Bài giảng Essentials of Investments - Chapter 6 Efficient Diversification
Extending Concepts to All Securities • The optimal combinations result in lowest level of risk for a given return • The optimal trade-off is described as the efficient frontier • These portfolios are dominant
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Chapter 6
Efficient
Diversification
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rp = W1r1 + W2r2
W1 = Proportion of funds in Security 1
W2 = Proportion of funds in Security 2
r1 = Expected return on Security 1
r2 = Expected return on Security 2
Two-Security Portfolio: Return
WiS
i=1
n
= 1
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sp
2 = w1
2s1
2 + w2
2s2
2 + 2W1W2 Cov(r1r2)
s1
2 = Variance of Security 1
s2
2 = Variance of Security 2
Cov(r1r2) = Covariance of returns for
Security 1 and Security 2
Two-Security Portfolio: Risk
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Covariance
r1,2 = Correlation coefficient of
returns
Cov(r1r2) = r1,2s1s2
s1 = Standard deviation of
returns for Security 1
s2 = Standard deviation of
returns for Security 2
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Correlation Coefficients: Possible
Values
If r = 1.0, the securities would be
perfectly positively correlated
If r = - 1.0, the securities would be
perfectly negatively correlated
Range of values for r 1,2
-1.0 < r < 1.0
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s2p = W1
2s1
2+ W2
2s2
2
+ 2W1W2
rp = W1r1 + W2r2 + W3r3
Cov(r1r2)
+ W3
2s3
2
Cov(r1r3)+ 2W1W3
Cov(r2r3)+ 2W2W3
Three-Security Portfolio
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rp = Weighted average of the
n securities
sp
2 = (Consider all pair-wise
covariance measures)
In General, For an n-Security
Portfolio:
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E(rp) = W1r1 + W2r2
Two-Security Portfolio
sp
2 = w1
2s1
2 + w2
2s2
2 + 2W1W2 Cov(r1r2)
sp = [w1
2s1
2 + w2
2s2
2 + 2W1W2
Cov(r1r2)]
1/2
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r = 0
E(r)
r = 1
r = -1
r = -1
r = .3
13%
8%
12% 20% St. Dev
TWO-SECURITY PORTFOLIOS WITH
DIFFERENT CORRELATIONS
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Portfolio Risk/Return Two Securities:
Correlation Effects
• Relationship depends on correlation
coefficient
• -1.0 < r < +1.0
• The smaller the correlation, the greater
the risk reduction potential
• If r = +1.0, no risk reduction is possible
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1
1 2
- Cov(r1r2)
W1 =
+ - 2Cov(r1r2)
2
W2 = (1 - W1)
Minimum Variance Combination
s 2
s 2
2E(r2) = .14 = .20Sec 2
12 = .2
E(r1) = .10 = .15Sec 1 s
s
r
s 2
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W1 =
(.2)2 - (.2)(.15)(.2)
(.15)2 + (.2)2 - 2(.2)(.15)(.2)
W1 = .6733
W2 = (1 - .6733) = .3267
Minimum Variance
Combination: r = .2
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rp = .6733(.10) + .3267(.14) = .1131
p = [(.6733)2(.15)2 + (.3267)2(.2)2 +
2(.6733)(.3267)(.2)(.15)(.2)]
1/2
p= [.0171]
1/2 = .1308
Minimum Variance: Return and Risk
with r = .2
s
s
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W1 =
(.2)2 - (.2)(.15)(.2)
(.15)2 + (.2)2 - 2(.2)(.15)(-.3)
W1 = .6087
W2 = (1 - .6087) = .3913
Minimum Variance
Combination: r = -.3
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rp = .6087(.10) + .3913(.14) = .1157
p = [(.6087)2(.15)2 + (.3913)2(.2)2 +
2(.6087)(.3913)(.2)(.15)(-.3)]1/2
p
= [.0102]
1/2
= .1009
Minimum Variance: Return and Risk
with r = -.3
s
s
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Extending Concepts to All Securities
• The optimal combinations result in
lowest level of risk for a given return
• The optimal trade-off is described as the
efficient frontier
• These portfolios are dominant
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Optimal Risky Portfolios
• Portfolio Diversification
• Portfolios of Two Risky Assets
• Asset Allocation
• Markowitz Portfolio Model
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Portfolio Diversification
Return
Time
Stock x
Stock y
x + y
Implications: combination of stocks can
reduce overall risk (variance).
