# FM11 Ch 05 Tool Kit by grzCRNSg

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```									8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                                  Model
Ch 05 Tool Kit                                                                                            3/5/2005

Chapter 5. Tool Kit for Risk and Return: Portfolio Theory and Asset Pricing Models

PROBABILITY DISTRIBUTIONS

The probability distribution is a listing of all possible outcomes and the corresponding probability.

Probability of
Occurrence                              Rate of Return Distribution
E                 F                G                  H
0.10                  10%               6%               14%                4%
0.20                  10%               8%               12%                6%
0.40                  10%              10%               10%                8%
0.20                  10%              12%               8%                 15%
0.10                  10%              14%               6%                 22%
1.00

EXPECTED RATE OF RETURN AND STANDARD DEVIATION

The expected rate of return is the rate of return that is expected to be realized from an investment. It is
determined as the weighted average of the probability distribution of returns.

To calculate the standard deviation, there are a few steps. First find the differences of all the possible returns
from the expected return. Second, square that difference. Third, multiply the squared number by the
probability of its occurrence. Fourth, find the sum of all the weighted squares. And lastly, take the square
root of that number.

Calculation of expected return and standard deviation for E
Expected rate of return for E               Standard deviation for E
Probability of                                         Deviation from    Squared
Occurrence          Rate of Return        Product         r hat         deviation      Sq Dev * Prob.

10%                    10%               1.00%              0%              0.00%               0.00%
20%                    10%               2.00%              0%              0.00%               0.00%
40%                    10%               4.00%              0%              0.00%               0.00%
20%                    10%               2.00%              0%              0.00%               0.00%
10%                    10%               1.00%              0%              0.00%               0.00%
100%                                                                           Sum:             0.00%
Expected                                            Std. Dev. =
Rate of Return, r                                      Square root of
hat =                     10%                          sum =                    0.00%

If the probabilities are fairly simple, then a short-cut method is to use the excel functions for AVERAGE and
STDEVP, but to "trick" them by entering arguments more than once, in a way that "weights" them like the
probabilities. For example, for stock E we would enter 6% once, since it has only a one in ten probability. We
would enter 8% twice, since it has a two in ten probability. We would enter 10% 4 times, since it has a four in
ten probability. We can do the same thing with the standard deviation function. Note that we use STDEVP
and not STDEV, since we are measuring the standard deviation for the entire population and not for a sample.
We call this the "indirect" method.

Indirect method                    r hat =        10%                                       s=          0.00%

Calculation of expected return and standard deviation for F
Expected rate of return for F                   Standard deviation for F

Michael C. Ehrhardt                                            Page 1                                                  4/30/2012
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Probability of                                        Deviation from     Squared
Occurrence         Rate of Return      Product           r hat          deviation      Sq Dev * Prob.

10%                   6%             0.60%             -4%              0.16%           0.02%
20%                   8%             1.60%             -2%              0.04%           0.01%
40%                  10%             4.00%             0%               0.00%           0.00%
20%                  12%             2.40%             2%               0.04%           0.01%
10%                  14%             1.40%             4%               0.16%           0.02%
100%                                                                       Sum:         0.05%
Expected                                          Std. Dev. =
Rate of Return, r                                    Square root of
hat =                   10%                          sum =                2.19%
Indirect method                 r hat =       10%                                      s=           2.19%

Calculation of expected return and standard deviation for G
Expected rate of return for G                Standard deviation for G
Probability of                                         Deviation from     Squared
Occurrence          Rate of Return       Product          r hat         deviation      Sq Dev * Prob.

10%                  14%             1.40%             4%               0.16%           0.02%
20%                  12%             2.40%             2%               0.04%           0.01%
40%                  10%             4.00%             0%               0.00%           0.00%
20%                   8%             1.60%             -2%              0.04%           0.01%
10%                   6%             0.60%             -4%              0.16%           0.02%
100%                                                                       Sum:         0.05%
Expected                                          Std. Dev. =
Rate of Return, r                                    Square root of
hat =                   10%                          sum =                2.19%
Indirect method                 r hat =      10.00%                                    s=       2.19%

Calculation of expected return and standard deviation for H
Expected rate of return for H                Standard deviation for H
Probability of                                         Deviation from     Squared
Occurrence          Rate of Return       Product          r hat         deviation      Sq Dev * Prob.

