1. ©1999 Thomas A. Rietz 1 Diversification and the CAPM The relationship between risk and expected returns

2. ©1999 Thomas A. Rietz 2 Introduction l Investors are concerned with –Risk –Returns l What determines the required compensation for risk? l It will depend on –The risks faced by investors –The tradeoff between risk and return they face

3. ©1999 Thomas A. Rietz 3 Agenda l Concepts of risk for –A single stock –Portfolios of stocks l Risk for the diversified investor: Beta –Calculating Beta l The relationship between Beta and Return: The Capital Asset Pricing Model (CAPM)

4. ©1999 Thomas A. Rietz 4 Overview l Investors demand compensation for risk –If investors hold “diversified” portfolios, risk can be defined through the interaction of a single investment with the rest of the portfolios through a concept called “beta” l The CAPM gives the required relationship between “beta” and the return demanded on the investment!

5. ©1999 Thomas A. Rietz 5 Vocabulary l Expected return: –What we expect to receive on average l Standard deviation of returns: –A measure of dispersion of actual returns l Correlation –The tendency for two returns to fall above or below the expected return a the same or different times l Beta –A measure of risk appropriate for diversified investors l Diversified investors –Investors who hold a portfolio of many investments l The Capital Asset Pricing Model (CAPM) –The relationship between risk and return for diversified investors

6. Measuring Expected Return l We describe what we expect to receive or the expected return: –Often estimated using historical averages (excel function: “average”).

7. Example: Die Throw l Suppose you pay $300 to throw a fair die. l You will be paid $100x(The Number rolled) l The probability of each outcome is 1/6. l The returns are: –(100-300)/300 = -66.67% –(200-300)/300 = -33.33% …etc. l The expected return E(r) is: –1/6x(-66.67%) + 1/6x(-33.33%) + 1/6x0% + 1/6x33.33% + 1/6x66.67% + 1/6x100% = 16.67%!

8. Example: IEM l Suppose –You buy and AAPLi contract on the IEM for $0.85 –You think the probability of a $1 payoff is 90% l The returns are: –(1-0.85)/0.85 = 17.65% –(0-0.85)/0.85 = -100% l The expected return E(r) is: –0.9x17.65% - 0.1x100% = 5.88%

9. Example: Market Returns l Recent data from the IEM shows the following average monthly returns from 5/95 to 10/99: –(http://www.biz.uiowa.edu/iem/markets/compdata/compfund.html)http://www.biz.uiowa.edu/iem/markets/compdata/compfund.html

10. Growth of $1000 Investments

11. l Often estimated using historical averages (excel function: “stddev”) Measuring Risk: Standard Deviation and Variance l Standard Deviation in Returns:

12. Example: Die Throw l Recall the dice roll example: –You pay $300 to throw a fair die. –You will be paid $100x(The Number rolled) –The probability of each outcome is 1/6. –The expected return E(r) is 16.67%. l The standard deviation is:

13. Example: IEM l Suppose –You buy and AAPLi contract on the IEM for $0.85 –You think the probability of a $1 payoff is 90% l The returns are: –(1-0.85)/0.85 = 17.65% –(0-0.85)/0.85 = -100% l The expected return E(r) is: –0.9x17.65% - 0.1x100% = 5.88% l The standard deviation is: –[0.9x(17.65%) 2 + 0.1x(-100%) 2 - 5.88% 2 ] 0.5 = 35.29%

14. Example: Market Returns l Recent data from the IEM shows the following average monthly returns & standard deviations from 5/95 to 10/99: –(http://www.biz.uiowa.edu/iem/markets/compdata/compfund.html)http://www.biz.uiowa.edu/iem/markets/compdata/compfund.html

15. Growth of $1000 Investments

16. Risk and Average Return

17. Measures of Association l Correlation shows the association across random variables l Variables with –Positive correlation: tend to move in the same direction –Negative correlation: tend to move in opposite directions –Zero correlation: no particular tendencies to move in particular directions relative to each other

18. –  AB is in the range [-1,1] –Often estimated using historical averages (excel function: “correl”) Covariance in returns,  AB, is defined as: Covariance and Correlation The correlation,  AB, is defined as:

