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Natali [406]
4 years ago
13

You want to evaluate three mutual funds using the Sharpe measure for performance evaluation. The risk-free return during the sam

ple period is 6%. The average returns, standard deviations, and betas for the three funds are given below, as are the data for the S&P 500 Index.
Average Return Standard Deviation Beta
Fund A 24 % 30 % 1.5
Fund B 12 % 10 % 0.5
Fund C 22 % 20 % 1.0
S&P 500 18 % 16 % 1.0

The fund with the highest Sharpe measure is:

a. Fund A.
b. Fund B.
c. Fund C.
d. Funds A and B (tied for highest).
e. Funds A and C (tied for highest).
Mathematics
1 answer:
riadik2000 [5.3K]4 years ago
3 0

Answer:

The correct option based on the below computation of Sharpe ratio for all funds is option C,Fund C.

Step-by-step explanation:

Sharpe ratio=(Average return of the fund-risk free rate of return)/standard deviation of the fund

Risk free rate of return is 6%

Fund A:

Sharpe ratio=(24%-6%)/30%=0.6

Fund B:

Sharpe ratio=(12%-6%)/10%=0.6

Fund C:

Sharpe ratio=(22%-6%)/20%=0.8

Fund has a sharpe ratio of 0.8 ,unlike funds A& B that have a ratio of 0.6 each

In other words option C is correct

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a) y=-0.317 x +46.02

b) Figure attached

c) S^2=\hat \sigma^2=MSE=\frac{190.33}{10}=19.03

Step-by-step explanation:

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For this case we need to calculate the slope with the following formula:

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\sum_{i=1}^n x_i = 30+30+30+50+50+50+70+70+70+90+90+90=720

\sum_{i=1}^n y_i =38+43+29+32+26+33+19+27+23+14+19+21=324

\sum_{i=1}^n x^2_i =30^2+30^2+30^2+50^2+50^2+50^2+70^2+70^2+70^2+90^2+90^2+90^2=49200

\sum_{i=1}^n y^2_i =38^2+43^2+29^2+32^2+26^2+33^2+19^2+27^2+23^2+14^2+19^2+21^2=9540

\sum_{i=1}^n x_i y_i =30*38+30*43+30*29+50*32+50*26+50*33+70*19+70*27+70*23+90*14+90*19+90*21=17540

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S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=49200-\frac{720^2}{12}=6000

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}=17540-\frac{720*324}{12}{12}=-1900

And the slope would be:

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Nowe we can find the means for x and y like this:

\bar x= \frac{\sum x_i}{n}=\frac{720}{12}=60

\bar y= \frac{\sum y_i}{n}=\frac{324}{12}=27

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In oder to calculate S^2 we need to calculate the MSE, or the mean square error. And is given by this formula:

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The degred of freedom for the error are given by:

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SSR=\frac{S^2_{xy}}{S_{xx}}=\frac{(-1900)^2}{6000}=601.67

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S^2=\hat \sigma^2=MSE=\frac{190.33}{10}=19.03

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