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Portfolio Risk behavior
Variance
# Assets
systematic risk
Unsystematic risk
After a certain number of securities,
portfolio variance can no longer be reduced
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Portfolios of Two Risky Assets
• Given
r1 =0.08, s1=0.12
r2 =0.13, s2=0.20
w1 =w2 = 0.5 (assumption)
• rp = w1r1 + w2r2
=0.5(0.08) + 0.5(0.13)
= 0.105
s2p=w
2
1s
2
1 + w
2
2s
2
2 + 2w1w2cov12
=0.25(0.0144)+0.25(0.04) +
2(0.5)(0.5)cs1s2
• case (1): Assume c=1.0
s2p = 0.0256
sp = 0.16
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return
stand. dev
0.12 0.16
0.08
0.2
1
2
0.105
0.13
Portfolio Return/Risk
If more weight is invested in security 1, the
tradeoff line will move downward. Otherwise,
it will move upward.
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Case 2: c =0.3
s2p= 0.017187
sp = 0.1311, rp = 0.105
0.08
0.105
Return
stand. dev
0.12 0.13 0.2
1
2
.
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Return
Stand. Dev.
Portfolio Return/Risk
c=-1
c=0.3
c=-1 c=1
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Capital Allocation for Two Risky
Assets
rf
1
2
Return
Sp
Max (rp -rf)/sp
{w}
w* =f(r1, r2, s1, s2, cov(1,2))
then, we get: rp, sp
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Example of optimal portfolio
The optimal weight in the less risky
asset will be:
w1=
(r1-rf)s22-(r2-rf)cov(1,2)
(r1-rf)s
2
2+(r2-rf)s
2
1-(r1-rf+r2-rf)cov(1,2)
w2 =1-w1
Given:
r1=0.1, s1=0.2
r2=0.3, s2=0.6 c(coeff. of corr)=-0.2
Then: cov=-0.24
w1=0.68
w2=1-w1=0.32
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Lending v.s Borrowing
rf
1
2
Return
Sp
U
Assume two portfolios (p, rf), weight
in portfolio, y, will be:
y = (rp -rf)/0.01As
2
p
Lending
p
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Markowitz Portfolio Selection
• Three assets case
return and variance formula for the
portfolio
• N-assets case
Return and variance formula for the
portfolio
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E(r)
The minimum-variance frontier of
risky assets
Efficient
frontier
Global
minimum
variance
portfolio Minimum
variance
frontier
Individual
assets
St. Dev.
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Extending to Include Riskless Asset
• The optimal combination becomes
linear
• A single combination of risky and
riskless assets will dominate
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E(r)
CAL (Global
minimum variance)
CAL (A)CAL (P)
M
P
A
F
P P&F A&FM
A
G
P
M
s
ALTERNATIVE CALS
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Dominant CAL with a Risk-Free
Investment (F)
CAL(P) dominates other lines -- it has the
best risk/return or the largest slope
Slope = (E(R) - Rf) / s
[ E(RP) - Rf) / s P ] > [E(RA) - Rf) / sA]
Regardless of risk preferences
combinations of P & F dominate
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Single Factor Model - CAPM
ri = E(Ri) + ßiF + e
ßi = index of a securities’ particular return
to the factor
F= some macro factor; in this case F is
unanticipated movement; F is commonly
related to security returns
Assumption: a broad market index like the
S&P500 is the common factor
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Single Index Model
Risk Prem Market Risk Prem
or Index Risk Prem
i = the stock’s expected return if the
market’s excess return is zero
ßi(rm - rf) = the component of return due to
movements in the market index
(rm - rf) = 0
ei = firm specific component, not due to market
movements
errrr ifmiifi
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ARit is the abnormal for security i at time t
- it is the error term of the market model calculated on an out of
sample basis
- it is basically the forecast error
- the difference between the actual Rit and the forecast
returns abnormal thecomputethen
ˆ and ˆget window,estimation in the OLSrun ii
mtiiitit RRAR
ˆˆ
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Let: Ri = (ri - rf)
Rm = (rm - rf)
Risk premium
format
Ri = i + ßi(Rm) + ei
Risk Premium Format
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Estimating the Index Model
Excess Returns (i)
Security
Characteristic
Line
. ..
. .
.
. .
. ..
. .
.
. .
. ..
.
.
.
. .
. ..
. .
.
. .
. .
.
. .
.
. .
.
. ... .
. .. .
Excess returns
on market index
Ri = i + ßiRm + ei