19. Notation for Two Asset and Portfolio Returns ItemAsset AAsset BPortfolio Actual Returnr Ai r Bi r Pi Expected ReturnE(r A ) E(r B ) E(r P ) Variance  A 2  B 2  P 2 Std. Dev.  A  B  P Correlation in Returns  AB Covariance in Returns  AB =  A  B  AB

20. Example: IEM l Suppose –You buy an MSFT090iH for $0.85 and a MSFT090iL contract for $0.15. –You think the probability of $1 payoffs are 90% & 10% l The expected returns are: –0.9x17.65% + 0.1x(-100%) = 5.88% –0.1x566.67% + 0.9x (-100%) = -33.33% l The standard deviations are: –[0.9x(17.65%) 2 + 0.1x(-100%) 2 - 5.88% 2 ] 0.5 = 35.29% –[0.1x(566.67%) 2 + 0.9x(-100%) 2 - (-33.33%) 2 ] 0.5 = 200% l The correlation is:

21. Example: Market Returns l Recent data from the IEM shows the following monthly return correlations from 5/95 to 10/99: –(http://www.biz.uiowa.edu/iem/markets/compdata/compfund.html)http://www.biz.uiowa.edu/iem/markets/compdata/compfund.html

22. Correlation of AAPL & IBM

23. Risk and Average Return

24. l The standard deviation is not a linear combination of the individual asset standard deviations l Instead, it is given by: Two Asset Portfolios: Risk l The standard deviation a the 50%/50%, AAPL & IBM portfolio is: l The portfolio risk is lower than either individual asset’s because of diversification.

25. Correlations and Diversification l Suppose –E(r) A = 16% and  A = 30% –E(r) B = 10% and  B = 16% Consider the E(r) P and  P of securities A and B as w A and  vary...

26. Case 1: Perfect positive correlation between securities, i.e.,  AB = +1

27. Case 2: Zero correlation between securities, i.e.,  AB = 0.

28. Case 3: Perfect negative correlation between securities, i.e.,  AB = -1

29. Comparison

30. 3 Asset Portfolios: Expected Returns and Standard Deviations l Suppose the fractions of the portfolio are given by w AAPL, w IBM and w MSFT. l The expected return is: –E(r P ) = w AAPL E(r AAPL ) + w IBM E(r IBM ) + w MSFT E(r MSFT ) l The standard deviation is:

31. For the Naively Diversified Portfolio, this gives:

33. The Concept of Risk With N Risky Assets l As you increase the number of assets in a portfolio: –the variance rapidly approaches a limit, –the variance of the individual assets contributes less and less to the portfolio variance, and –the interaction terms contribute more and more. l Eventually, an asset contributes to the risk of a portfolio not through its standard deviation but through its correlation with other assets in the portfolio. l This will form the basis for CAPM.

34. l Portfolio variance consists of two parts: –1. Non-systematic (or idiosyncratic) risk and –2. Systematic (or covariance) risk l The market rewards only systematic risk because diversification can get rid of non- systematic risk Variance of a naively diversified portfolio of N assets

35. Naive Diversification

36. 26 Risky Assets Over a 10 Year Period

37. Consider Naive Portfolios of 1 through all 26 of these Assets (Added in Alphabetical Order)

38. The Capital Asset Pricing Model l CAPM Characteristics: –  i =  i  m  im /  m 2 l Asset Pricing Equation: –E(r i ) = r f +  i [E(r m )-r f ] l CAPM is a model of what expected returns should be if everyone solves the same passive portfolio problem l CAPM serves as a benchmark –Against which actual returns are compared –Against which other asset pricing models are compared

39. The Idea Behind CAPM l The value of an asset reflects –The risk associated with that asset given –Investors own a combination of l The risk free asset and l The market portfolio. l A risky asset –Has no effect on the risk free rate. –Effects the portfolio through its covariance with it. l The “market price of risk” is: E(R m )-R f l Where do these ideas come from?

40. The Capital Asset Pricing Model l Advantages: –Simplicity –Works well on average l Disadvantages: –Makes many simplifying assumptions about markets, returns and investor behavior –How do you estimate beta? Can all aspects of risk be summarized by beta? –What is the true market portfolio and risk free rate?

