BUSINESS STATISTICS AND REGRESSION

QUESTION

MAE 356 Analytical Methods in Economics and Finance, Trimester 1, 2012

ASSIGNMENT 1: Due date Friday 18th May 5 pm.
Word limit: Maximum 1500 words plus computer analysis
Weight: 15%

The capital asset pricing model (CAPM) is an important model in the field of finance/financial
economics. It explains variations in the rate of return on a security as a function of the rate of
return on a portfolio consisting of all publicly traded stocks, which is known as the market
portfolio. Generally, the rate of return on any investment is measured relative to its opportunity
cost, which is measured as the return on a risk-free asset. The resulting difference is called the
risk premium, since it is the reward or punishment for making a risky investment. The CAPM
says that the risk premium on security j is proportional to the risk premium on the market
portfolio. That is,
where r
j
and r
f
( )
rrrr −=β

fmjfj
are the returns to security j and the risk-free rate, respectively, r
is the return on the
market portfolio, and
j
m
β
is the j’th security’s “beta” value. A stock’s beta is important to investors
because it reveals the stock’s volatility. It measures the sensitivity of security j’s return to variation in
the whole stock market. As such, values of beta less than one (1) indicate that the stock is
‘defensive’, since its variation is less than the market’s. A beta greater than one (1) indicates an
‘aggressive stock.’ Investors usually want an estimate of a stock’s beta before purchasing it. The
CAPM model shown above is the ‘economic model’ in this case. The ‘econometric model’ is obtained
by including an intercept in the model (even though theory says it should be zero) and an error term,
( )
errrr
+−+=− βα

fmjjfj
Data:
Please download the required data kept in the file ‘Assignmentdata_T12012’ in excel format
from the D2L site. The file contains data on monthly returns of six firms, viz., Microsoft (MSFT),
General Electric (GE), General Motors (GM), IBM, Disney (DIS) and Mobil-Exxon (XOM) from
January 1998 to December 2008 and with 132 observations. In the data file, the first column is
named “OBS”, under which you will find the observation dates. The second column (column B)
till the seventh column (column G) is labelled “DIS”, “GE”, “GM”, “IBM”, “MSFT” and “XOM”,
respectively. The last two columns represent the rate of return on the market portfolio (MKT),
and the rate of return on the risk free asset (RISKFREE).

You should use MSExcel for your statistical analysis to answer the following questions.
Please make
sure you include all your regression output as an appendix to your submission.
(a) Using XOM and MKT data plot the returns for the entire period and comment on the
relative fluctuations of these two variables.        [1]

(b) Calculate and construct the series of the risk premium on Microsoft and the risk
premium on the market portfolio for the entire period, using the data for “MSFT”,
“MARKET” and “RKFREE”.        [1]

(c) Present the descriptive statistics of monthly returns of GE, GM, IBM and DIS data.
Interpret and compare the measures of central tendency and deviation of the variables.
[2]

(d) Estimate the CAPM model for Microsoft and GM, and comment on their estimated beta
values.            [2]
α
should be zero. Does this seem
correct given your estimates?        [2]
(e) Finance theory suggests that the intercept parameter
j
(f) Suppose a financial consultant believes that Microsoft’s beta value is equal to 1. Test the
consultant’s claim of Microsoft’s beta value at 1% level of significance against the alternative
that it is less than one. Interpret your result.      [2]
(g) Predict the risk premium for Microsoft given the risk premium for market portfolio of 2%
and 7%.          [1]

(h)  Divide the data series into two halves, one for January 1998 to September 2001 and the
other for October 2001 to December 2008. Using 5% significance, test the null hypothesis
that both alpha and beta for Microsoft are equal over the two sub-samples, i.e., test for
parameter stability over the two periods.       [2]
(i) Briefly summarize your findings about Microsoft’s stock and its relationship to the stock
market.          [2]

Notes:  This is an individual assignment. All Excel worksheets should be attached at the end
of your submitted assignment. These should clearly demonstrate the work undertaken
independently by you.  Submissions should be made both in hardcopy and online on DSO.
On-campus students must submit to the campus specific faculty office while the off campus
students submit the assignments as per the information provided in the unit guide and should
contact the Division of Student Affairs (DSA).

