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Portfolio Theory: Two Risky Assets
Karl B. Diether
Fisher College of Business
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Portfolios
A portfolio is a collection of assets.
The weights fundamentally define a portfolio.
The weights are the proportion invested in each asset
Portfolios can contain many assets.
A portfolio can be completely comprised of risky assets.
If you own only one asset do you still have portfolio?
Yes, a pretty simple one.
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Diversification
Diversification
The principle of diversification is fundamental to finance.Portfolios allow an investor to become diversified.
Which bet do you prefer?
Flip a fair coin once; if it is heads I will give a $1000, you get nothingif it is tails.
Flip a fair coin 1000 times; each time you flip heads I will give you$1.00. I will give you nothing for tails.
Most people prefer the second option; most of the risk is diversified awaythrough multiple flips.
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Diversification
You own Dell
Suppose you own only one security, Dell Computer Corp. What sources ofrisk do you face?
Systematic risk
What is systematic risk?
What are some other names for systematic risk?
Can you think of some concrete examples?
Idiosyncratic risk
What is idiosyncratic risk?
What are some other names for idiosyncratic risk?
Can you think of some concrete examples?
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Diversification
Half in Dell and half in PepsiCoSuppose instead you put half your money in Dell and half in PepsiCo.
What happens to your portfolios risk?
Why is idiosyncratic risk reduced?
Arent you subject to more idiosyncratic risk? Bad things can happento both Dell and Pepsi?
Why is systematic risk unaffected?
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Adding Securities: Systematic and Idiosyncratic Risk
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Adding Stocks to An Equal Weight Portfolio
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Diversification
Defining a diversified portfolio
Are all portfolios with lots of securities diversified?
Do other conditions need to be met to call a portfolio diversified?
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Statistical Detour: Covariance
What is covariance?
Covariance is a measure of how much two variables move together.
Consider a few examples (source: Welch)
Negatively Covary Zero Covariation Positively CovaryAgility vs. Weight IQ vs. Gender Wealth vs. LongevityWealth vs. Disease Age vs. Blood Type Arm Strength vs. QB Quality
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Covariance
CovarianceIfx and y are random variables: cov(x, y) = E
x E(x)
y E(y)
Computing Covariance
Ifx and y are random variables that take on the values xi and yi withprobability pi,
cov(x, y) =n
i=1
pixi E(x)
yi E(y)
If A and B are securities, then the covariance between the return on A andthe return on B is written as the following:
cov(ra, rb) =n
i=1
piria E(ra)
rib E(rb)
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Spam and Donuts
You want to invest in Hormel and Krispy Kreme
What is the covariance between their returns (cov(rhrl, rkk))?
Scenario Probability rhrl rkkGood 0.30 0.12 0.20Normal 0.40 0.08 0.10Bad 0.30 0.08 0.00
Step 1: Compute the expected returns of Hormel and Krispy Kreme
E(rhrl) = 0.3(0.12) + 0.4(0.08) + 0.3(0.08) = 9.2%
E(rkk) = 0.3(0.20) + 0.4(0.10) + 0.3(0.00) = 10%
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Spam and Donuts
Step 2: Use the covariance formula
cov(rhrl, rkk) = pg[rg,hrl E(rhrl)][rg,kk E(rkk)]+
pn[rn,hrl E(rhrl)][rn,kk E(rkk)]+
pb[rb,hrl E(rhrl)][rb,kk E(rkk)]
= 0.3(0.12 0.092)(0.20 0.10)+
0.4(0.08 0.092)(0.10 0.10)+
0.3(0.08
0.092)(0.00
0.10)
= 0.0012
What does 0.0012 tell us?
Does cov(rhrl, rkk) = 0.0012 mean a strong relation or a weak one?
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Correlation
Computing Correlation
Ifx and y are random variables, then the correlation between x and y((x, y)) is the following:
(x, y) =cov(x, y)
(x)(y)
If A and B are securities, then the covariance between the return on A andthe return on B is written as the following:
(ra, rb) = cov(ra, rb)(ra)(rb)
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Correlation: -1 to 1
Correlation ranges from -1 to 1
-1, indicates perfect negative correlation.
0, indicates that the two variables are unrelated.
+1, indicates perfect positive correlation.
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Correlation: Spam and Donuts
What is (rhrl, rkk)?
(ra) =p
0.3(0.12 0.092)2 + 0.4(0.8 0.092)2 + 0.3(0.08 0.092)2 = 1.8%
(rb) =p
0.3(0.20 0.10)2 + 0.4(0.10 0.10)2 + 0.3(0.00 0.10)2 = 7.7%
(rhrl, rkk) =cov(rhrl, rkk)
(rhrl)(rkk)
=0.0012
(0.018)(0.077)= 0.87
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Estimating Covariance
EstimationUsually we have to estimate covariances and correlations using past datajust like variances.