41. CAPM Assumptions l No transactions costs l No taxes l Infinitely divisible assets l Perfect competition –No individual can affect prices l Only expected returns and variances matter –Quadratic utility or –Normally distributed returns l Unlimited short sales and borrowing and lending at the risk free rate of return l Homogeneous expectations

42. Feasible portfolios with N risky assets

43. Dominated and Efficient Portfolios

44. How would you find the efficient frontier? 1. Find all asset expected returns and standard deviations. 2. Pick one expected return and minimize portfolio risk. 3. Pick another expected return and minimize portfolio risk. 4. Use these two portfolios to map out the efficient frontier.

45. Utility Maximization

46. Utility maximization with a riskfree asset

47. Three Important Funds l The riskless asset has a standard deviation of zero l The minimum variance portfolio lies on the boundary of the feasible set at a point where variance is minimum l The market portfolio lies on the feasible set and on a tangent from the riskfree asset

48. A world with one riskless asset and N risky assets

49. Tobin’s Two-Fund Separation l When the riskfree asset is introduced, l All investors prefer a combination of 1) The riskfree asset and 2) The market portfolio l Such combinations dominate all other assets and portfolios

50. The Capital Market Line l All investors face the same Capital Market Line (CML) given by:

51. Equilibrium Portfolio Returns l The CML gives the expected return-risk combinations for efficient portfolios. l What about inefficient portfolios? –Changing the expected return and/or risk of an individual security will effect the expected return and standard deviation of the market! l In equilibrium, what a security adds to the risk of a portfolio must be offset by what it adds in terms of expected return –Equivalent increases in risk must result in equivalent increases in returns.

52. How is Risk Priced? l Consider the variance of the market portfolio: l It is the covariance with the market portfolio and not the variance of a security that matters l Therefore, the CAPM prices the covariance with the market and not variance per se

53. The CAPM Pricing Equation! l The expected return on any asset can be written as: l This is simply the no arbitrage condition! l This is also known as the Security Market Line (SML).

54. Using the CAPM: Finding E(r i ) Suppose you have the following information: r f = 3.5% E(r m )=8.5%  IBM =0.75 l What should E(r IBM ) be? l Answer:

55. Using the CAPM: Finding  i l Suppose you have the following information: r f = 3.5% E(r m )=8.5% E(r IBM )=7.25% What should  IBM be? l Answer:

56. Using the CAPM: Finding E(rm) Suppose you have the following information: r f = 3.5%  IBM =0.75 E(r IBM )=7.25% l What should E(r m ) be? l Answer:

57. Using the CAPM: Finding r f Suppose you have the following information: E(r m )=8.5%  DE =0.75 E(r DE )=7.25% l What should r f be? l Answer:

58. Notes on Estimating b’s l Let r it, r mt and r ft denote historical returns for the time period t=1,2,...,T. The are two standard ways to estimate historical  ’s using regressions: –Use the Market Model: r it -r ft =  i +  i (r mt -r ft ) + e it –Use the Characteristic Line: r it = a i + b i r mt + e it  i = a i + (1-b i )r ft and  i = b i l Typical regression estimates: –Value Line (Market Model): l 5 Yrs, Weekly Data, VW NYSE as Market –Merrill Lynch (Characteristic Line): l 5 Yrs, Monthly Data, S&P500 as Market

59. Example Characteristic Line: AAPL vs S&P500 (IEM Data)

60. Example Characteristic Line: IBM vs S&P500 (IEM Data)

61. Example Characteristic Line: MSFT vs S&P500 (IEM Data)

62. Notes on Estimating  ’s l Betas for our companies AAPLIBMMSFTSP500 Raw:0.18440.98381.18671 Adjusted:0.45630.98911.12451 Avg. R:2.42%3.64%4.72%1.75%

63. Average Returns vs (Adjusted) Betas

64. ©1999 Thomas A. Rietz 64 Summary l State what has been learned l Define ways to apply training l Request feedback of training session

65. ©1999 Thomas A. Rietz 65 Where to get more information l Other training sessions l List books, articles, electronic sources l Consulting services, other sources