myers Squibb beta = Expected market risk premium r = rf + beta (rm - rf ) = 5.6 + .81 (8.4) = 12.4% .81 = 8.4% Testing the CAPM Beta vs. Average Risk Premium Avg Risk Premium 1931-2005 30 20 SML Investors 10 Market Portfolio 0 1.0 Portfolio Beta Testing the CAPM Return vs. Book-to-Market Dollars (log scale)100 High-minus low book-to-market 10 0.1 http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html 2006 1996 1986 1976 1966 1956 1946 1936 1 1926 Small minus big Validity of capital asset pricing model EVIDENCE IS MIXED: 1. Long-run average returns are significantly related to beta. 2. But beta is not a complete explanation. Low beta stocks have earned higher rates of return than predicted by the model. So have small company stocks and stocks with low price to book value ratios. Capital asset pricing model is attractive Because: 1. It is simple and usually gives sensible answers. 2. It distinguishes between diversifiable and non-diversifiable risk. CAPM is controversial BECAUSE: 1. No one knows for sure how to define and measure the market portfolio -- and using the wrong market index could lead to the wrong answers. 2. The model is hard to prove -- or disprove. 3. The model has competitors. The Consumption CAPM • In standard CAPM, investors are concerned with the level and uncertainty of their wealth. (Consumption is outside the model) • In the Consumption CAPM, investors are concerned with the level and uncertainty of their consumption. Stocks that provide low consumption (those with low consumption betas) should have low expected returns. • Is the Consumption CAPM useful? - It has the advantage that you don’t have to identify the market portfolio. - Unfortunately consumption is difficult to measure (especially total consumption for everyone). -Consumption CAPM is difficult to apply for practical use. Arbitrage Pricing Theory (APT) APT assumes that r = a + b1 (rfactor 1 ) + b2 (rfactor 2 ) + .... + noise Suppose that a diversified portfolio has no exposure to any factor. It is essentially risk-free and should offer a return of rf. So a = rf. The expected risk premium on a portfolio that is exposed only to factor 1 (say) should vary in proportion to its exposure to that factor. If a portfolio is exposed to several factors then its risk will vary in proportion to those factors. So r - rf = b1 (rfactor 1 - rf ) + b2 (rfactor 2 - rf ) + ... Arbitrage pricing theory (APT) Preserves distinction between diversifiable and non-diversifiable risk CAPM and APT can both hold - e.g. CAPM implies one factor APT, with r factor1 = r m But APT is more general - e.g. unlike CAPM, market portfolio doesn't have to be efficient But usefulness of APT requires heavy-duty statistics to identify factors measure factor returns