Describe how you collaborated with other team members. Describe your contribution and also other team members contributions. [5 marks]

FINS5542, Assignment 3, Group Assignment (Group Size of 5)
Date Due: Tuesday, 22 November by 11pm.
Electronic submission of Questions 1, 2 and 4 is via the course website. Questions 1 and 2 are to be done and submitted as a group.
Each group member should write their own answer to question 4 and
include in the group submission. (The work for questions 1 and 2
should be fairly distributed among group members. Mark deductions
may occur if there has been an inappropriate work distribution.) The
presentation in Question 3 is an individual presentation and you will
receive an individual mark for this question. You need to have formed
your group by 11pm Monday 7 November via the Assignment Group
Builder tool on our course website, under Assessments. If you have
less than 5 group members you may be allocated additional group
members. If you are unable to form a group, please email Johnny Lu
tianyun.lu@unsw.edu.au by 11pm Thursday 3 November and you will
be assigned to a group. When working with your group members, this
can be done electronically, e.g. email and Skype.
1. For 4 S&P100 stocks (that are currently components of the S&P100
Index), for the 25 year period starting July 1981 and ending June 2006,
compute quarterly realized betas from daily data. The market return
in the beta estimation should be the S&P500 return. Data for these
beta calculations should be sourced through CRSP from WRDS. You
have flexibility in choosing the software that you will use for these
beta calculations.
For each stock, find two macroeconomic variables, that help explain quarterly beta. You should report the two variables that are
the strongest with the main criteria being a high a R2 as possible
from simple linear regressions of realized beta onto a constant and the
variable. Robust p-values (robust to changing variability) should also
be considered. These simple linear regressions should be estimated in
Stata.
1
The two variables for each stock, can be different or the same, between the stocks.
[20 marks]
2. For the following 4 industries, US Smoke, Books, Drugs, and Steel,
download from Ken French’s website from the 48 industry classification, monthly industry returns (equal weighted) and for each industry
portfolio develop an appropriate multi-factor model (either the Fama
and French 3 factor or Cahart 4 factor) for its monthly return, over a
chosen time period of at least 20 years, starting January 2000.
Key criteria in your analysis should be the use of robust p-values
(robust to changing variability) and the adjusted R2
. You should
also display plots of residuals versus fitted values for the analysis of
residuals. You are not required to conduct a formal hypothesis test on
the residuals. These multiple linear regressions should be estimated
in Stata.
[10 marks]
3. Individual Presentation – 4 minutes: (scheduled in week 9 or 10
during the lecture time or an alternatively arranged time)
Discuss the momentum effect in stock returns.
This will be conducted as an audio Skype call where you are to
discuss the topic for approximately 4 minutes. Please email (by 11pm
Sunday 30 October) Johnny Lu, both first name and last name, your
student id number, your Skype name, and your preferred presentation
time. A class announcement this week will provide further details on
presentation times. Where possible we will try to accommodate your
preferred 3 hour window. You will be provided the skype name of your
examiner which you should send a contact request to before the day
of your presentation. On your presentation day please skype audio
call your examiner at your allocated time. Your presentation will be
marked on the basis of the content and the clarity of your discussion,
both of equal importance. There is no written submission requirement
for this question.
2
[15 marks]
4. Individual Written Summary
Describe how you collaborated with other team members. Describe
your contribution and also other team members contributions.
[5 marks]