RESIT Assessment – Statistical Exercise.

RESIT Assessment – Statistical Exercise.Instructions
Students should refer to the original assignment instruction outlined in the course guide.
Consider any feedback you may have received and submit your revised assignment. In addition, include a new section at the end of the assignment (up to a maximum of 200 words) in which you comment on what you changed in your assignment in response to any feedback received or your reflection on the task.

The FEEDBACK IS :
Youhaven’tsubmittedtheexcelwiththedataandtheregressions. Thesubmittedexcelfileistheexamplethatispostedonmoodle.

Theintroductionandthediscussionon CAPM areveryconfusing.

Itisnotclearwhatsortofdataisconsideredfortheanalysis.

Verygeneraldiscussionisgivenonregressionanalysis.

Whydoweneedhistograms?

Needtocollectdataanddotheregressionanalysisinordertogetsomeconclusionsontheperformanceof CAPM.
We test the CAPM for this coursework; you will use one market index and a list of 10 companies’ weekly data and these companies should be from at least two sectors. Consider three sample periods: (1) Jan 2006 – Dec 2008, (2) Jan 2009 – Dec 2011 and (3) Jan 2012 – Dec 2014. The required data can be downloaded from Yahoo finance: http://uk.finance.yahoo.com/
Tasks:
(1) Make sure that your choice of companies and sectors would capture high market capitalisation.
(2) Using data for the entire sample period, run time-series regression on each of the selected companies onto a constant and market excess return and verify whether there exists a significant beta.
(3) Report the t-static for alpha and the R^2 for each company.
(4) Do a cross-sectional regression: for all i = 10.
(5) Discuss your results and merits and demerits of CAPM analysis.
(6) Discuss whether your results are sensitive to sector characteristics.
(7) Word limit: 1500
Brief notes:
1. Why use simple regression to estimate ß? Here dependent variable is stock return of individual firms (yi) and independent variable is market return (xi).
Because ßi=sim/(sm^2)=Covariance (market return(xi), individual stock return(yi))/variance of market return (xi)
In simple regression,

So the coefficient is actually ßi=sim/(sm^2)

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