10%                   4%             0.40%             -6%              0.36%           0.04%
20%                   6%             1.20%             -4%              0.16%           0.03%
40%                   8%             3.20%             -2%              0.04%           0.02%
20%                  15%             3.00%             5%               0.25%           0.05%
10%                  22%             2.20%             12%              1.44%           0.14%
100%                                                                       Sum:         0.28%
Expected                                          Std. Dev. =
Rate of Return, r                                    Square root of
hat =                  10.00%                        sum =                5.27%
Indirect method                 r hat =      10.00%                                    s=       5.27%

Michael C. Ehrhardt                                        Page 2                                              4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                             Model
COVARIANCE

The covariance is a measure that combines the variance of a stock's return with the tendency of those returns
to move up or down at the same time another stock moves up or down.

To calculate the covariance, there are a few steps. First find the differences of all the
possible returns from the expected return; do this for both stocks. Second, multiply the
differences of both stocks. Third, multiplythe previous product by the probability of its
occurrence. Fourth, find the some of all the weighted products. The result is the covariance.

Calculation of covariance between F and G

Probability of       Deviation of F     Deviation of G     Product of       Product *
Occurrence           from r hat         from r hat        deviations         Prob.

10%                   -4%                4%            -0.1600%          -0.02%
20%                   -2%                2%            -0.0400%          -0.01%
40%                    0%                0%             0.0000%          0.00%
20%                    2%                -2%           -0.0400%          -0.01%
10%                    4%                -4%           -0.1600%          -0.02%
100%
Covariance =
sum =                  -0.048%

Calculation of covariance between F and H

Probability of       Deviation of F     Deviation of H     Product of       Product *
Occurrence           from r hat         from r hat        deviations         Prob.

10%                   -4%               -6%             0.2400%          0.02%
20%                   -2%               -4%             0.0800%          0.02%
40%                    0%               -2%             0.0000%          0.00%
20%                    2%                5%             0.1000%          0.02%
10%                    4%               12%             0.4800%          0.05%
100%
Covariance =
sum =                   0.108%

Calculation of covariance between F and E

Probability of       Deviation of F     Deviation of E     Product of       Product *
Occurrence           from r hat         from r hat        deviations         Prob.

10%                   -4%                0%             0.0000%          0.00%
20%                   -2%                0%             0.0000%          0.00%
40%                    0%                0%             0.0000%          0.00%
20%                    2%                0%             0.0000%          0.00%
10%                    4%                0%             0.0000%          0.00%
100%
Covariance =
sum =                   0.000%

Michael C. Ehrhardt                                            Page 3                                             4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                                 Model

CORRELATION COEFFICIENT
Like covariance, the correlation coefficient also measures the tendency of two stocks to move together, but it is
standardized and it is always in the range of -1 to +1. The correlation coefficient is equal to the covariance
divided by the product of the standard deviations.

Calculation of the correlation between F and G

rFG = Covariance FG                ÷              SigmaF * SigmaG
=          -0.048%             ÷                 2.19%            2.19%
=          -0.048%             ÷                0.048%
rFG =               -1.0

Calculation of the correlation between F and H

rFH = Covariance FH                ÷              SigmaF * SigmaH
=           0.108%             ÷                 2.19%            5.27%
=           0.108%             ÷                0.116%
rFH =             0.935

PORTFOLIO RISK AND RETURN: THE TWO-ASSET CASE

Suppose there are two assets, A and B. w A is the percent of the portfolio invested in asset A.
Since the total percents invested in the asset must add up to 1, (1-w A) is the percent of the
portfolio invested in asset B.

The expected return on the portfolio is the weighted average of the expected returns on
asset A and asset B.

