Least Squares Estimate of Beta
From the list of companies in the file “4fg32016.xls”,
choose one industry that you think is highly risky and
another industry that you think is relatively safe.
Divide your sample into three periods: Jan 2006 –
Dec 2008, Jan. 2009 Dec.
2011 and Jan. 2012 –
Dec. 2014 time intervals and choose one of the three
periods with which you will work.
A) Using your computer regression software, the
observations that you have chosen and equation 2.1
(see page 3), estimate by ordinary least squares the
parameters of α and β of one firm in each of these
two industries. Do the estimates of beta correspond
well with your prior intuition or beliefs? Why or why
B) For one of these companies, make a time plot of
the historical company risk premium, the risk premium
predicted by the regression model, and the associated
residuals. Are there any episodes or dates that
appear to correspond with unusually large residuals?
If so, attempt to interpret them.
C) For each of the companies, test the null hypothesis
that α = 0 against the alternative hypotheses that
α ≠ 0, using a significance level of 95%. Would
rejection of the null hypotheses imply that CAPM has
been invalidated? Why or why not?
D) For each company, construct a 95% confidence
interval for β . Then test the null hypotheses that the
company’s risk is the same as the average risk over
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