Data Analysis Project for Desklib

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Data Analysis Project
Name:
Institution:

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Task 1: CAPM and Fama French three factors model. [6 marks]
a. Pls download the daily price data of the assigned stock from Yahoo finance
(https://au.finance.yahoo.com/) from January 3, 2011 to December 31, 2018.
Student ID ending number Stock
0 The Boeing Company
1 IBM
2 Microsoft
3 Wal-Mart
4 American Express
5 Apple
6 Goldman Sachs
7 Intel
8 Google (Alphabet)
9 Amazon
b. Download Fama French daily three factors data from Ken French’s data library
(https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.ht
ml).
c. Calculate daily log return of your assigned stock using the daily adjusted price (Adj
Close).
d. Merge your stock data with the Fama French three factors data. [Hint: you can use the
function of “merge”], and fill up the following summary statistic table. [Ensure stock
return and three factors are measured in the same scale.] [2 marks]
Table 1: Summary Statistics (2011-2018)
Variable Stock Return Mkt.Rf SMB HML RF
Min -0.0624011 -6.970 -1.9200 -1.6900 0
Max 0.045543 5.0600 3.600000 2.390 0.01
Mean 0.0004208 0.0447 -0.005266 -0.006607 0.001412
Median 0.0004884 0.0600 -0.0100 -0.0300 0
SD 0.00988367 0.9461735 0.5150679 0.4845208 0.002458
N 2010 2010 2010 2010 2010
(Mkt.Rf stands for market risk premium, SD stands for standard deviation and N stands

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for number of observations)
e. Pls create a new variable Stock.Rf, which equals to the difference between Stock
Return and RF, and run a regression of :
Stock . Rf =α + βMkt . Rf +u.
Report the regression results in a table (1 mark) and also make a figure, where
Mkt.Rf is in the X-axis, and Stock.Rf is in the Y-axis, and also plot the fitted line
in the figure (1 mark).
Call:
lm(formula = Merged_data$Stock_Returns ~ Merged_data$Mkt.RF)
Residuals:
Min 1Q Median 3Q Max
-0.061725 -0.005351 0.000098 0.005811 0.044641
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0003866 0.0002202 1.756 0.079304 .
Merged_data$Mkt.RF 0.0007702 0.0002325 3.312 0.000942 ***
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.009859 on 2007 degrees of freedom
Multiple R-squared: 0.005436, Adjusted R-squared: 0.004941
F-statistic: 10.97 on 1 and 2007 DF, p-value: 0.0009421
At significance level 0.05, the results above exhibit the p-value of 0.0009421
which is less than 0.05 thus the model is adequate. Moreover, the coefficients
exhibit the regression estimate as follows;
stock . Rf =0.00386+0.0007702 Mkt . Rf