1. FINANCE 8. Capital Markets and The Pricing of Risk Professor André Farber Solvay Business School Université Libre de Bruxelles Fall 2007

2. June 3, 2015 MBA 2007 Risk and return |2 Introduction to risk Objectives for this session : –1. Review the problem of the opportunity cost of capital –2. Analyze return statistics –3. Introduce the variance or standard deviation as a measure of risk for a portfolio –4. See how to calculate the discount rate for a project with risk equal to that of the market –5. Give a preview of the implications of diversification

3. June 3, 2015 MBA 2007 Risk and return |3 Setting the discount rate for a risky project Stockholders have a choice: –either they invest in real investment projects of companies –or they invest in financial assets (securities) traded on the capital market The cost of capital is the opportunity cost of investing in real assets It is defined as the forgone expected return on the capital market with the same risk as the investment in a real asset

4. June 3, 2015 MBA 2007 Risk and return |4 Uncertainty: 1952 – 1973- the Golden Years 1952: Harry Markowitz * –Portfolio selection in a mean –variance framework 1953: Kenneth Arrow * –Complete markets and the law of one price 1958: Franco Modigliani * and Merton Miller * –Value of company independant of financial structure 1963: Paul Samuelson * and Eugene Fama –Efficient market hypothesis 1964: Bill Sharpe * and John Lintner –Capital Asset Price Model 1973: Myron Scholes *, Fisher Black and Robert Merton * –Option pricing model

5. June 3, 2015 MBA 2007 Risk and return |5 Three key ideas 1. Returns are normally distributed random variables Markowitz 1952: portfolio theory, diversification 2. Efficient market hypothesis Movements of stock prices are random Kendall 1953 3. Capital Asset Pricing Model Sharpe 1964 Lintner 1965 Expected returns are function of systematic risk

6. June 3, 2015 MBA 2007 Risk and return |6 Preview of what follow First, we will analyze past markets returns. We will: –compare average returns on common stocks and Treasury bills –define the variance (or standard deviation) as a measure of the risk of a portfolio of common stocks –obtain an estimate of the historical risk premium (the excess return earned by investing in a risky asset as opposed to a risk-free asset) The discount rate to be used for a project with risk equal to that of the market will then be calculated as the expected return on the market: Expected return on the market Current risk- free rate Historical risk premium =+

7. June 3, 2015 MBA 2007 Risk and return |7 Implications of diversification The next step will be to understand the implications of diversification. We will show that: –diversification enables an investor to eliminate part of the risk of a stock held individually (the unsystematic - or idiosyncratic risk). –only the remaining risk (the systematic risk) has to be compensated by a higher expected return –the systematic risk of a security is measured by its beta (  ), a measure of the sensitivity of the actual return of a stock or a portfolio to the unanticipated return in the market portfolio –the expected return on a security should be positively related to the security's beta

8. June 3, 2015 MBA 2007 Risk and return |8 Capital Asset Pricing Model Expected return Beta Risk free interest rate r rMrM 1 β

9. June 3, 2015 MBA 2007 Risk and return |9 Returns The primitive objects that we will manipulate are percentage returns over a period of time: The rate of return is a return per dollar (or £, DEM,...) invested in the asset, composed of –a dividend yield –a capital gain The period could be of any length: one day, one month, one quarter, one year. In what follow, we will consider yearly returns

10. June 3, 2015 MBA 2007 Risk and return |10 Ex post and ex ante returns Ex post returns are calculated using realized prices and dividends Ex ante, returns are random variables –several values are possible –each having a given probability of occurence The frequency distribution of past returns gives some indications on the probability distribution of future returns

11. June 3, 2015 MBA 2007 Risk and return |11 Frequency distribution Suppose that we observe the following frequency distribution for past annual returns over 50 years. Assuming a stable probability distribution, past relative frequencies are estimates of probabilities of future possible returns.

12. June 3, 2015 MBA 2007 Risk and return |12 Mean/expected return Arithmetic Average (mean) –The average of the holding period returns for the individual years Expected return on asset A: –A weighted average return : each possible return is multiplied or weighted by the probability of its occurence. Then, these products are summed to get the expected return.

13. June 3, 2015 MBA 2007 Risk and return |13 Variance -Standard deviation Measures of variability (dispersion) Variance Ex post: average of the squared deviations from the mean Ex ante: the variance is calculated by multiplying each squared deviation from the expected return by the probability of occurrence and summing the products Unit of measurement : squared deviation units. Clumsy.. Standard deviation : The square root of the variance Unit :return

14. June 3, 2015 MBA 2007 Risk and return |14 Return Statistics - Example

15. June 3, 2015 MBA 2007 Risk and return |15 Normal distribution Realized returns can take many, many different values (in fact, any real number > -100%) Specifying the probability distribution by listing: –all possible values –with associated probabilities as we did before wouldn't be simple. We will, instead, rely on a theoretical distribution function (the Normal distribution) that is widely used in many applications. The frequency distribution for a normal distribution is a bellshaped curve. It is a symetric distribution entirely defined by two parameters – the expected value (mean) – the standard deviation

16. June 3, 2015 MBA 2007 Risk and return |16 Belgium - Monthly returns 1951 - 1999

17. June 3, 2015 MBA 2007 Risk and return |17 S&P 500

18. June 3, 2015 MBA 2007 Risk and return |18 Microsoft

19. June 3, 2015 MBA 2007 Risk and return |19 Normal distribution illustrated

20. June 3, 2015 MBA 2007 Risk and return |20 Risk premium on a risky asset The excess return earned by investing in a risky asset as opposed to a risk-free asset U.S.Treasury bills, which are a short-term, default-free asset, will be used a the proxy for a risk-free asset. The ex post (after the fact) or realized risk premium is calculated by substracting the average risk-free return from the average risk return. Risk-free return = return on 1-year Treasury bills Risk premium = Average excess return on a risky asset

21. June 3, 2015 MBA 2007 Risk and return |21 Total returns US 1926-2002 Arithmetic Mean Standard Deviation Risk Premium Common Stocks12.2%20.5%8.4% Small Company Stocks16.933.213.1 Long-term Corporate Bonds6.28.72.4 Long-term government bonds5.89.42.0 Intermediate-term government bond (1926-1999) 5.45.81.6 U.S. Treasury bills3.83.2 Inflation3.14.4 Source: Ross, Westerfield, Jaffee (2005) Table 9.2

22. June 3, 2015 MBA 2007 Risk and return |22 Market Risk Premium: The Very Long Run 1802-18701871-19251926-19991802-2002 Common Stock6.88.512.29.7 Treasury Bills5.44.13.84.3 Risk premium1.44.48.45.4 Source: Ross, Westerfield, Jaffee (2005) Table 9A.1 The equity premium puzzle: Was the 20th century an anomaly?

23. June 3, 2015 MBA 2007 Risk and return |23 Diversification

24. June 3, 2015 MBA 2007 Risk and return |24 Conclusion 1. Diversification pays - adding securities to the portfolio decreases risk. This is because securities are not perfectly positively correlated 2. There is a limit to the benefit of diversification : the risk of the portfolio can't be less than the average covariance (cov) between the stocks The variance of a security's return can be broken down in the following way: The proper definition of the risk of an individual security in a portfolio M is the covariance of the security with the portfolio: Total risk of individual security Portfolio risk Unsystematic or diversifiable risk