^           ^                    ^
r p  w A r A  (1  w A ) r B

The standard deviation of the portfolio, sp, is not a weighted average. It is:

s p  WAs A  (1  WA )2 s B  2WA (1  WA ) r AB s A s B
2 2                 2

ATTAINABLE PORTFOLIOS: THE TWO ASSET-CASE

Asset A              Asset B
Expected return, r hat         5%                    8%
Standard deviation, s          4%                   10%

Using the equations above, we can find the expected return and standard deviation of a
portfolio with different percents invested in each asset.

Michael C. Ehrhardt                                            Page 4                                                 4/30/2012
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Correlation =                      1
Proportion of
Proportion of         Portfolio in
Portfolio in Security A   Security B
(Value of wA)      (Value of 1-w B)                     rp                sp
1.00              0.00                         5.00%              4.0%
0.90              0.10                         5.30%              4.6%
0.80              0.20                         5.60%              5.2%
0.70              0.30                         5.90%              5.8%
0.60              0.40                         6.20%              6.4%
0.50              0.50                         6.50%              7.0%
0.40              0.60                         6.80%              7.6%
0.30              0.70                         7.10%              8.2%
0.20              0.80                         7.40%              8.8%
0.10              0.90                         7.70%              9.4%
0.00              1.00                         8.00%             10.0%

rAB = +1: Attainable Set of Risk/Return
Combinations
10%
Expected return

5%

0%
0%       5%          10%           15%
Risk, sp

Correlation =                      0

Proportion of
Proportion of         Portfolio in
Portfolio in Security A   Security B
(Value of wA)      (Value of 1-w A)                     rp                sp
1.00              0.00                         5.00%              4.0%
0.90              0.10                         5.30%              3.7%
0.80              0.20                         5.60%              3.8%
0.70              0.30                         5.90%              4.1%
0.60              0.40                         6.20%              4.7%
0.50              0.50                         6.50%              5.4%
0.40              0.60                         6.80%              6.2%
0.30              0.70                         7.10%              7.1%
0.20              0.80                         7.40%              8.0%
0.10              0.90                         7.70%              9.0%
0.00              1.00                         8.00%             10.0%

Michael C. Ehrhardt                                                         Page 5            4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                           Model

rAB = 0: Attainable Set of Risk/Return
Combinations
10%

Expected return    5%

0%
0%          5%         10%          15%

Risk, sp

Correlation =                                 -1

Proportion of
Proportion of         Portfolio in
Portfolio in Security A   Security B
(Value of wA)      (Value of 1-w A)                                      rp                 sp
1.00              0.00                                          5.00%               4.0%
0.90              0.10                                          5.30%               2.6%
0.80              0.20                                          5.60%               1.2%
0.70              0.30                                          5.90%               0.2%
0.60              0.40                                          6.20%               1.6%
0.50              0.50                                          6.50%               3.0%
0.40              0.60                                          6.80%               4.4%
0.30              0.70                                          7.10%               5.8%
0.20              0.80                                          7.40%               7.2%
0.10              0.90                                          7.70%               8.6%
0.00              1.00                                          8.00%              10.0%

rAB = -1: Attainable Set of Risk/Return
Combinations
10%
Expected return

5%

0%
0%          5%         10%               15%
Risk, sp

Michael C. Ehrhardt                                                                          Page 6             4/30/2012
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ATTAINABLE AND EFFICIENT PORTFOLIOS: MANY ASSETS

OPTIMAL PORTFOLIOS

Michael C. Ehrhardt                        Page 7    4/30/2012
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EFFICIENT SET WITH A RISK-FREE ASSET

OPTIMAL PORTFOLIO WITH A RISK-FREE ASSET

Michael C. Ehrhardt                          Page 8   4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                         Model

CALCULATING BETAS

We downloaded stock prices and dividends from http://finance.yahoo.com for General
Electric using its ticker symbol, GE. We also downloaded data for the S&P 500 (^SPX)
which contains most actively traded stocks, and the Fidelity Magellan mutual fund
(FMAGX). We computed returns, as shown in Chapter 4. We also obtained the monthly
rates on 3-month Treasury bills from the FRED II data base at the St. Louis Federal
Reserve, http://research.stlouisfed.org.