SOLUTION

OBS Market Premium Stock Premium SUMMARY OUTPUT
MSFT Jan 98 to Sep 01
Jan-98 -0.045721 0.104005 Regression Statistics
Feb-98 0.02201 0.084934 Multiple R 0.624866
Mar-98 -0.000978 0.003747 R Square 0.390458
Apr-98 -0.036418 -0.040297 Adjusted R Square 0.376282
May-98 -0.071425 -0.104616 Standard Error 0.126028
Jun-98 -0.015076 0.230789 Observations 45
Jul-98 -0.070714 -0.033032
Aug-98 -0.204577 -0.174255 ANOVA
Sep-98 0.023556 0.106951 df SS MS F Significance F
Oct-98 0.038837 -0.073567 Regression 1 0.437492 0.437492 27.54473 4.47E-06
Nov-98 0.017566 0.107882 Residual 43 0.682968 0.015883
Dec-98 0.019113 0.092843 Total 44 1.120461
Jan-99 -0.005744 0.21774
Feb-99 -0.083165 -0.187203 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Mar-99 -0.007718 0.148425 Intercept 0.051118 0.023699 2.156949 0.036643 0.003324 0.098912 0.003324 0.098912
Apr-99 0.00448 -0.137268 X Variable 1 1.726914 0.329042 5.248307 4.47E-06 1.063338 2.390491 1.063338 2.390491
May-99 -0.06492 -0.051886
Jun-99 0.00664 0.073358 SUMMARY OUTPUT
Jul-99 -0.075135 -0.09301 Oct 01 to Dec 08
Aug-99 -0.054983 0.03366 Regression Statistics
Sep-99 -0.067877 -0.066617 Multiple R 0.579881
Oct-99 0.018388 -0.021576 R Square 0.336262
Nov-99 -0.008854 -0.062084 Adjusted R Square 0.328453
Dec-99 0.032905 0.231286 Standard Error 0.058221
Jan-00 -0.093613 -0.21553 Observations 87
Feb-00 -0.02137 -0.139985
Mar-00 -0.005008 0.130251 ANOVA
Apr-00 -0.112167 -0.396229 df SS MS F Significance F
May-00 -0.085797 -0.149797 Regression 1 0.145968 0.145968 43.06256 3.96E-09
Jun-00 -0.004641 0.222431 Residual 85 0.288122 0.00339
Jul-00 -0.075855 -0.186094 Total 86 0.43409
Aug-00 0.013471 -0.06234
Sep-00 -0.110339 -0.195279 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Oct-00 -0.084834 0.081699 Intercept -0.00202 0.007009 -0.2889 0.773364 -0.01596 0.011911 -0.01596 0.011911
Nov-00 -0.163736 -0.228159 X Variable 1 0.943024 0.143705 6.562207 3.96E-09 0.657299 1.228749 0.657299 1.228749
Dec-00 -0.037344 -0.301699
Jan-01 -0.008737 0.359511
Feb-01 -0.149397 -0.083907
Mar-01 -0.11461 -0.117413
Apr-01 0.046484 0.201437
May-01 -0.023889 -0.013343
Jun-01 -0.051631 0.021068
Jul-01 -0.054721 -0.129688
Aug-01 -0.09282 -0.171827
Sep-01 -0.11532 -0.126848
Oct-01 0.007037 0.115478
Nov-01 0.061454 0.086933
Dec-01 0.001481 0.015411
Jan-02 -0.03295 -0.05523
Feb-02 -0.039035 -0.101618
Mar-02 0.027593 0.016668
Apr-02 -0.067179 -0.151007
May-02 -0.027348 -0.042722
Jun-02 -0.086913 0.057775
Jul-02 -0.098137 -0.139852
Aug-02 -0.008576 0.006366
Sep-02 -0.115675 -0.124502
Oct-02 0.060758 0.208251
Nov-02 0.049106 0.066566
Dec-02 -0.064669 -0.115035
Jan-03 -0.03489 -0.093472
Feb-03 -0.027358 -0.009843
Mar-03 -0.001077 0.010109
Apr-03 0.071867 0.044832
May-03 0.052297 -0.048377
Jun-03 0.008392 0.033913
Jul-03 0.01433 0.021231
Aug-03 0.015198 -0.005545
Sep-03 -0.017622 0.039745
Oct-03 0.051181 -0.063107
Nov-03 0.007607 -0.02545
Dec-03 0.037262 0.056296
Jan-04 0.014794 0.00196
Feb-04 0.006137 -0.049836
Mar-04 -0.019915 -0.069539
Apr-04 -0.03232 0.040045
May-04 0.005047 -0.005253
Jun-04 0.010273 0.07754
Jul-04 -0.050461 -0.015231
Aug-04 -0.011696 -0.053371
Sep-04 0.005975 -0.001759
Oct-04 0.00033 -0.005907
Nov-04 0.027923 0.048325
Dec-04 0.0161 -0.022437
Jan-05 -0.048177 -0.038087
Feb-05 -0.002275 -0.064544
Mar-05 -0.042927 -0.065338
Apr-05 -0.052292 0.019642
May-05 0.010406 -0.004585
Jun-05 -0.018319 -0.067059
Jul-05 0.011041 -0.001292
Aug-05 -0.039353 0.038827
Sep-05 -0.021251 -0.092123
Oct-05 -0.057744 -0.038126
Nov-05 0.000696 0.040446
Dec-05 -0.035984 -0.094735
Jan-06 -0.003158 0.033212
Feb-06 -0.045884 -0.086513
Mar-06 -0.02687 -0.033277
Apr-06 -0.033162 -0.158589
May-06 -0.077992 -0.105335
Jun-06 -0.047236 -0.018142
Jul-06 -0.052302 -0.017782
Aug-06 -0.024565 0.022254
Sep-06 -0.027038 0.017712
Oct-06 -0.014424 -0.001784
Nov-06 -0.026084 -0.023677
Dec-06 -0.036857 -0.03065
Jan-07 -0.030572 -0.01652
Feb-07 -0.065428 -0.135357
Mar-07 -0.037561 -0.06116
Apr-07 -0.007657 0.026723
May-07 -0.008056 -0.018557
Jun-07 -0.060068 -0.085066
Jul-07 -0.082803 -0.067338
Aug-07 -0.029897 -0.047039
Sep-07 0.006473 -0.009021
Oct-07 -0.013978 0.209671
Nov-07 -0.081469 -0.116406
Dec-07 -0.032922 0.030944
Jan-08 -0.078945 -0.10091
Feb-08 -0.04274 -0.182973
Mar-08 -0.02285 0.031006
Apr-08 0.038564 -0.007647
May-08 0.004345 -0.022636
Jun-08 -0.095565 -0.045542
Jul-08 -0.02898 -0.080897
Aug-08 -0.005598 0.048679
Sep-08 -0.1077 -0.031626
Oct-08 -0.187266 -0.165897
Nov-08 -0.085506 -0.08897
Dec-08 0.021182 -0.038876

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