A.Choose the preferred portfolio when dominance is sufficient.
A.
A dominates B; K dominates J; S dominates R. X and Y involve a risk–return trade-off, so the choice depends on preferences and the rest of the available opportunity set.
Mean-Variance Analysis
EXERCISE 02
Asset A has expected return 6 and variance 1.5; asset B has expected return 3.5 and variance 4. Covariance is −0.35. Returns use a common unit, and variances use its square. Portfolio weights sum to one.
A.Find minimum-variance weights and portfolio risk.
Asset A takes returns −1, 1 and 3 with probability 1/3 each. Asset B takes returns −1, 1 and 2 with probabilities 1/4, 1/4 and 1/2. Weights sum to one. First compare their moments; then consider the stipulated correlation −1 and check whether it is consistent with these marginal distributions.
A.Apply mean–variance dominance.
B.Calculate the formal minimum-variance weights for correlation −1, and assess feasibility.
A.
E[R]=j∑pjRj,Var(R)=j∑pjRj2−E[R]2
μA=3−1+1+3=1
σA2=31+1+9−1=38
μB=−41+41+22=1
σB2=41+41+24−1=23
B dominates A under the mean–variance criterion: identical expected return and lower variance.
B.
σp2=x2σA2+(1−x)2σB2+2x(1−x)σAB
ρ=−1⇒σp2=[xσA−(1−x)σB]2
xA=8/3+3/23/2=73
A: 42.857143%; B: 57.142857%.
μp=1,σp2=0(ρ=−1 assumed)
This zero-risk result is conditional. Perfect negative correlation requires B to be an affine decreasing function of A almost surely.
B=1−σAσB(A−1)=1−43(A−1)
A values −1, 1 and 3 would require B values 2.5, 1 and −0.5, each with probability 1/3. Those are not the supplied B distribution. Therefore no joint distribution with the stated marginals can have correlation −1; the formal portfolio is not feasible for those exact distributions.
Mean-Variance Analysis
EXERCISE 04
A has expected return 0.09 and variance 0.14; B has expected return 0.13 and variance 0.18. Covariance is 0.10. Weights sum to one and portfolio variance must not exceed 0.15. Short selling is permitted; also report whether the optimum is long-only.
A.Maximise expected return subject to the variance cap.
A.
σp2=x2σA2+(1−x)2σB2+2x(1−x)σAB
μp=0.09x+0.13(1−x)=0.13−0.04x
σp2=0.14x2+0.18(1−x)2+0.20x(1−x)
σp2≤0.15⟺0.12x2−0.16x+0.03≤0
x±=0.240.16±0.162−4(0.12)(0.03)
Feasible A weights lie between 0.225708115 and 1.107625219. Expected return decreases with x, so choose the lower endpoint.
xA=x−
22.570811%.
xB=1−x−
77.429189%.
μmax=0.13−0.04x−
12.097168%.
Variance equals 0.15 and standard deviation equals 0.387298335. Both weights are positive, so the same optimum is feasible without short selling.
Mean-Variance Analysis
EXERCISE 05
A has expected return 1 and variance 4; B has expected return 2 and variance 9. Correlation is −1/2 and weights sum to one. Use the stated common return unit and squared-unit variances. Short selling is permitted; the reported optima also have non-negative weights.
A.Find the minimum-variance portfolio and quantify diversification.
B.Derive the efficient frontier.
C.Find the maximum expected return when variance is at most 2.
A.
σp2=x2σA2+(1−x)2σB2+2x(1−x)σAB
σAB=ρσAσB=−21(2)(3)=−3
σp2=4x2+9(1−x)2−6x(1−x)=19x2−24x+9
xmin=σA2+σB2−2σABσB2−σAB
xA=4+9+69+3=1912,xB=197
σmin2=1927,σmin=1927,μmin=1926
A: 63.157895%; B: 36.842105%. Variance 1.421052632; standard deviation 1.192079121. Compared with the lower standalone standard deviation of 2, diversification reduces risk by 0.807920879 return units.
B.
μp=x+2(1−x)=2−x⇒x=2−μp
σp2=19(2−μp)2−24(2−μp)+9
σp2=19μp2−52μp+37
μefficient(σ)=3852+76σ2−108
Choose the upper-return branch, with variance at least 27/19 and expected return at least 26/19. The lower-return branch is inefficient. With long-only weights, also restrict expected return to at most 2.