rRF, Risk-free
rM, Market                       rp, Fidelity  rate (Monthly                 Excess stock
Return (S&P                      Magellan Fund return on 3     Excess market    return
Date             500 Index)     rj, GE Return       Return      month T-bill) return (rM-rRF)   (rj-rRF)
March 2003                       0.8%             6.0%             1.1%         0.09%            0.7%         5.9%
February 2003                   -1.7%             4.7%            -1.2%         0.10%           -1.8%         4.6%
January 2003                    -2.7%            -5.0%            -2.8%         0.10%           -2.8%        -5.1%
December 2002                   -6.0%            -9.5%            -7.2%         0.10%           -6.1%        -9.6%
November 2002                    5.7%             7.4%             5.2%         0.10%            5.6%         7.3%
October 2002                     8.6%             2.4%             9.4%         0.13%            8.5%         2.3%
September 2002                 -11.0%           -17.7%           -10.8%         0.14%          -11.1%       -17.8%
August 2002                      0.5%            -6.4%             1.0%         0.14%            0.4%        -6.5%
July 2002                       -7.9%            10.8%            -7.2%         0.14%           -8.0%        10.7%
June 2002                       -7.2%            -6.1%            -7.7%         0.14%           -7.4%        -6.3%
May 2002                        -0.9%            -1.3%            -0.3%         0.14%           -1.1%        -1.4%
April 2002                      -6.1%           -15.6%            -6.4%         0.14%           -6.3%       -15.8%
March 2002                       3.7%            -2.9%             3.4%         0.15%            3.5%        -3.0%
February 2002                   -2.1%             4.1%            -1.7%         0.14%           -2.2%         4.0%
January 2002                    -1.6%            -7.3%            -3.1%         0.14%           -1.7%        -7.4%
December 2001                    0.8%             4.6%             0.7%         0.14%            0.6%         4.4%
November 2001                    7.5%             5.7%             7.5%         0.16%            7.4%         5.6%
October 2001                     1.8%            -2.1%             2.4%         0.18%            1.6%        -2.3%
September 2001                  -8.2%            -8.6%            -8.1%         0.22%           -8.4%        -8.8%
August 2001                     -6.4%            -6.0%            -6.5%         0.28%           -6.7%        -6.3%
July 2001                       -1.1%           -10.9%            -1.5%         0.29%           -1.4%       -11.2%
June 2001                       -2.5%             0.0%            -2.5%         0.29%           -2.8%        -0.3%
May 2001                         0.5%             1.0%             0.9%         0.30%            0.2%         0.7%
April 2001                       7.7%            15.9%             8.8%         0.32%            7.4%        15.6%
March 2001                      -6.4%            -9.6%            -6.4%         0.37%           -6.8%       -10.0%
February 2001                   -9.2%             1.1%            -9.4%         0.41%           -9.6%         0.7%
January 2001                     3.5%            -4.1%             3.3%         0.43%            3.0%        -4.5%
December 2000                    0.4%            -3.0%             0.7%         0.48%           -0.1%        -3.4%
November 2000                   -8.0%            -9.6%            -8.5%         0.51%           -8.5%       -10.1%
October 2000                    -0.5%            -5.2%            -1.8%         0.51%           -1.0%        -5.7%
September 2000                  -5.3%            -1.2%            -5.4%         0.50%           -5.8%        -1.7%
August 2000                      6.1%            13.4%             6.4%         0.51%            5.6%        12.9%
July 2000                       -1.6%            -2.2%            -1.2%         0.50%           -2.1%        -2.7%
June 2000                        2.4%             0.7%             3.9%         0.47%            1.9%         0.2%
May 2000                        -2.2%             0.4%            -3.4%         0.48%           -2.7%        -0.1%
April 2000                      -3.1%             1.0%            -4.3%         0.47%           -3.6%         0.6%
March 2000                       9.7%            17.9%             9.0%         0.47%            9.2%        17.4%
February 2000                   -2.0%            -1.2%             1.0%         0.46%           -2.5%        -1.7%
January 2000                    -5.1%           -13.4%            -4.8%         0.44%           -5.5%       -13.8%
December 1999                    5.8%            19.2%             6.8%         0.43%            5.4%        18.8%
November 1999                    1.9%            -4.0%             2.1%         0.42%            1.5%        -4.4%
October 1999                     6.3%            14.3%             6.0%         0.41%            5.8%        13.9%
September 1999                  -2.9%             5.9%            -1.5%         0.39%           -3.2%         5.5%
August 1999                     -0.6%             3.0%            -1.2%         0.39%           -1.0%         2.6%
July 1999                       -3.2%            -3.2%            -3.4%         0.38%           -3.6%        -3.6%
June 1999                        5.4%            11.1%             6.5%         0.38%            5.1%        10.7%