Estimating Covariance
if ri1, ri2, ri3, . . .riT are one-period returns for security i, rj1, rj2, rj3, . . .rjTare one-period returns for security j, then the sample or estimatedcovariance is the following:
cov(ri, rj) = 1T 1
Tt=1
(rit ri)(rjt rj)
where ri and rj are the sample means of returns for security i and j:
ri =1
T
Tt=1
rit and rj =1
T
Tt=1
rjt.
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Estimating Correlation
The estimated or sample correlation coefficient
(ri, rj) =cov(ri, rj)
(ri)(rj)
where (ri) is the sample standard deviation of security i and (rj) is thesample standard deviation of security j.
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A Portfolio of Two Risky Assets
The return on a two-asset portfolio:
rp = wra + (1 w)rb
ra is the return and w is the weight on asset A.
rb is the return and 1 w is the weight on asset B.
Note: the weights of the portfolio sum to one.
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A Portfolio of Two Risky Assets
Two Asset Portfolio: Expected return and standard deviation
If A and B are assets and w is the portfolio weight on asset A, then theexpected return of a portfolio composed of A and B is
E(rp) = wE(ra) + (1 w)E(rb),
the variance of the portfolio is
2(rp) = w
2
2(ra) + (1 w)2
2(rb) + 2w(1 w)cov(ra, rb),
and the standard deviation of the portfolio is
(rp) =
2(rp).
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Asset Allocation: Two Risky Assets
Suppose you can invest in the following risky assets:
A stock index like the S&P 500.
A corporate bond index.
How should you split your money?
What does it depend on?What information do you need to answer the question?
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Asset Allocation: Two Risky Assets
Example: A stock index and bond index
E(r)
Stock Index 12% 20%Bond Index 4% 7%
(rs, rb) = -0.10, cov(rs, rb) = -0.0014
What are the feasible allocations?
Try different weights: compute E(rp) and (rp) each time:
E(rp) = wE(rs) + (1
w)E(rb)
2(rp) = w
2
2(rs) + (1 w)2
2(rb) + 2w(1 w) cov(rs, rb)
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2% 6% 10% 14% 18% 22% 26% 30% 34%
E(r)
r
Investment Opportunity Set
Bond IndexMinimum Variance Portfolio
Stock Index
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Asset Allocation: Two Risky Assets
Which portfolio should you choose?
In general its a matter of preference (for risk and expected return).
Can we rule out some portfolios?
Are some portfolios just plain stupid to hold?
Is it just plain stupid to hold just bonds (100% in the bond)?
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E(r)
r
Investment Opportunity Set: Changes in
=1
=0
=-1
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The Shape of the Investment Opportunity Set
The investment opportunity set
The shape of the investment opportunity set is determined by thecovariance between the assets.
if is sufficiently low we can find a portfolio with lower variance thaneither of the assets.
If two assets are perfectly negatively correlated you can diversify awayall risk.
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Adding a Riskfree Asset
Adding a risk free asset
Suppose that we also can invest in a riskfree asset with a return of 3%.
How does adding a riskfree asset change things?
What does the investment opportunity set look like now?
Does adding a riskfree rate increase the number of portfolios that arational and risk averse investor should avoid?
Is there now a single optimal risky portfolio?
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E(r)
r
Investment Opportunity Set
CAL 1
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Investment Opportunity Set
CAL 1CAL 2
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E(r)
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Investment Opportunity Set
CAL 1
CAL 2
CAL 3
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Which CAL is the Best?
Which CAL is the best?
Clearly CAL 3 is the best of the three. For a given standard deviationit offers more expected return.
Also, for a given expected return it has a lower variance.
The risky portfolio that defines CAL 3 is better than the riskyportfolios that define CAL 1 and CAL 2.
What is the optimal CAL?
It is CAL with the highest possible slope or the best expected return standard deviation tradeoff.
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2%
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E(r)
r
Optimal CAL
Optimal CAL
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The Optimal CAL and the Tangency Portfolio
The optimal CAL is the one with the highest slope (Sharpe ratio)
Slope =E(rrisky) rf
(rrisky)
Properties and implications
The optimal CAL is the tangency line between the riskfree rate andthe risky investment opportunity curve.
The risky portfolio that the optimal CAL is tangent with is called thetangency portfolio.
Investors will combine the tangency portfolio with the riskfree asset toform the overall portfolio the best suits their preferences for risk andexpected return.
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Looking Forward
Mean variance analysis
We will generalize our mean-variance analysis to portfolios with many riskyassets.
Models
We will also introduce our first model based on mean-variance analysis(The CAPM).
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