As a group, you will describe and analyse daily returns (see the ‘Problems’ section for a formal definition) of two stocks in the period 2015 – 2018. The data are described in the ‘Data’ section at the end of this document.

STAT0004 Take Home Assessment 2019
Deadline: 16:00 Wednesday 24 April 2019
You will work in a group (of approximately 3 students) to produce a single report.
1 Rules for the take home assessment
• Your group will submit, via the Submit your take home assessment Moodle page, one
PDF file containing your report and one R program file.
• Each group member must click their respective “Submit” buttons in order for the
group’s submission to be successful and final. By ticking the submission declaration
box in Moodle you are agreeing to the following declaration:
Declaration: I am aware of the UCL Statistical Science Department’s regulations on plagiarism for assessed coursework. I have read the guidelines in
the student handbook and understand what constitutes plagiarism. I hereby
affirm that the work my group is submitting for this in- course assessment is
entirely our own.
• The Turn-It-In R plagiarism detection system may be used to scan your submission for
evidence of plagiarism and collusion.
• You will work together within your group and the usual plagiarism and collusion regulations do not apply to this form of interaction. However, they do apply to collusion
with other groups or plagiarism of work from other groups or from other sources.
• Any plagiarism will normally result in zero marks for all students involved, and may
also mean that your overall examination mark is recorded as non-complete. Guidelines
as to what constitutes plagiarism may be found in Departmental Student Handbooks.
The relevant excerpt from the Statistical Science handbook is also posted on Moodle.
• Late submission will incur a penalty unless there are extenuating circumstances (e.g.
medical) supported by appropriate documentation. Penalties are set out in the latest
editions of the Statistical Science Department student handbooks, available from the
departmental web pages.
• Failure to submit this in-course assessment may mean that your overall examination
mark is recorded as “non-complete”, i.e., you will not obtain a pass for the course.
• All members of a group will be awarded the same mark for the assignment.
• I may ask you as a group to come and discuss your output with me.
• You will receive, via Moodle, feedback on your work and a provisional grade — grades
are provisional until confirmed by the Statistics Examiners’ Meeting in June 2019.
1
2 Tasks description
As a group, you will describe and analyse daily returns (see the ‘Problems’ section for a
formal definition) of two stocks in the period 2015 – 2018. The data are described in the
‘Data’ section at the end of this document. You do not need to investigate their source
further — just report on the data as they are presented to you. Also do not introduce other
data into your work. Your group will prepare and submit a single, short, structured report
that addresses each of the problems set out below. All the summary statistics in the report
should come from an R program, or be readable from plots in the report. Your report and
program will be marked by me (Tengyao Wang) and you may be required to discuss them
with me. You will receive group specific feedback on your submission.
To complete this assignment successfully you need to start work very soon after
the assignment is set and to plan your time carefully. It is quite possible to
complete the assignment by the end of the second term.
Problems
The return of a stock on a given trading day is defined as the increase in its closing price
from the previous trading day (negative if it is a decrease). Mathematically, if pi
is the
closing price on trading day i, then the return on day i is pi − pi−1.
Please address the following problems in your take home assessment.
1. Using techniques such as summary statistics and plots, describe the returns of the two
stocks assigned to your group on each of the trading days (except 2 Jan 2015, where
closing price of the previous trading day is unknown). Your description should include
both univariate and multivariate analysis.
2. A stock analyst claims that there is increased market volatility in 2018 compared to
previous years, represented by an increase in the magnitude of stock price movements.
(a) Using the absolute values of the returns for the first of your two stocks, carry out
an appropriate two sample t-test for the analyst’s claim.
(b) Explain to this analyst, in non-technical terms, the result of your test in a single
sentence.
3. An investor wants to predict returns of a stock on a given day using its return from
the previous trading day.
(a) Using the second of your two stocks, build an appropriate simple linear model
to investigate the feasibility of her strategy. Set out the model in mathematical
notation and find the regression coefficients.
(b) Explain to this investor, in non-technical terms, the meaning of your regression
coefficients and how well her strategy might work.
2
For the linear model, you may assume that the residual plots raise no issues about
model assumptions or fit and you should not attempt to analyse or study them (I
know that this is not what normally happens but I am trying to make your life easier).
Report
Name your report group*.pdf, where * should be replaced with your group number (e.g., for
Group 01, it should be group01.pdf). The report should be consistent with the following:
• You must use the Microsoft Word template provided on the Moodle page for your
report and are not allowed to change its font, font sizes or margins (if you wish to be
allowed to use alternative word processing software then you must agree the details
with me before submission). If the template has been changed, up to 4% of marks
can be lost and I will reformat the document to the template standard, to which the
following point will apply.
• The report must not be longer than 2 pages (2 sides) in A4 paper, including figures. I
will only mark the first 2 pages of any report. Note that this doesn’t mean that you
should aim to fill all the space available to you. Writing more text doesn’t necessarily
get you more marks.
• The report must be capable of being read on its own: i.e., it should not refer to the R
program but just contain data/plots from the program’s output.
• Please save your report as a PDF file from Microsoft Word (FILE, Export, Create
PDF/XPS).
• It must be written in clear comprehensible English with readable and well-labelled
figures.
• Your report should be anonymous — i.e., there should be no mention of group members’
names anywhere in your submission.

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