finance 10. risk and expected returns professor andré farber solvay business school université...
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FINANCE10. Risk and expected returns
Professor André Farber
Solvay Business SchoolUniversité Libre de BruxellesFall 2006
MBA 2006 Risk and return (2) |2
Risk and return
• Objectives for this session:
• 1. Efficient set
• 2. Beta
• 3. Optimal portfolio
• 4. CAPM
MBA 2006 Risk and return (2) |3
The efficient set for many securities
• Portfolio choice: choose an efficient portfolio
• Efficient portfolios maximise expected return for a given risk
• They are located on the upper boundary of the shaded region (each point in this region correspond to a given portfolio)
Risk
Expected Return
MBA 2006 Risk and return (2) |4
Choosing between 2 risky assets
• Choose the asset with the highest ratio of excess expected return to risk:
• Example: RF = 6%
• Exp.Return Risk
• A 9% 10%
• B 15% 20%
• Asset Sharpe ratio
• A (9-6)/10 = 0.30
• B (15-6)/20 = 0.45 **
i
Fi RR
ratio Sharpe
A
B
A
Risk
Expected return
MBA 2006 Risk and return (2) |5
Optimal portofolio with borrowing and lending
Optimal portfolio: maximize Sharpe ratio
M
MBA 2006 Risk and return (2) |6
Capital asset pricing model (CAPM)
• Sharpe (1964) Lintner (1965)
• Assumptions
• Perfect capital markets
• Homogeneous expectations
• Main conclusions: Everyone picks the same optimal portfolio
• Main implications:
– 1. M is the market portfolio : a market value weighted portfolio of all stocks
– 2. The risk of a security is the beta of the security:
• Beta measures the sensitivity of the return of an individual security to the return of the market portfolio
• The average beta across all securities, weighted by the proportion of each security's market value to that of the market is 1
Beta
Prof. André FarberSOLVAY BUSINESS SCHOOLUNIVERSITÉ LIBRE DE BRUXELLES
MBA 2006 Risk and return (2) |8
Measuring the risk of an individual asset
• The measure of risk of an individual asset in a portfolio has to incorporate the impact of diversification.
• The standard deviation is not an correct measure for the risk of an individual security in a portfolio.
• The risk of an individual is its systematic risk or market risk, the risk that can not be eliminated through diversification.
• Remember: the optimal portfolio is the market portfolio.
• The risk of an individual asset is measured by beta.
• The definition of beta is:
22 )(
),(
M
iM
M
Mii
R
RRCov
MBA 2006 Risk and return (2) |9
Beta
• Several interpretations of beta are possible:
• (1) Beta is the responsiveness coefficient of Ri to the market
• (2) Beta is the relative contribution of stock i to the variance of the market portfolio
• (3) Beta indicates whether the risk of the portfolio will increase or decrease if the weight of i in the portfolio is slightly modified
MBA 2006 Risk and return (2) |10
Beta as a slope
15, 25
15, 15
-5, -5
-5, -15
-10, -17.5
20, 27.5
-20
-15
-10
-5
0
5
10
15
20
25
30
-15 -10 -5 0 5 10 15 20 25
Return on market
Ret
urn
on
ass
et
Slope = Beta = 1.5
MBA 2006 Risk and return (2) |11
A measure of systematic risk : beta
• Consider the following linear model
• Rt Realized return on a security during period t
A constant : a return that the stock will realize in any period
• RMt Realized return on the market as a whole during period t
A measure of the response of the return on the security to the return on the market
• ut A return specific to the security for period t (idosyncratic return or unsystematic return)- a random variable with mean 0
• Partition of yearly return into:
– Market related part ß RMt
– Company specific part + ut
tMtt uRR
MBA 2006 Risk and return (2) |12
Beta - illustration
• Suppose Rt = 2% + 1.2 RMt + ut
• If RMt = 10%
• The expected return on the security given the return on the market
• E[Rt |RMt] = 2% + 1.2 x 10% = 14%
• If Rt = 17%, ut = 17%-14% = 3%
MBA 2006 Risk and return (2) |13
Measuring Beta
• Data: past returns for the security and for the market
• Do linear regression : slope of regression = estimated beta
1
2
3
4
5
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10
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A B C D E F G H IBeta Calculation - monthly data
Market A B
Mean 2.08% 0.00% 4.55% D3. =AVERAGE(D12:D23)
StDev 5.36% 4.33% 10.46% D4. =STDEV(D12:D23)
Correl 78.19% 71.54% D5. =CORREL(D12:D23,$B$12:$B$23)
R² 61.13% 51.18% D6. =D5 2̂
Beta 1 0.63 1.40 D7. =SLOPE(D12:D23,$B$12:$B$23)
I ntercept 0 -1.32% 1.64% D8. =I NTERCEPT(D12:D23,$B$12:$B$23)
Data
Date Rm RA RB
1 5.68% 0.81% 20.43%
2 -4.07% -4.46% -7.03%
3 3.77% -1.85% -10.14%
4 5.22% -1.94% 6.91%
5 4.25% 3.49% 4.65%
6 0.98% 3.44% 7.64%
7 1.09% -4.27% 8.41%
8 -6.50% -2.70% -1.25%
9 -4.19% -4.29% -11.19%
10 5.07% 3.75% 13.18%
11 13.08% 9.71% 19.22%
12 0.62% -1.67% 3.77%
MBA 2006 Risk and return (2) |14
Decomposing of the variance of a portfolio
• How much does each asset contribute to the risk of a portfolio?