Michael C. Ehrhardt                                        Page 9                                            4/30/2012
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May 1999                            -2.5%                   -3.5%               -3.0%            0.38%              -2.9%           -3.9%
April 1999                           3.8%                   -4.8%                2.4%            0.36%               3.4%           -5.1%

Average return
(annual)                          -8.8%                     -3.4%               -8.2%             3.7%            -12.5%            -7.0%
Standard deviation
(annual)                          17.6%                     29.2%               18.2%             0.5%             17.6%            29.1%
Correlation with market return, r                             0.66                0.99             0.09              1.00             0.66
R-square                                                      0.44                0.98             0.01              1.00             0.44
Slope                                                         1.09                1.02             0.00              1.00             1.09

Using the AVERAGE function and the STDEV function, we found the average historical
returns and standard deviations. (We converted these from monthly figures to annual
figures. Notice that you must multiply the monthly standard deviation by the square root
of 12, and not 12, to convert it to an annual basis.) These are shown in the rows above.
We also use the CORREL function to find the correlation of the market with the other assets

Using the function Wizard for SLOPE, we found the slope of the regression line, which is
the beta coefficient. We also use the function Wizard and the RSQ function to find the
R-Squared of the regression.

Using the Chart Wizard, we plotted the GE returns on the y-axis and the market returns on
the x-axis. We also used the menu Chart > Options to add a trend line, and to display the
regression equation and R2 on the chart. The chart is shown below. We also used the
regression feature to get more detailed data. These results are also shown below.

GE Analysis
The beta coefficient is about 1.10, as shown by the slope coefficient in the regression
equation on the chart. The beta coefficient has a t statistic of 7.07, and there is virtually a
zero chance of getting this if the true beta coefficient is equal to zero. Therefore, this is a
statistically significant coefficient. However, the confidence interval ranges from 0.78 to
1.41, which is very wide. The R2 of about 0.44 indicates that 44% of the variance of the
stock return can be explained by the market. The rest of the stock's variance is due to
factors other than the market. This is consistent with the wide scatter of points in the
graph.

GE Regression Results               (See columns J-N)
Historic
Realized                                           Beta
Returns                                                       Coefficient              1.09
rj = 1.0924 rM + 0.0053                    on GE, rj(%)
R2 = 0.4358                                                                                           t statistic            5.96
30%
Probability of t stat.           0.0%
Lower 95% confidence interval              0.72
Upper 95% confidence interval              1.46
20%

Intercept
Coefficient              0.01
10%
t statistic            0.56
Probability of t stat.          57.6%
0%
Lower 95% confidence interval             -0.01
-30%      -20%      -10%          0%        10%         20%         30%              Upper 95% confidence interval              0.02

-10%               Historic Realized Returns
on the Market,
rM(%)

-20%

Michael C. Ehrhardt                                                   Page 10                                                        4/30/2012
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-20%

Magellan Analysis

The beta coefficient is about 1.02, as shown by the slope coefficient in the regression
equation on the chart. The beta coefficient has a t statistic of 42.86, and there is virtually a
zero chance of getting this if the true beta coefficient is equal to zero. Therefore, this is a
statistically significant coefficient. The confidence interval ranges from 0.97 to 1.07, which
is very small compared to the confidence interval for a single stock. The R2 of about 0.98
indicates that 98% of the variance of the portfolio return can be explained by the market.
This is consistent with the very narrow scatter of points in the graph. The estimate of the
intercept is equal to 0.00, and has a t statistic with a probability of 57.0%. Since this is
greater than 5%, we would say that the coefficient is not statistically significant-- in other
words, the true intercept might well be equal to zero.

