240 likes | 256 Views
FINANCE 8. Capital Markets and The Pricing of Risk. Professor André Farber Solvay Business School Université Libre de Bruxelles Fall 2007. Introduction to risk. Objectives for this session : 1. Review the problem of the opportunity cost of capital 2. Analyze return statistics
E N D
FINANCE8. Capital Markets and The Pricing of Risk Professor André Farber Solvay Business School Université Libre de Bruxelles Fall 2007
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 MBA 2007 Risk and return
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 MBA 2007 Risk and return
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 MBA 2007 Risk and return
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 MBA 2007 Risk and return
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 Historical risk premium Current risk-free rate = + MBA 2007 Risk and return
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 MBA 2007 Risk and return
Capital Asset Pricing Model Expected return rM r Risk free interest rate β 1 Beta MBA 2007 Risk and return
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 MBA 2007 Risk and return
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 MBA 2007 Risk and return
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 . MBA 2007 Risk and return
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. MBA 2007 Risk and return
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 MBA 2007 Risk and return
Return Statistics - Example MBA 2007 Risk and return
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 MBA 2007 Risk and return
Belgium - Monthly returns 1951 - 1999 MBA 2007 Risk and return
S&P 500 MBA 2007 Risk and return
Microsoft MBA 2007 Risk and return
Normal distribution illustrated MBA 2007 Risk and return
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 MBA 2007 Risk and return
Total returns US 1926-2002 Source: Ross, Westerfield, Jaffee (2005) Table 9.2 MBA 2007 Risk and return
Market Risk Premium: The Very Long Run The equity premium puzzle: Source: Ross, Westerfield, Jaffee (2005) Table 9A.1 Was the 20th century an anomaly? MBA 2007 Risk and return
Diversification MBA 2007 Risk and return
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: Portfolio risk Total risk of individual security Unsystematic or diversifiable risk MBA 2007 Risk and return