• The variance of the portfolio with 2 risky assets
• can be written as
• The variance of the portfolio is the weighted average of the covariances of each individual asset with the portfolio.
22222 2 BBABBAAAP XXXX
BPBAPA
BBABABABBAAA
BBABBAABBAAAP
XX
XXXXXX
XXXXXX
)()(
)()(22
22222
MBA 2006 Risk and return (2) |15
Example
Exp.Return Sigma VarianceRiskless rate 5 0 0A 15 20 400B 20 30 900Correlation 0
Prop. Variance-covarianceA 0.50 400 0B 0.50 0 900
Cov(Ri,Rp) 200.00 450.00X 0.50 0.50
Variance 325.00St.dev. 18.03Exp.Ret. Rp 17.50
MBA 2006 Risk and return (2) |16
Beta and the decomposition of the variance
• The variance of the market portfolio can be expressed as:
• To calculate the contribution of each security to the overall risk, divide each term by the variance of the portfolio
nMniMiMMM XXXX ......22112
1......
1......
2211
2222
221
1
nMniMiMM
M
nMn
M
iMi
M
M
M
M
XXXX
or
XXXX
MBA 2006 Risk and return (2) |17
Marginal contribution to risk: some math
• Consider portfolio M. What happens if the fraction invested in stock I changes?
• Consider a fraction X invested in stock i
• Take first derivative with respect to X for X = 0
• Risk of portfolio increase if and only if:
• The marginal contribution of stock i to the risk is
22222 )1(2)1( iiMMP XXXX
)(2 2
0
2
MiM
X
P
dX
d
2MiM
iM
MBA 2006 Risk and return (2) |18
Marginal contribution to risk: illustration
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
Fraction in B
Ris
k o
f p
ort
folio
Cor = 0 Cor = 0.25 Cor = 0.50 Cor = 0.75 Cor = 1.0
MBA 2006 Risk and return (2) |19
Beta and marginal contribution to risk
• Increase (sightly) the weight of i:
• The risk of the portfolio increases if:
• The risk of the portfolio is unchanged if:
• The risk of the portfolio decreases if:
12
2 M
iMiMMiM
12
2 M
iMiMMiM
12
2 M
iMiMMiM
MBA 2006 Risk and return (2) |20
Inside beta
• Remember the relationship between the correlation coefficient and the covariance:
• Beta can be written as:
• Two determinants of beta
– the correlation of the security return with the market
– the volatility of the security relative to the volatility of the market
Mi
iMiM
M
iiM
M
iMiM
2
MBA 2006 Risk and return (2) |21
Properties of beta
• Two importants properties of beta to remember
• (1) The weighted average beta across all securities is 1
• (2) The beta of a portfolio is the weighted average beta of the securities
1......2211 nMniMiMM XXXX
nMnPiMiPMPMPP XXXX ......2211
MBA 2006 Risk and return (2) |22
Risk premium and beta
• 3. The expected return on a security is positively related to its beta
• Capital-Asset Pricing Model (CAPM) :
• The expected return on a security equals:
the risk-free rate
plus
the excess market return (the market risk premium)
times
Beta of the security
)( FMF RRRR
MBA 2006 Risk and return (2) |23
CAPM - Illustration
Expected Return
Beta1
MR
FR
MBA 2006 Risk and return (2) |24
CAPM - Example
• Assume: Risk-free rate = 6% Market risk premium = 8.5%
• Beta Expected Return (%)
• American Express 1.5 18.75
• BankAmerica 1.4 17.9
• Chrysler 1.4 17.9
• Digital Equipement 1.1 15.35
• Walt Disney 0.9 13.65
• Du Pont 1.0 14.5
• AT&T 0.76 12.46
• General Mills 0.5 10.25
• Gillette 0.6 11.1
• Southern California Edison 0.5 10.25
• Gold Bullion -0.07 5.40
MBA 2006 Risk and return (2) |25
Pratical implications
• Efficient market hypothesis + CAPM: passive investment
• Buy index fund
• Choose asset allocation
Arbitrage Pricing Model
Professeur André Farber
MBA 2006 Risk and return (2) |27
Market Model
• Consider one factor model for stock returns:
• Rj = realized return on stock j
• = expected return on stock j
• F = factor – a random variable E(F) = 0
• εj = unexpected return on stock j – a random variable
• E(εj) = 0 Mean 0
• cov(εj ,F) = 0 Uncorrelated with common factor
• cov(εj ,εk) = 0 Not correlated with other stocks
jjjj FRR
jR
MBA 2006 Risk and return (2) |28
Diversification
• Suppose there exist many stocks with the same βj.
• Build a diversified portfolio of such stocks.
• The only remaining source of risk is the common factor.
FRR jjj
MBA 2006 Risk and return (2) |29
Created riskless portfolio
• Combine two diversified portfolio i and j.
• Weights: xi and xj with xi+xj =1
• Return:
• Eliminate the impact of common factor riskless portfolio
• Solution:
FxxRxRx
RxRxR
jjiijjii
jjiiP
)()(
0 jiii xx
ji
jix
ji
ijx
MBA 2006 Risk and return (2) |30
Equilibrium
• No arbitrage condition:
• The expected return on a riskless portfolio is equal to the risk-free rate.
Fjji
ii
ji
j RRR
j
Fj
i
FiRRRR
At equilibrium:
MBA 2006 Risk and return (2) |31
Risk – expected return relation
jFj RR
FM RR
Linear relation between expected return and beta
For market portfolio, β = 1
Back to CAPM formula:
jFMFj RRRR )(