Magellan Regression Results        (See columns J-N)
rp = 1.0206 rM + 0.0007                Historic
Realized                                           Beta
R2 = 0.9756
Returns                                                       Coefficient             1.02
on Magellan,
t statistic          42.86
rP(%)
20%                                                            Probability of t stat.          0.0%
Lower 95% confidence interval               0.97
Upper 95% confidence interval               1.07

10%
Intercept
Coefficient            0.00
t statistic          0.57
Probability of t stat.        57.0%
Lower 95% confidence interval            0.00
0%
Upper 95% confidence interval            0.00
-30%     -20%     -10%          0%      10%       20%       30%

Historic Realized Returns
on the Market, rM(%)
-10%

-20%

Michael C. Ehrhardt                                                       Page 11                                            4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                                           Model

The Market Model vs. CAPM

We have been regressing the stock (or portfolio) returns against the market returns.
However, CAPM actually states that we should regress the excess stock returns (the stock
return minus the short-term risk free rate) against the excess market returns (the market
return minus the short-term risk free rate). We show the graph for such a regression
below. Notice that it is virtually identical to the market model regression we used earlier
for GE. Since it usually doesn't change the results whether we use the market model to
estimate beta instead of the CAPM model, we usually use the market model.

(See columns J-N)
CAPM (excess return) Model Regression Results
Beta
Excess Returns
on GE, rS-rRF                                                              Coefficient            1.09
y = 1.0881x + 0.0055
t statistic           5.92
R2 = 0.4326               30%
Probability of t stat.          0.0%
Lower 95% confidence interval              0.72
Upper 95% confidence interval             1.46
20%
Intercept
Coefficient            0.01
10%                                                                        t statistic          0.58
Probability of t stat.        56.3%
Lower 95% confidence interval           -0.01
Upper 95% confidence interval            0.02
0%
-30%     -20%      -10%            0%      10%     20%         30%

Excess Returns
-10%                 on the Market, rM-rRF

-20%

Table 5-4
Regression                           Probability of    Lower 95%         Upper 95%
Coefficient         t Statistic        t Statistic     Confidence        Confidence
Panel a: General Electric
(Market model)

Intercept                                                0.01                 0.56             0.58             -0.01           0.02
Slope                                                    1.09                 5.96             0.00              0.72           1.46

Panel b: Magellan Fund
(Market model)
Intercept                                                0.00                 0.57             0.57              0.00           0.00
Slope                                                    1.02                42.86             0.00              0.97           1.07

Panel c: General Electric
(CAPM: Excess returns)
Intercept                                                0.01                 0.58             0.56             -0.01           0.02
Slope                                                    1.09                 5.92             0.00              0.72           1.46

Note: The market model uses unadjusted returns, the CAPM model uses returns in excess of the risk-free rate.

Michael C. Ehrhardt                                              Page 12                                                       4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                                  Model

Peformance Measures for Magellan

Jensens's Alpha
Intercept from CAPM regression
0.91% per year
0.62 t statistic
54.020% Probability that the intercept is not zero

Sharpe's Reward-to-Variability Ratio
Average annual return in excess of risk-free rate divided by standard deviation

Magellan            -11.8%        divided by        18.2%
-0.65

S&P 500             -12.5%        divided by        17.6%
-0.71

Treynor's Reward-to-Volatility Ratio
Average annual return in excess of risk-free rate divided by beta

Magellan            -11.8%        divided by                1.02
-0.116

S&P 500             -12.5%        divided by                1.00
-0.125

Michael C. Ehrhardt                                   Page 13                                          4/30/2012
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Michael C. Ehrhardt                        Page 21   4/30/2012
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Excess portfolio
return
(rp-rRF)
1.0%
-1.3%
-2.9%
-7.3%
5.1%
9.3%
-10.9%
0.8%
-7.3%
-7.8%
-0.5%
-6.5%
3.2%
-1.9%
-3.3%
0.6%
7.3%
2.2%
-8.3%
-6.8%
-1.8%
-2.8%
0.6%
8.4%
-6.8%
-9.8%
2.8%
0.2%
-9.0%
-2.3%
-5.9%
5.9%
-1.7%
3.4%
-3.9%
-4.8%
8.6%
0.5%
-5.3%
6.4%
1.6%
5.6%
-1.9%
-1.6%
-3.7%
6.1%

Michael C. Ehrhardt                        Page 22   4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                             Model
-3.4%
2.0%

-11.8%

18.2%
0.99
0.97
1.02

(See columns J-N)                    SUMMARY OUTPUT

1.09         Regression Statistics
Multiple R 0.660151
R Square       0.4358
0.423535
0.063974
Standard Error
Observations       48

ANOVA
df          SS        MS        F   Significance F
Regression          1 0.145419213 0.145419 35.53134 3.31E-07
Residual           46 0.188264329 0.004093
Total              47 0.333683542

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%
Intercept   0.005252 0.009331973 0.562764 0.576328 -0.01353 0.024036 -0.01353
X Variable 11.092423 0.183267374 5.960817 3.31E-07 0.723526 1.461321 0.723526

Michael C. Ehrhardt                                Page 23                                       4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                             Model

(See columns J-N)                    SUMMARY OUTPUT

1.02         Regression Statistics
Multiple R 0.987709
R Square 0.975568
0.975037
0.008313
Standard Error
Observations       48

ANOVA
df          SS        MS        F   Significance F
Regression          1 0.126920945 0.126921 1836.783 9.92E-39
Residual           46 0.003178581 6.91E-05
Total              47 0.130099526

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%
Intercept   0.000694 0.001212568 0.572575 0.569721 -0.00175 0.003135 -0.00175
X Variable 11.020579     0.0238132 42.85771 9.92E-39 0.972646 1.068513 0.972646

Michael C. Ehrhardt                                Page 24                                       4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                             Model

(See columns J-N)                    SUMMARY OUTPUT

1.09         Regression Statistics
Multiple R 0.657757
R Square 0.432644
0.42031
0.063991
Standard Error
Observations       48

ANOVA
df          SS        MS        F   Significance F
Regression          1 0.143638947 0.143639 35.07783 3.78E-07
Residual           46 0.188363734 0.004095
Total              47 0.33200268

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%
Intercept   0.005488 0.009432336 0.58187 0.563495     -0.0135 0.024475   -0.0135
X Variable 11.088092 0.183716906 5.922654 3.78E-07 0.718289 1.457894 0.718289

Michael C. Ehrhardt                                Page 25                                       4/30/2012
8d5577e6-e498-474c-8b93-4cd9bac3deb0.xls                                                          Model

LINEST Results: y=mx+b
Slope (m)      1.02050123   0.000756   Intercept (b)
m
Std. Error of 0.023867615   0.001225   Std. Error of b
R2            0.975455386   0.008313   Std. Error of y
F             1828.138238         46   Degrees of freedom
SS Regression 0.126347973   0.003179   SS Residual

42.75673325 0.617118 t-stat for intercept
t-stat for slope
Prob of t      1.10246E-38 0.540199 Prob of t

Michael C. Ehrhardt                                Page 26                                     4/30/2012
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Upper 95.0%
0.024036
1.461321

Michael C. Ehrhardt                              Page 36   4/30/2012
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Upper 95.0%
0.003135
1.068513

Michael C. Ehrhardt                              Page 37   4/30/2012
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Upper 95.0%
0.024475
1.457894

Michael C. Ehrhardt                              Page 38   4/30/2012

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